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OMSim framework and geometry
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OMSim framework and geometry
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Common framework
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OMSim framework and geometry
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OMSim framework and geometry
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OMSim framework and geometry
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OMSim framework and geometry
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OMSim framework and geometry
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Classes
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OMSim framework and geometry
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Common framework
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Classes
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OMSim framework and geometry
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Common framework
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Classes
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OMSim framework and geometry
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Common framework
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Classes
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OMSim framework and geometry
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Common framework
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Classes
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OMSim framework and geometry
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Common framework
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Classes
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OMSim framework and geometry
+
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Common framework
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Classes
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OMSim framework and geometry
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Common framework
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Classes
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OMSim framework and geometry
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Common framework
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CustomProperties Class Reference
OMSim framework and geometry
+
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Common framework
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DEGG Class Reference
OMSim framework and geometry
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DEGG Class Reference
Common framework
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IceCubeIce Class Reference
OMSim framework and geometry
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Common framework
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OMSim framework and geometry
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Common framework
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OMSim framework and geometry
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Common framework
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OMSim framework and geometry
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OMSim framework and geometry
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Common framework
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OMSim framework and geometry
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OMSim framework and geometry
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diff --git a/class_o_m_sim_tracking_action-members.html b/class_o_m_sim_tracking_action-members.html index a45b740129..28f570e39b 100644 --- a/class_o_m_sim_tracking_action-members.html +++ b/class_o_m_sim_tracking_action-members.html @@ -129,7 +129,7 @@ diff --git a/class_o_m_sim_tracking_action.html b/class_o_m_sim_tracking_action.html index 06504b27e0..b29009b0ca 100644 --- a/class_o_m_sim_tracking_action.html +++ b/class_o_m_sim_tracking_action.html @@ -151,7 +151,7 @@ diff --git a/class_o_m_sim_u_iinterface-members.html b/class_o_m_sim_u_iinterface-members.html index a03be7d09e..a46a729198 100644 --- a/class_o_m_sim_u_iinterface-members.html +++ b/class_o_m_sim_u_iinterface-members.html @@ -136,7 +136,7 @@ diff --git a/class_o_m_sim_u_iinterface.html b/class_o_m_sim_u_iinterface.html index 3da02ff8bd..3008928a5f 100644 --- a/class_o_m_sim_u_iinterface.html +++ b/class_o_m_sim_u_iinterface.html @@ -120,7 +120,7 @@ Private Attributes | List of all members
-
OMSimUIinterface Class Reference
OMSim framework and geometry
+
OMSimUIinterface Class Reference
Common framework
@@ -417,7 +417,7 @@

  • OMSimUIinterface
    • -
  • Generated on Fri Jul 19 2024 07:25:23 for OMSim by doxygen 1.9.1
    • +
  • Generated on Mon Jul 22 2024 12:57:24 for OMSim by doxygen 1.9.1

diff --git a/class_parameter_table-members.html b/class_parameter_table-members.html index fa291cbf35..9f3e088bdf 100644 --- a/class_parameter_table-members.html +++ b/class_parameter_table-members.html @@ -135,7 +135,7 @@ diff --git a/class_parameter_table.html b/class_parameter_table.html index 474e84a43f..f2db464853 100644 --- a/class_parameter_table.html +++ b/class_parameter_table.html @@ -118,7 +118,7 @@ Private Attributes | List of all members
-
ParameterTable Class Reference
OMSim framework and geometry
+
ParameterTable Class Reference
Common framework
@@ -503,7 +503,7 @@

  • ParameterTable
    • -
  • Generated on Fri Jul 19 2024 07:25:23 for OMSim by doxygen 1.9.1
    • +
  • Generated on Mon Jul 22 2024 12:57:24 for OMSim by doxygen 1.9.1

diff --git a/class_reflective_surface-members.html b/class_reflective_surface-members.html index 990c4320ec..f1088168db 100644 --- a/class_reflective_surface-members.html +++ b/class_reflective_surface-members.html @@ -139,7 +139,7 @@ diff --git a/class_reflective_surface.html b/class_reflective_surface.html index 15efce32c4..7c1ce99111 100644 --- a/class_reflective_surface.html +++ b/class_reflective_surface.html @@ -118,7 +118,7 @@ Public Attributes | List of all members
-
ReflectiveSurface Class Reference
OMSim framework and geometry
+
ReflectiveSurface Class Reference
Common framework
@@ -275,7 +275,7 @@

  • ReflectiveSurface
    • -
  • Generated on Fri Jul 19 2024 07:25:23 for OMSim by doxygen 1.9.1
    • +
  • Generated on Mon Jul 22 2024 12:57:24 for OMSim by doxygen 1.9.1

diff --git a/class_refraction_and_absorption-members.html b/class_refraction_and_absorption-members.html index 1b4b615a1c..1180bd367f 100644 --- a/class_refraction_and_absorption-members.html +++ b/class_refraction_and_absorption-members.html @@ -142,7 +142,7 @@ diff --git a/class_refraction_and_absorption.html b/class_refraction_and_absorption.html index bf6c78f360..662ace8178 100644 --- a/class_refraction_and_absorption.html +++ b/class_refraction_and_absorption.html @@ -117,7 +117,7 @@ Public Member Functions | List of all members
-
RefractionAndAbsorption Class Reference
OMSim framework and geometry
+
RefractionAndAbsorption Class Reference
Common framework
@@ -211,7 +211,7 @@ diff --git a/class_refraction_only-members.html b/class_refraction_only-members.html index 4e0dd2bffd..ccb13cdd79 100644 --- a/class_refraction_only-members.html +++ b/class_refraction_only-members.html @@ -142,7 +142,7 @@ diff --git a/class_refraction_only.html b/class_refraction_only.html index 06fa9979c9..99f5b3256d 100644 --- a/class_refraction_only.html +++ b/class_refraction_only.html @@ -117,7 +117,7 @@ Public Member Functions | List of all members
-
RefractionOnly Class Reference
OMSim framework and geometry
+
RefractionOnly Class Reference
Common framework
@@ -211,7 +211,7 @@ diff --git a/class_s_n_base_particle_generator-members.html b/class_s_n_base_particle_generator-members.html index 820b51b2d2..08099f3f9d 100644 --- a/class_s_n_base_particle_generator-members.html +++ b/class_s_n_base_particle_generator-members.html @@ -146,7 +146,7 @@ diff --git a/class_s_n_base_particle_generator.html b/class_s_n_base_particle_generator.html index 8aabe0d8f6..e3fa1c2bb0 100644 --- a/class_s_n_base_particle_generator.html +++ b/class_s_n_base_particle_generator.html @@ -214,7 +214,7 @@ diff --git a/class_scintillation_properties-members.html b/class_scintillation_properties-members.html index 6df4428f69..182f52ace8 100644 --- a/class_scintillation_properties-members.html +++ b/class_scintillation_properties-members.html @@ -145,7 +145,7 @@ diff --git a/class_scintillation_properties.html b/class_scintillation_properties.html index 0de8095edd..e062c0d0b0 100644 --- a/class_scintillation_properties.html +++ b/class_scintillation_properties.html @@ -119,7 +119,7 @@ Private Attributes | List of all members
-
ScintillationProperties Class Reference
OMSim framework and geometry
+
ScintillationProperties Class Reference
Common framework
@@ -445,7 +445,7 @@

  • ScintillationProperties
    • -
  • Generated on Fri Jul 19 2024 07:25:23 for OMSim by doxygen 1.9.1
    • +
  • Generated on Mon Jul 22 2024 12:57:24 for OMSim by doxygen 1.9.1

diff --git a/classabc_data_file-members.html b/classabc_data_file-members.html index dd1537dcbf..f7a9fcf629 100644 --- a/classabc_data_file-members.html +++ b/classabc_data_file-members.html @@ -134,7 +134,7 @@ diff --git a/classabc_data_file.html b/classabc_data_file.html index 53562a3b2a..e9b4a21be5 100644 --- a/classabc_data_file.html +++ b/classabc_data_file.html @@ -120,7 +120,7 @@ Protected Attributes | List of all members
-
abcDataFile Class Referenceabstract
OMSim framework and geometry
+
abcDataFile Class Referenceabstract
Common framework
@@ -239,7 +239,7 @@

  • abcDataFile
    • -
  • Generated on Fri Jul 19 2024 07:25:22 for OMSim by doxygen 1.9.1
    • +
  • Generated on Mon Jul 22 2024 12:57:24 for OMSim by doxygen 1.9.1

diff --git a/classabc_detector_component-members.html b/classabc_detector_component-members.html index 5bd23a90d9..bab3919b9f 100644 --- a/classabc_detector_component-members.html +++ b/classabc_detector_component-members.html @@ -160,7 +160,7 @@ diff --git a/classabc_detector_component.html b/classabc_detector_component.html index 207e654ad1..47157017e6 100644 --- a/classabc_detector_component.html +++ b/classabc_detector_component.html @@ -120,7 +120,7 @@ Protected Attributes | List of all members
-
abcDetectorComponent Class Referenceabstract
OMSim framework and geometry
+
abcDetectorComponent Class Referenceabstract
Common framework
@@ -695,7 +695,7 @@

  • abcDetectorComponent
    • -
  • Generated on Fri Jul 19 2024 07:25:22 for OMSim by doxygen 1.9.1
    • +
  • Generated on Mon Jul 22 2024 12:57:24 for OMSim by doxygen 1.9.1

diff --git a/classabc_material_data-members.html b/classabc_material_data-members.html index 282be250fd..18ac9c7ec2 100644 --- a/classabc_material_data-members.html +++ b/classabc_material_data-members.html @@ -141,7 +141,7 @@ diff --git a/classabc_material_data.html b/classabc_material_data.html index e394f11823..019d144c24 100644 --- a/classabc_material_data.html +++ b/classabc_material_data.html @@ -119,7 +119,7 @@ Protected Member Functions | List of all members
-
abcMaterialData Class Referenceabstract
OMSim framework and geometry
+
abcMaterialData Class Referenceabstract
Common framework
@@ -265,7 +265,7 @@

  • abcMaterialData
    • -
  • Generated on Fri Jul 19 2024 07:25:22 for OMSim by doxygen 1.9.1
    • +
  • Generated on Mon Jul 22 2024 12:57:24 for OMSim by doxygen 1.9.1

diff --git a/classes.html b/classes.html index e6101d5c91..1bc1b3c08b 100644 --- a/classes.html +++ b/classes.html @@ -176,7 +176,7 @@ diff --git a/classm_d_o_m-members.html b/classm_d_o_m-members.html index 2d84179f39..0f0533def4 100644 --- a/classm_d_o_m-members.html +++ b/classm_d_o_m-members.html @@ -215,7 +215,7 @@ diff --git a/classm_d_o_m.html b/classm_d_o_m.html index 1374087968..c11498006c 100644 --- a/classm_d_o_m.html +++ b/classm_d_o_m.html @@ -575,7 +575,7 @@

  • mDOM
    • -
  • Generated on Fri Jul 19 2024 07:25:23 for OMSim by doxygen 1.9.1
    • +
  • Generated on Mon Jul 22 2024 12:57:24 for OMSim by doxygen 1.9.1
diff --git a/classm_d_o_m_flasher-members.html b/classm_d_o_m_flasher-members.html index 5dabd4db24..474f26f7c8 100644 --- a/classm_d_o_m_flasher-members.html +++ b/classm_d_o_m_flasher-members.html @@ -179,7 +179,7 @@ diff --git a/classm_d_o_m_flasher.html b/classm_d_o_m_flasher.html index 60af5ad926..a1ab6c07f4 100644 --- a/classm_d_o_m_flasher.html +++ b/classm_d_o_m_flasher.html @@ -119,7 +119,7 @@ Private Attributes | List of all members
-
mDOMFlasher Class Reference
OMSim framework and geometry
+
mDOMFlasher Class Reference
Common framework
@@ -462,7 +462,7 @@

  • mDOMFlasher
    • -
  • Generated on Fri Jul 19 2024 07:25:23 for OMSim by doxygen 1.9.1
    • +
  • Generated on Mon Jul 22 2024 12:57:24 for OMSim by doxygen 1.9.1

diff --git a/classm_d_o_m_harness-members.html b/classm_d_o_m_harness-members.html index 08ac5f6155..f2e340193e 100644 --- a/classm_d_o_m_harness-members.html +++ b/classm_d_o_m_harness-members.html @@ -180,7 +180,7 @@ diff --git a/classm_d_o_m_harness.html b/classm_d_o_m_harness.html index 027bf48cc4..daba0826dc 100644 --- a/classm_d_o_m_harness.html +++ b/classm_d_o_m_harness.html @@ -364,7 +364,7 @@

  • mDOMHarness
    • -
  • Generated on Fri Jul 19 2024 07:25:23 for OMSim by doxygen 1.9.1
    • +
  • Generated on Mon Jul 22 2024 12:57:24 for OMSim by doxygen 1.9.1
diff --git a/classm_d_o_m_p_m_t_response-members.html b/classm_d_o_m_p_m_t_response-members.html index e4add84ae0..995ead7104 100644 --- a/classm_d_o_m_p_m_t_response-members.html +++ b/classm_d_o_m_p_m_t_response-members.html @@ -154,7 +154,7 @@ diff --git a/classm_d_o_m_p_m_t_response.html b/classm_d_o_m_p_m_t_response.html index 30cd045265..d202df1a4e 100644 --- a/classm_d_o_m_p_m_t_response.html +++ b/classm_d_o_m_p_m_t_response.html @@ -228,7 +228,7 @@ diff --git a/classp_d_o_m-members.html b/classp_d_o_m-members.html index 1a95dae50d..3beeb5ef13 100644 --- a/classp_d_o_m-members.html +++ b/classp_d_o_m-members.html @@ -172,7 +172,7 @@ diff --git a/classp_d_o_m.html b/classp_d_o_m.html index 365d2e85a7..ea12615813 100644 --- a/classp_d_o_m.html +++ b/classp_d_o_m.html @@ -118,7 +118,7 @@ Public Attributes | List of all members
-
pDOM Class Reference
OMSim framework and geometry
+
pDOM Class Reference
Common framework
@@ -361,7 +361,7 @@

  • pDOM
    • -
  • Generated on Fri Jul 19 2024 07:25:23 for OMSim by doxygen 1.9.1
    • +
  • Generated on Mon Jul 22 2024 12:57:24 for OMSim by doxygen 1.9.1

diff --git a/dir_000001_000004.html b/dir_000001_000004.html index 317267fdb5..f8ecdd4912 100644 --- a/dir_000001_000004.html +++ b/dir_000001_000004.html @@ -119,7 +119,7 @@

geometry_construction → framework Relation

  • common
  • geometry_construction
    • -
  • Generated on Fri Jul 19 2024 07:25:23 for OMSim by doxygen 1.9.1
    • +
  • Generated on Mon Jul 22 2024 12:57:24 for OMSim by doxygen 1.9.1
diff --git a/dir_000002_000003.html b/dir_000002_000003.html index 1aae894655..0a9f701115 100644 --- a/dir_000002_000003.html +++ b/dir_000002_000003.html @@ -119,7 +119,7 @@

src → include Relation

  • common
  • geometry_construction
  • src
    • -
  • Generated on Fri Jul 19 2024 07:25:23 for OMSim by doxygen 1.9.1
    • +
  • Generated on Mon Jul 22 2024 12:57:24 for OMSim by doxygen 1.9.1
diff --git a/dir_000002_000004.html b/dir_000002_000004.html index cc5bac4654..fac2feff64 100644 --- a/dir_000002_000004.html +++ b/dir_000002_000004.html @@ -119,7 +119,7 @@

src → framework Relation

< diff --git a/dir_000003_000004.html b/dir_000003_000004.html index 536d3e6b68..03c877fc0e 100644 --- a/dir_000003_000004.html +++ b/dir_000003_000004.html @@ -119,7 +119,7 @@

include → framework Relation

diff --git a/dir_000005_000006.html b/dir_000005_000006.html index 4e0516b6e3..1a755d3f4d 100644 --- a/dir_000005_000006.html +++ b/dir_000005_000006.html @@ -119,7 +119,7 @@

src → include Relation

  • common
  • framework
  • src
    • -
  • Generated on Fri Jul 19 2024 07:25:23 for OMSim by doxygen 1.9.1
    • +
  • Generated on Mon Jul 22 2024 12:57:24 for OMSim by doxygen 1.9.1
diff --git a/dir_000007_000000.html b/dir_000007_000000.html index b71feb66db..3dde57fab6 100644 --- a/dir_000007_000000.html +++ b/dir_000007_000000.html @@ -119,7 +119,7 @@

effective_area → common Relation

  • effective_area
    • -
  • Generated on Fri Jul 19 2024 07:25:23 for OMSim by doxygen 1.9.1
    • +
  • Generated on Mon Jul 22 2024 12:57:24 for OMSim by doxygen 1.9.1
diff --git a/dir_000007_000011.html b/dir_000007_000011.html index f208b50b78..481cd50907 100644 --- a/dir_000007_000011.html +++ b/dir_000007_000011.html @@ -119,7 +119,7 @@

effective_area → include Relation

  • effective_area
    • -
  • Generated on Fri Jul 19 2024 07:25:23 for OMSim by doxygen 1.9.1
    • +
  • Generated on Mon Jul 22 2024 12:57:24 for OMSim by doxygen 1.9.1
diff --git a/dir_000008_000013.html b/dir_000008_000013.html index 34cfa39f30..4109975951 100644 --- a/dir_000008_000013.html +++ b/dir_000008_000013.html @@ -119,7 +119,7 @@

radioactive_decays → include Relation

  • radioactive_decays
    • -
  • Generated on Fri Jul 19 2024 07:25:23 for OMSim by doxygen 1.9.1
    • +
  • Generated on Mon Jul 22 2024 12:57:24 for OMSim by doxygen 1.9.1
diff --git a/dir_000010_000000.html b/dir_000010_000000.html index 5f58f9d4e2..79408d95d5 100644 --- a/dir_000010_000000.html +++ b/dir_000010_000000.html @@ -119,7 +119,7 @@

src → common Relation

  • effective_area
  • src
    • -
  • Generated on Fri Jul 19 2024 07:25:23 for OMSim by doxygen 1.9.1
    • +
  • Generated on Mon Jul 22 2024 12:57:24 for OMSim by doxygen 1.9.1
diff --git a/dir_000010_000011.html b/dir_000010_000011.html index 09cc667535..4fbbed362f 100644 --- a/dir_000010_000011.html +++ b/dir_000010_000011.html @@ -119,7 +119,7 @@

src → include Relation

  • effective_area
  • src
    • -
  • Generated on Fri Jul 19 2024 07:25:23 for OMSim by doxygen 1.9.1
    • +
  • Generated on Mon Jul 22 2024 12:57:24 for OMSim by doxygen 1.9.1
diff --git a/dir_000011_000000.html b/dir_000011_000000.html index 54382da1b6..3c07573598 100644 --- a/dir_000011_000000.html +++ b/dir_000011_000000.html @@ -119,7 +119,7 @@

include → common Relation

diff --git a/dir_000012_000000.html b/dir_000012_000000.html index cd6312c08e..efcf4f3818 100644 --- a/dir_000012_000000.html +++ b/dir_000012_000000.html @@ -119,7 +119,7 @@

src → common Relation

  • radioactive_decays
  • src
    • -
  • Generated on Fri Jul 19 2024 07:25:23 for OMSim by doxygen 1.9.1
    • +
  • Generated on Mon Jul 22 2024 12:57:24 for OMSim by doxygen 1.9.1
diff --git a/dir_000012_000013.html b/dir_000012_000013.html index 9ec476619c..960ce0809f 100644 --- a/dir_000012_000013.html +++ b/dir_000012_000013.html @@ -119,7 +119,7 @@

src → include Relation

  • radioactive_decays
  • src
    • -
  • Generated on Fri Jul 19 2024 07:25:23 for OMSim by doxygen 1.9.1
    • +
  • Generated on Mon Jul 22 2024 12:57:24 for OMSim by doxygen 1.9.1
diff --git a/dir_000013_000000.html b/dir_000013_000000.html index d3f77fbeb1..1cc3bf4a34 100644 --- a/dir_000013_000000.html +++ b/dir_000013_000000.html @@ -119,7 +119,7 @@

include → common Relation

diff --git a/dir_000014_000000.html b/dir_000014_000000.html index 860545affa..0ea7f747b9 100644 --- a/dir_000014_000000.html +++ b/dir_000014_000000.html @@ -119,7 +119,7 @@

src → common Relation

  • supernova
  • src
    • -
  • Generated on Fri Jul 19 2024 07:25:23 for OMSim by doxygen 1.9.1
    • +
  • Generated on Mon Jul 22 2024 12:57:24 for OMSim by doxygen 1.9.1
diff --git a/dir_000014_000015.html b/dir_000014_000015.html index abf059b1db..240c4b1b10 100644 --- a/dir_000014_000015.html +++ b/dir_000014_000015.html @@ -119,7 +119,7 @@

src → include Relation

  • supernova
  • src
    • -
  • Generated on Fri Jul 19 2024 07:25:23 for OMSim by doxygen 1.9.1
    • +
  • Generated on Mon Jul 22 2024 12:57:24 for OMSim by doxygen 1.9.1
diff --git a/dir_000015_000000.html b/dir_000015_000000.html index 8e29b6d794..69ff8479db 100644 --- a/dir_000015_000000.html +++ b/dir_000015_000000.html @@ -119,7 +119,7 @@

include → common Relation

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@@ -129,7 +129,7 @@ diff --git a/effective__area_2include_2_o_m_sim_event_action_8hh_source.html b/effective__area_2include_2_o_m_sim_event_action_8hh_source.html index b514f2ce37..18ae737117 100644 --- a/effective__area_2include_2_o_m_sim_event_action_8hh_source.html +++ b/effective__area_2include_2_o_m_sim_event_action_8hh_source.html @@ -173,7 +173,7 @@ diff --git a/effective__area_2include_2_o_m_sim_physics_list_8hh_source.html b/effective__area_2include_2_o_m_sim_physics_list_8hh_source.html index 6794512979..02b8835cb7 100644 --- a/effective__area_2include_2_o_m_sim_physics_list_8hh_source.html +++ b/effective__area_2include_2_o_m_sim_physics_list_8hh_source.html @@ -150,7 +150,7 @@ diff --git a/effective__area_2include_2_o_m_sim_primary_generator_action_8hh_source.html b/effective__area_2include_2_o_m_sim_primary_generator_action_8hh_source.html index 1ae8393546..e9ccc76fbf 100644 --- a/effective__area_2include_2_o_m_sim_primary_generator_action_8hh_source.html +++ b/effective__area_2include_2_o_m_sim_primary_generator_action_8hh_source.html @@ -145,7 +145,7 @@ diff --git a/files.html b/files.html index 671f83495f..a7c19faf59 100644 --- a/files.html +++ b/files.html @@ -119,66 +119,62 @@
Here is a list of all documented files with brief descriptions:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
 0common.h
 1effectiveArea.h
 2radioactive.h
 3SN.h
 4bubble.h
 abcDetectorComponent.hhProvides helper base class abcDetectorComponent for constructing and managing detector components in OMSim
 CADMesh.hh
 OMSim.ccImplementation of the OMSim class
 OMSim.hhMain simulation class for the Optical Module (OM) simulation. This file defines the OMSim class, which controls the entire simulation process in all studies and includes the general program options
 OMSim_effective_area.ccMain for the calculation of effective areas
 OMSim_radioactive_decays.ccMain of the radioactive decay study
 OMSim_supernova.ccMain of the supernova study
 OMSimActionInitialization.hh
 OMSimAngularScan.hhDefines the AngularScan class for configuring and running GPS beam with angular scans
 OMSimCommandArgsTable.hhDefinition of the OMSimCommandArgsTable singleton class, which controls user args
 OMSimDataFileTypes.hhCollection of classes and methods to handle material creation from user data in json files
 OMSimDecaysAnalysis.hhDefines the OMSimDecaysAnalysis class and DecayStats struct for the radioactive decays simulation
 OMSimDecaysGPS.hhDefines the OMSimDecaysGPS class for the radioactive decays simulation
 OMSimDEGG.hhConstruction of the DEGG class. From DOUMEKI
 OMSimDEGGHarness.hhConstruction of the DEGG harness
 OMSimDetectorConstruction.hh
 OMSimEffectiveAreaAnalyisis.hh
 OMSimEffectiveAreaDetector.hhDefines the OMSimEffectiveAreaDetector class for effective area simulation detector construction
 effective_area/include/OMSimEventAction.hh
 radioactive_decays/include/OMSimEventAction.hhDefines the OMSimEventAction and EventInfoManager classes for the radioactive decays simulation
 supernova/include/OMSimEventAction.hh
 OMSimG4RadioactiveDecay.hhModified version of the original Geant4 RadioactiveDecay class to define custom decay time
 OMSimG4Scintillation.hhOriginal Geant4 scintillation class modified to accept unlimited number of lifetimes
 OMSimHitManager.hhDefines structures and classes related to optical module photon hit management
 OMSimInputData.hhDefinition of ParameterTable and InputDataManager
 OMSimLogger.hh
 OMSimLOM16.hhConstruction of LOM16
 OMSimLOM18.cc
 OMSimLOM18.hhConstruction of LOM18
 OMSimMDOM.hhConstruction of mDOM
 OMSimMDOMFlasher.hhDefines the mDOMFlasher class for simulating the 10 flashers in an mDOM optical module
 OMSimMDOMHarness.hhConstruction of mDOM harness
 OMSimOpticalModule.hh
 OMSimPDOM.hhImplementation of the pDOM/Gen1 DOM class
 effective_area/include/OMSimPhysicsList.hh
 radioactive_decays/include/OMSimPhysicsList.hhDefines the OMSimPhysicsList class for the radioactive decays simulation
 supernova/include/OMSimPhysicsList.hh
 OMSimPMTConstruction.hhConstruction of the PMTs
 OMSimPMTResponse.hhSimulation of PMT response
 effective_area/include/OMSimPrimaryGeneratorAction.hh
 radioactive_decays/include/OMSimPrimaryGeneratorAction.hhDefines a simple OMSimPrimaryGeneratorAction class for the radioactive decays simulation using GPS
 supernova/include/OMSimPrimaryGeneratorAction.hh
 OMSimPrimaryGeneratorMessenger.ccPrimary generator messenger to choose the corresponding primary generator
 OMSimPrimaryGeneratorMessenger.hh
 OMSimRadDecaysDetector.hhDefines the OMSimRadDecaysDetector class for the radioactive decays simulation
 OMSimRunAction.hh
 OMSimSensitiveDetector.hh
 OMSimSNAnalysis.ccAnalyze data and write output files
 OMSimSNAnalysis.hh
 OMSimSNdetector.hh
 OMSimSNParticleGenerators.hhThis file contains the classes in charge of particle generation
 OMSimSNTools.hhProvides the definition for the OMSimSNTools class, centralizing utility methods for Supernova (SN) neutrino interactions
 OMSimSteppingAction.hhDefines OMSimSteppingAction.Currently it only checks for trapped photons
 OMSimTrackingAction.hh
 OMSimUIinterface.hh
 5_group_definitions.h
 abcDetectorComponent.hhProvides helper base class abcDetectorComponent for constructing and managing detector components in OMSim
 CADMesh.hh
 OMSim.ccImplementation of the OMSim class
 OMSim.hhMain simulation class for the Optical Module (OM) simulation. This file defines the OMSim class, which controls the entire simulation process in all studies and includes the general program options
 OMSim_effective_area.ccMain for the calculation of effective areas
 OMSim_radioactive_decays.ccMain of the radioactive decay study
 OMSim_supernova.ccMain of the supernova study
 OMSimActionInitialization.hh
 OMSimAngularScan.hhDefines the AngularScan class for configuring and running GPS beam with angular scans
 OMSimCommandArgsTable.hhDefinition of the OMSimCommandArgsTable singleton class, which controls user args
 OMSimDataFileTypes.hhCollection of classes and methods to handle material creation from user data in json files
 OMSimDecaysAnalysis.hhDefines the OMSimDecaysAnalysis class and DecayStats struct for the radioactive decays simulation
 OMSimDecaysGPS.hhDefines the OMSimDecaysGPS class for the radioactive decays simulation
 OMSimDEGG.hhConstruction of the DEGG class. From DOUMEKI
 OMSimDEGGHarness.hhConstruction of the DEGG harness
 OMSimDetectorConstruction.hh
 OMSimEffectiveAreaAnalyisis.hh
 OMSimEffectiveAreaDetector.hhDefines the OMSimEffectiveAreaDetector class for effective area simulation detector construction
 effective_area/include/OMSimEventAction.hh
 radioactive_decays/include/OMSimEventAction.hhDefines the OMSimEventAction and EventInfoManager classes for the radioactive decays simulation
 supernova/include/OMSimEventAction.hh
 OMSimG4RadioactiveDecay.hhModified version of the original Geant4 RadioactiveDecay class to define custom decay time
 OMSimG4Scintillation.hhOriginal Geant4 scintillation class modified to accept unlimited number of lifetimes
 OMSimHitManager.hhDefines structures and classes related to optical module photon hit management
 OMSimInputData.hhDefinition of ParameterTable and InputDataManager
 OMSimLogger.hh
 OMSimLOM16.hhConstruction of LOM16
 OMSimLOM18.cc
 OMSimLOM18.hhConstruction of LOM18
 OMSimMDOM.hhConstruction of mDOM
 OMSimMDOMFlasher.hhDefines the mDOMFlasher class for simulating the 10 flashers in an mDOM optical module
 OMSimMDOMHarness.hhConstruction of mDOM harness
 OMSimOpticalModule.hh
 OMSimPDOM.hhImplementation of the pDOM/Gen1 DOM class
 effective_area/include/OMSimPhysicsList.hh
 radioactive_decays/include/OMSimPhysicsList.hhDefines the OMSimPhysicsList class for the radioactive decays simulation
 supernova/include/OMSimPhysicsList.hh
 OMSimPMTConstruction.hhConstruction of the PMTs
 OMSimPMTResponse.hhSimulation of PMT response
 effective_area/include/OMSimPrimaryGeneratorAction.hh
 radioactive_decays/include/OMSimPrimaryGeneratorAction.hhDefines a simple OMSimPrimaryGeneratorAction class for the radioactive decays simulation using GPS
 supernova/include/OMSimPrimaryGeneratorAction.hh
 OMSimPrimaryGeneratorMessenger.ccPrimary generator messenger to choose the corresponding primary generator
 OMSimPrimaryGeneratorMessenger.hh
 OMSimRadDecaysDetector.hhDefines the OMSimRadDecaysDetector class for the radioactive decays simulation
 OMSimRunAction.hh
 OMSimSensitiveDetector.hh
 OMSimSNAnalysis.ccAnalyze data and write output files
 OMSimSNAnalysis.hh
 OMSimSNdetector.hh
 OMSimSNParticleGenerators.hhThis file contains the classes in charge of particle generation
 OMSimSNTools.hhProvides the definition for the OMSimSNTools class, centralizing utility methods for Supernova (SN) neutrino interactions
 OMSimSteppingAction.hhDefines OMSimSteppingAction.Currently it only checks for trapped photons
 OMSimTrackingAction.hh
 OMSimUIinterface.hh
@@ -186,7 +182,7 @@ diff --git a/files_dup.js b/files_dup.js index b52faf77f3..bd4babb10f 100644 --- a/files_dup.js +++ b/files_dup.js @@ -1,10 +1,6 @@ var files_dup = [ - [ "0common.h", "0common_8h_source.html", null ], - [ "1effectiveArea.h", "1effective_area_8h_source.html", null ], - [ "2radioactive.h", "2radioactive_8h_source.html", null ], - [ "3SN.h", "3_s_n_8h_source.html", null ], - [ "4bubble.h", "4bubble_8h_source.html", null ], + [ "5_group_definitions.h", "5__group__definitions_8h_source.html", null ], [ "abcDetectorComponent.hh", "abc_detector_component_8hh.html", [ [ "Component", "structabc_detector_component_1_1_component.html", "structabc_detector_component_1_1_component" ] ] ], diff --git a/functions.html b/functions.html index 5a2f6b589b..fedbf2cbd3 100644 --- a/functions.html +++ b/functions.html @@ -147,7 +147,7 @@

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      diff --git a/functions_c.html b/functions_c.html index e7605a61d7..94eeb83dcd 100644 --- a/functions_c.html +++ b/functions_c.html @@ -228,7 +228,7 @@

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          diff --git a/functions_e.html b/functions_e.html index aaee98e03d..09885110d1 100644 --- a/functions_e.html +++ b/functions_e.html @@ -185,7 +185,7 @@

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            diff --git a/functions_f.html b/functions_f.html index 294751d5cb..157f12f02f 100644 --- a/functions_f.html +++ b/functions_f.html @@ -135,7 +135,7 @@

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              diff --git a/functions_func.html b/functions_func.html index ab8ce249df..234390dd62 100644 --- a/functions_func.html +++ b/functions_func.html @@ -147,7 +147,7 @@

              - a -

                diff --git a/functions_func_b.html b/functions_func_b.html index 1cc17c853b..f95110476b 100644 --- a/functions_func_b.html +++ b/functions_func_b.html @@ -125,7 +125,7 @@

                - b -

                  diff --git a/functions_func_c.html b/functions_func_c.html index 34b7b88ca1..9af0dce288 100644 --- a/functions_func_c.html +++ b/functions_func_c.html @@ -228,7 +228,7 @@

                  - c -

                    diff --git a/functions_func_d.html b/functions_func_d.html index 381fd18447..a7be400f4b 100644 --- a/functions_func_d.html +++ b/functions_func_d.html @@ -131,7 +131,7 @@

                    - d -

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                      - e -

                        diff --git a/functions_func_f.html b/functions_func_f.html index 27386b4c6e..c8f464c016 100644 --- a/functions_func_f.html +++ b/functions_func_f.html @@ -132,7 +132,7 @@

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                            diff --git a/functions_func_h.html b/functions_func_h.html index 09191e991f..c900b3a660 100644 --- a/functions_func_h.html +++ b/functions_func_h.html @@ -131,7 +131,7 @@

                            - h -

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                                diff --git a/functions_func_l.html b/functions_func_l.html index b95dc4e3af..7c24a37a67 100644 --- a/functions_func_l.html +++ b/functions_func_l.html @@ -125,7 +125,7 @@

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                                  diff --git a/functions_func_m.html b/functions_func_m.html index 2fc9af5baa..508b02e308 100644 --- a/functions_func_m.html +++ b/functions_func_m.html @@ -131,7 +131,7 @@

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                                    diff --git a/functions_func_n.html b/functions_func_n.html index cf67534092..1f45aa9f0f 100644 --- a/functions_func_n.html +++ b/functions_func_n.html @@ -125,7 +125,7 @@

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                                            diff --git a/functions_func_s.html b/functions_func_s.html index df33d3b243..149c07c2e7 100644 --- a/functions_func_s.html +++ b/functions_func_s.html @@ -206,7 +206,7 @@

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                                                diff --git a/functions_func_u.html b/functions_func_u.html index d7540f019e..6f3d5dff6a 100644 --- a/functions_func_u.html +++ b/functions_func_u.html @@ -125,7 +125,7 @@

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                                                  diff --git a/functions_func_w.html b/functions_func_w.html index 45fb2f232d..d7c94898a3 100644 --- a/functions_func_w.html +++ b/functions_func_w.html @@ -146,7 +146,7 @@

                                                  - w -

                                                    diff --git a/functions_func_~.html b/functions_func_~.html index baa4f9683f..e6c2cfe964 100644 --- a/functions_func_~.html +++ b/functions_func_~.html @@ -128,7 +128,7 @@

                                                    - ~ -

                                                      diff --git a/functions_g.html b/functions_g.html index fd829dcfc7..29ea0db993 100644 --- a/functions_g.html +++ b/functions_g.html @@ -238,7 +238,7 @@

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                                                        diff --git a/functions_h.html b/functions_h.html index 67ef807ec1..0e19c919d3 100644 --- a/functions_h.html +++ b/functions_h.html @@ -134,7 +134,7 @@

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                                                                              diff --git a/functions_u.html b/functions_u.html index 31480214d1..221279061c 100644 --- a/functions_u.html +++ b/functions_u.html @@ -125,7 +125,7 @@

                                                                              - u -

                                                                                diff --git a/functions_v.html b/functions_v.html index ad2a69f9de..b1e6b830fc 100644 --- a/functions_v.html +++ b/functions_v.html @@ -128,7 +128,7 @@

                                                                                - v -

                                                                                  diff --git a/functions_vars.html b/functions_vars.html index eed955125d..fa582bfde3 100644 --- a/functions_vars.html +++ b/functions_vars.html @@ -364,7 +364,7 @@

                                                                                  - w -

                                                                                    diff --git a/functions_w.html b/functions_w.html index 5937cfc7bf..a4c659f19f 100644 --- a/functions_w.html +++ b/functions_w.html @@ -149,7 +149,7 @@

                                                                                    - w -

                                                                                      diff --git a/functions_~.html b/functions_~.html index 329d373ed9..8ec53f428b 100644 --- a/functions_~.html +++ b/functions_~.html @@ -128,7 +128,7 @@

                                                                                      - ~ -

                                                                                        diff --git a/globals.html b/globals.html index f49cc5ba7b..6f0a4be6bf 100644 --- a/globals.html +++ b/globals.html @@ -131,7 +131,7 @@ diff --git a/globals_defs.html b/globals_defs.html index 6d204433b3..1e5b89f312 100644 --- a/globals_defs.html +++ b/globals_defs.html @@ -123,7 +123,7 @@ diff --git a/globals_func.html b/globals_func.html index 1ab4b2eb5d..3913e69e91 100644 --- a/globals_func.html +++ b/globals_func.html @@ -128,7 +128,7 @@ diff --git a/graph_legend.html b/graph_legend.html index 94c8604f29..3e8526e307 100644 --- a/graph_legend.html +++ b/graph_legend.html @@ -182,7 +182,7 @@ diff --git a/group___effective_area.html b/group___effective_area.html index 0610969589..4e2d20744c 100644 --- a/group___effective_area.html +++ b/group___effective_area.html @@ -130,43 +130,6 @@

                                                                                        Detailed Description

                                                                                        -
                                                                                        Note
                                                                                        In the following a short introduction of an effective area study is made with the mDOM as an example. For further details see Chapter 10 of Lew Classen's thesis or Section 9.3.5 of Martin Unland's thesis.
                                                                                        -

                                                                                        During the design of a module its sensitivity is optimised by considering the optical properties of various materials and altering the geometry and positioning of the mechanical components in the Geant4 simulation. The metric to optimise the module's sensitivity is the effective area \(A_{\mathrm{eff}}(\theta, \phi)\). This represents the area that is detected from a plane wave of incidence angle of \(\theta\) (zenith) and \(\phi\) (azimuth) with respect to the module. This parameter is calculated with OMSim by simulating a disk emitting mono-energetic photons perpendicular to its surface with a uniform density profile. The photon generation is made with the module AngularScan, running the method AngularScan::runSingleAngularScan once for each direction to be investigated


                                                                                        - Figure 1: Screenshot of an mDOM illuminated by a disk emitter simulating the incidence of a plane wave from the direction \(\theta\) (zenith) and \(\phi\) (azimuth) using the Geant4 visualiser. The photon trajectories are represented by orange lines, and yellow dots mark the locations of physical interactions. Image from this thesis.

                                                                                        After simulating $N$ photons from a plane of area \(A_{\mathrm{rad}}\) (which has to be larger than the projected area of the mDOM), the effective area is calculated as

                                                                                        -\[ A_{\mathrm{eff}}(\theta, \phi) = \frac{N_{\mathrm{det}}(\theta, \phi)}{N}\cdot A_{\mathrm{rad}}, \] -

                                                                                        -

                                                                                        where \(N_{\mathrm{det}}\) is the number of photons detected by the module. To optimise the sensitivity over multiple directions, \(A_{\mathrm{eff}}(\theta, \phi)\) is calculated for various angle pairs, and the mean effective area, \(\overline{A}_{\mathrm{eff}}\), is determined. The \(n\) angle pairs are chosen using healpix, which separates a sphere into \(n\) pixels of equal area. Thus,

                                                                                        -\[ \overline{A}_{\mathrm{eff}} = \frac{1}{n}\sum_{i=1}^n A_{\mathrm{eff}}(\theta_i, \phi_i). \] -

                                                                                        -

                                                                                        Since the effective area is wavelength dependent, the calculation must be repeated for different wavelengths. Wavelengths shorter than 300nm are absorbed by the pressure vessel, whereas the QE of the PMT approaches zero at wavelengths longer than 700nm.

                                                                                        -

                                                                                        -Example using healpy

                                                                                        -

                                                                                        In the following a toy example of the usage of the effective area module is given. Although there are c++ healpix libraries, in my opinion the easiest way of getting the angle pair coordinates is using Healpy in python.

                                                                                        -

                                                                                        In principle for short simulations you could run the program directly from python using the angles from healpy as input parameters:

                                                                                        import healpy as hp
                                                                                        -
                                                                                        import numpy as np
                                                                                        -
                                                                                        from os import system
                                                                                        -
                                                                                        -
                                                                                        NSIDE = 8 #only powers of 2 allowed, the larger, the more pixels are calculated
                                                                                        -
                                                                                        NPIX = hp.nside2npix(NSIDE)
                                                                                        -
                                                                                        thetas, phis = np.degrees(hp.pix2ang(nside=NSIDE, ipix=np.arange(NPIX)))
                                                                                        -
                                                                                        -
                                                                                        for i, (theta, phi) in enumerate(zip(thetas, phis)):
                                                                                        -
                                                                                        if i==0:
                                                                                        -
                                                                                        system(f"./OMSim_effective_area -n 10000 --environment 1 -r 300 -t {theta} -f {phi} --output_file output")
                                                                                        -
                                                                                        else:
                                                                                        -
                                                                                        system(f"./OMSim_effective_area -n 10000 --environment 1 -r 300 -t {theta} -f {phi} --output_file output --no_header")
                                                                                        -

                                                                                        However, this is very inefficient. The best is to save the angle pairs into a file and pass it as argument. If you give a file as argument, the arg theta and phi are ignored.

                                                                                        -
                                                                                        import healpy as hp
                                                                                        -
                                                                                        import numpy as np
                                                                                        -
                                                                                        from os import system
                                                                                        -
                                                                                        -
                                                                                        NSIDE = 8 #only powers of 2 allowed, the larger, the more pixels are calculated
                                                                                        -
                                                                                        NPIX = hp.nside2npix(NSIDE)
                                                                                        -
                                                                                        thetas, phis = np.degrees(hp.pix2ang(nside=NSIDE, ipix=np.arange(NPIX)))
                                                                                        -
                                                                                        fname = "angle_pairs.txt"
                                                                                        -
                                                                                        np.savetxt(fname, np.column_stack((thetas, phis)))
                                                                                        -
                                                                                        system(f"./OMSim_effective_area -n 10000 --environment 1 -r 300 --angles_file {fname} --output_file output")
                                                                                        -

                                                                                        In my PC the first code block needs 51 seconds (tested with NSIDE=2) , the second block only 14 seconds (as simulation has to be initialised only once).

                                                                                        @@ -209,7 +172,7 @@

                                                                                        diff --git a/group__common.html b/group__common.html index 4f6e98b1d6..bdd3bbf61e 100644 --- a/group__common.html +++ b/group__common.html @@ -5,7 +5,7 @@ -OMSim: OMSim framework and geometry +OMSim: Common framework @@ -117,61 +117,13 @@ Files | Classes
                                                                                        -
                                                                                        OMSim framework and geometry
                                                                                        +
                                                                                        Common framework

                                                                                        These files define the geometry and materials common to all studies. More...

                                                                                        Detailed Description

                                                                                        -

                                                                                        -OMSim framework

                                                                                        -

                                                                                        -Materials and User Data

                                                                                        -

                                                                                        User-defined material data are stored in JSON files under /common/data to minimize file length (the original detector construction had over 4,000 lines, mainly due to material properties!). The InputDataManager (OMSimInputData.hh) loads these properties directly into the Geant4 framework. Materials loaded via this class can be retrieved using Geant4's conventional method G4Material::GetMaterial, but the framework also provides the wrapper InputDataManager::getMaterial to handle default parameters. The class also provides an analogue method for optical surfaces InputDataManager::getOpticalSurface which does not exists in Geant4.

                                                                                        -

                                                                                        Since different materials have different type of properties, the data is loaded in multiple ways. These different material types are defined in OMSimDataFileTypes.hh. Additionally, geometry data used during PMT construction are also stored in JSON files (/common/data/PMTs). These are saved in a "tree" (essentially a dictionary containing the JSON file's keys and values) in InputDataManager::mTable. This approach was adopted because various PMTs are constructed similarly, eliminating the need to define a unique class for each PMT type, as is done for the optical modules. Thus, an instance of InputDataManager is passed always to all classes related to geometry construction (see geometry).

                                                                                        -

                                                                                        If you wish to load additional data, you can either define a new type in OMSimDataFileTypes or load it into a tree as previously mentioned. For simpler tasks, use the static method InputDataManager::loadtxt, which operates similarly to Python's numpy.loadtxt. For example:

                                                                                        std::vector<G4PV2DDataVector> data = InputDataManager::loadtxt("path/file_name.txt");
                                                                                        -
                                                                                        std::vector<G4double> first_column = data.at(0);
                                                                                        -
                                                                                        std::vector<G4double> second_column = data.at(1);
                                                                                        -
                                                                                        // ...
                                                                                        -
                                                                                        InputDataManager::loadtxt
                                                                                        static std::vector< std::vector< double > > loadtxt(const std::string &pFilePath, bool pUnpack=true, size_t pSkipRows=0, char pDelimiter=' ')
                                                                                        Reads numerical data from a file and returns it as a 2D vector. Similar to numpy.loadtxt.
                                                                                        Definition: OMSimInputData.cc:135
                                                                                        -

                                                                                        -Geometry construction

                                                                                        -

                                                                                        Each optical module and harness is defined in its respective class, located in the /common/geometry_construction/ folder. These inherit from the virtual base class OMSimOpticalModule. This inheritance ensures the definition of functions to retrieve the pressure vessel's weight (necessary for radioactive decay studies) and the count of PMTs inside the module. The OMSimOpticalModule interface inherits from abcDetectorComponent, a general helper class simplifying construction. Most OMSim geometries inherit from this class, as illustrated in the dependency diagram below: -

                                                                                        - Inheritance diagram -
                                                                                        -

                                                                                        -

                                                                                        The OMSimPMTConstruction class constructs PMTs. There are two PMT construction approaches. The first is simple, with a solid photocathode where all entering photons are recorded. The second type simulates the photocathode as a thin layer, also representing the internal components accounting for internal reflections. For more information, refer to Chapter 9 of Martin Unland's thesis. The construction of different PMT models (e.g. the 3'' or 10'' PMTs) is quite similar. However, the frontal window shape varies among models, leading to diverse combinations of ellipsoids and spheres.

                                                                                        -

                                                                                        - Figure 1: Cross section of simple mDOM PMT model. Image from M. Unland's thesis.

                                                                                        - Figure 2: Side view of complex mDOM PMT model. Image from M. Unland's thesis.

                                                                                        In the complex PMT model the photocathode has an absorption length that matches the measured quantum efficiency of the mDOM PMTs. For the other PMT models this matching has to be still be performed.

                                                                                        -

                                                                                        - Figure 3: QE of simulation with the absorption length currently used compared to measurements. Image from M. Unland's thesis.

                                                                                        -PMT Response and Saving Hits

                                                                                        -
                                                                                        Warning
                                                                                        Only the mDOM PMT currently supports a detailed PMT response.
                                                                                        -

                                                                                        For photon detection in both simple and complex geometries, the photons must be absorbed within the photocathode volume. The PMTs' photocathodes are made sensitive through the OMSimSensitiveDetector class, following Geant4's G4VSensitiveDetector pattern. This configuration is achieved by invoking OMSimOpticalModule::configureSensitiveVolume (or OMSimPMTConstruction::configureSensitiveVolume when simulating a single PMT). It is essential to invoke this method in the detector construction, as it needs the instance of OMSimDetectorConstruction to call G4VUserDetectorConstruction::SetSensitiveDetector for successful operation in Geant4 (refer to OMSimDetectorConstruction::registerSensitiveDetector).

                                                                                        -

                                                                                        Every step of a particle through the photocathode triggers the OMSimSensitiveDetector::ProcessHits method. It verifies if the particle is a photon and whether it was absorbed. For a deeper understanding of Geant4's philosophy concerning G4VSensitiveDetector, consult the Geant4 guide for application developers.

                                                                                        -

                                                                                        In OMSimPMTConstruction::configureSensitiveVolume, PMTs are associated with an instance of OMSimPMTResponse, contingent on the PMT under simulation. This class offers a precise PMT simulation by sampling from real measurements, obtaining the relative transit time, charge (in PE), and detection probability (using the measured scans from M. Unland's thesis). For detailes, refer to Section 9.3.4 of the linked thesis. This sampling is performed for every absorbed photon in OMSimSensitiveDetector::ProcessHits invoking OMSimPMTResponse::processPhotocathodeHit.


                                                                                        - Figure 4: PMT response compared to measurement for different light sources. Image from M. Unland's thesis.

                                                                                        The data of absorbed photons is managed by the OMSimHitManager singleton. To analyse and export this data, consult example methods like OMSimEffectiveAreaAnalyisis::writeScan and OMSimDecaysAnalysis::writeHitInformation for direction.

                                                                                        -

                                                                                        An additional feature allows for the direct application of a QE cut. This ensures that only absorbed photons passing the QE test are retained in OMSimHitManager. To enable this feature, provide the "QE_cut" argument via the command line. In this case OMSimSensitiveDetector::ProcessHits will call OMSimPMTResponse::passQE and break early if it returns false, without storing the photon information.

                                                                                        -
                                                                                        Note
                                                                                        In most scenarios, it's not recommended to use –QE_cut since it reduces your statistics. Its presence in OMSim is primarily for testing purposes. It's generally better to perform post-analysis using the saved OMSimPMTResponse::PMTPulse::detectionProbability for each absorbed photon.
                                                                                        -

                                                                                        -Making other volumes sensitive to photons

                                                                                        -

                                                                                        For some studies you might want a volume to detect photons, without this being necessarely a PMT. For such cases, the framework has a provision in place: use the OMSimSensitiveDetector and pass DetectorType::GeneralPhotonDetector as its constructor argument. In this case the OMSimSensitiveDetector::ProcessHits will use an instance NoResponse as PMT response, which is just a dummy placeholder.
                                                                                        - Remember to inform the OMSimHitManager that this detector is equivalent to "a single PMT", ensuring internal vector sizes adjust accordingly. This approach ensures a smooth integration of the photosensitive volume within the current system. Below is an example illustrating how this can be incorporated within the detector construction:

                                                                                        -
                                                                                        #include "OMSimSensitiveDetector.hh"
                                                                                        -
                                                                                        //... Assume the logical volume of your detector has been defined and is referred to as "lDetectorLV"
                                                                                        -
                                                                                        OMSimSensitiveDetector* lSensitiveDetector = new OMSimSensitiveDetector("myDetector", DetectorType::GeneralPhotonDetector);
                                                                                        -
                                                                                        OMSimHitManager lHitManager = OMSimHitManager::getInstance();
                                                                                        -
                                                                                        lHitManager.setNumberOfPMTs(1, lHitManager.getNextDetectorIndex());
                                                                                        -
                                                                                        registerSensitiveDetector(lDetectorLV, lSensitiveDetector);
                                                                                        -
                                                                                        OMSimHitManager
                                                                                        Manages detected photon information.
                                                                                        Definition: OMSimHitManager.hh:57
                                                                                        -
                                                                                        OMSimHitManager::getInstance
                                                                                        static OMSimHitManager & getInstance()
                                                                                        Returns the singleton instance of the OMSimHitManager.
                                                                                        Definition: OMSimHitManager.cc:17
                                                                                        -
                                                                                        OMSimHitManager::setNumberOfPMTs
                                                                                        void setNumberOfPMTs(int pNumberOfPMTs, int pModuleIndex=0)
                                                                                        Stores the number of PMTs in a module for correct data handling.
                                                                                        Definition: OMSimHitManager.cc:127
                                                                                        -
                                                                                        OMSimSensitiveDetector
                                                                                        Represents a sensitive detector.
                                                                                        Definition: OMSimSensitiveDetector.hh:51
                                                                                        -

                                                                                        In this case, OMSimSensitiveDetector::ProcessHits will store all absorbed photons. The number of photons absorbed will depend on the absorption length of the material connected to the logical volume. If there's a need to make a volume sensitive to particles other than photons, add a new entry to the DetectorType enum (in OMSimSensitiveDetector.hh) and incorporate a new method that handles this scenario in OMSimSensitiveDetector::ProcessHits. You might also track these particles in OMSimTrackingAction or OMSimSteppingAction, but using a class derived from G4VSensitiveDetector aligns with the philosophy of Geant4.

                                                                                        Files

                                                                                        @@ -300,7 +252,7 @@

                                                                                        diff --git a/group__common.js b/group__common.js index f3453aa0b6..693b8f2376 100644 --- a/group__common.js +++ b/group__common.js @@ -19,6 +19,9 @@ var group__common = [ "OMSimMDOMHarness.hh", "_o_m_sim_m_d_o_m_harness_8hh.html", null ], [ "OMSimPDOM.hh", "_o_m_sim_p_d_o_m_8hh.html", null ], [ "OMSim", "class_o_m_sim.html", [ + [ "Installing Geant4", "index.html#autotoc_md30", null ], + [ "Requirements", "index.html#autotoc_md31", null ], + [ "Compiling OMSim", "index.html#autotoc_md32", null ], [ "OMSim", "class_o_m_sim.html#afc01df8f57a1303823b79ffd79088a89", null ], [ "~OMSim", "class_o_m_sim.html#a61d63cc8b99c7ac89ecce97720fbb41a", null ], [ "configureLogger", "class_o_m_sim.html#a3e43df3d28f3e5e7cbec8a6e3ef1dcf5", null ], diff --git a/group__radioactive.html b/group__radioactive.html index 967a46cf14..cdf60cf4c8 100644 --- a/group__radioactive.html +++ b/group__radioactive.html @@ -130,18 +130,6 @@

                                                                                        Detailed Description

                                                                                        -
                                                                                        Warning
                                                                                        This study has been tested only for Vitrovex glass (mDOM/LOM16) and the 80mm mDOM PMTs. Okamoto glass (D-Egg/LOM18) is currently under investigation.
                                                                                        -

                                                                                        The simulation considers the measured scintillation parameters and the specific activity of the isotopes to provide insights into the behavior of OMs in both air and ice environments over a time window \(t_{w}\). The number of time windows simulated is given by the argument –numevents. The primary output is a timestamped list of detected photons, which can be utilized to compute parameters such as the module's expected dark rate. The simulation steps can be summarized as:

                                                                                          -
                                                                                        • Determining the number of decays within \(t_{w}\) based on measured data.
                                                                                          • -
                                                                                        • Initiating decay chains for each event by positioning an isotope randomly in the pressure vessel.
                                                                                          • -
                                                                                        • Assigning decay times from a uniform distribution within [0, \(t_{w}\)], in case the time difference between mother-daughter decay times surpasses \(t_{w}\).
                                                                                          • -
                                                                                        • Capturing photons detected by the PMTs for downstream analysis.
                                                                                          • -
                                                                                        -

                                                                                        Important customizations in the simulation involve the extension of Geant4's original scintillation class, facilitating the simulation of more complex decay processes (8 lifetimes), and the modification the G4RadioactiveDecay class which amends default decay time of isotopes. The scintillation properties of the mDOM glass were measured in the scope of several theses. For a summary check section 11.2 of this thesis.

                                                                                        -

                                                                                        Currently, there are two analysis modes:

                                                                                          -
                                                                                        • With the '–multiplicity_study' argument: After each \(t_{w}\) time window, the multiplicity is calculated and saved to a file. Raw data isn't stored, as multiplicity studies generally involve extended simulation durations, leading to large volumes of photon data.
                                                                                          • -
                                                                                        • Without the '–multiplicity_study' argument: Data pertaining to photons and decayed isotopes is saved to files.
                                                                                          • -

                                                                                        Files

                                                                                        @@ -199,7 +187,7 @@ diff --git a/group__sngroup.html b/group__sngroup.html index 7f1660aa4c..564bdbc950 100644 --- a/group__sngroup.html +++ b/group__sngroup.html @@ -124,84 +124,6 @@

                                                                                        Comprehensive analysis and simulations focusing on the detection of CCSN neutrinos with segmented sensors. More...

                                                                                        Detailed Description

                                                                                        -

                                                                                        This simulation is designed to emulate the detection of Core Collapse Supernova (CCSN or simply SN in the following) neutrinos using segmented sensors. It directly generates particles resulting from Inverse Beta Decay (IBD) and Electron Neutrino-Electron Elastic Scattering (ENES).

                                                                                        -
                                                                                          -
                                                                                        • IBD: \(\bar{\nu}_e + p \rightarrow n + e^+\)
                                                                                          • -
                                                                                        • ENES: \(\nu_e + e^- \rightarrow \nu_e + e^-\)
                                                                                          • -
                                                                                        -

                                                                                        In the IBD case, the outgoing neutron is not simulated; hence, the neutron capture process that might be detected is not included in the simulation. Each event is assigned a weight based on the interaction probability, detailed later on this page. By default, the surrounding ice is represented as a cylinder facing the CCSN, simplifying the weight calculations.

                                                                                        -

                                                                                        Although CCSN models incorporate neutrino oscillations, the default simulation does not include any oscillation scenario in the weight calculations.

                                                                                        -

                                                                                        - Figure 1: Diagram of the steps involved to generate the events for the simulation of CCSN neutrinos. The scheme is valid for both IBD and ENES, except for the threshold check. Here, stands for both electron from ENES or positron from IBD, and ν (este simbolo se vera bien?) for both electronic neutrino from ENES or electronic antineutrino from IBD.. Image from this thesis.

                                                                                        The detailed procedure for this simulation is comprehensively described in this thesis, specifically in section 6.4. Below is a summary extracted from this source, outlining the steps taken to generate the events:

                                                                                        -
                                                                                          -
                                                                                        1. Utilizing the models, the expected flux per area is calculated from the luminosity \(L(t)\) and the mean energy \(<E(t)>\) according to \begin{equation} \label{eq:fluxes} \Phi (t) = \frac{1}{4\pi d^2} \cdot \frac{L(t)}{<E(t)>}. \end{equation}
                                                                                          2. -
                                                                                        2. The distribution of \(\Phi (t)\) is used to sample a time \(t\) of the burst via the inverse CDF (Cumulative Distribution Function) method. All other sampling from distributions within this simulation also employs the inverse CDF method.
                                                                                          3. -
                                                                                        3. For the sampled time \(t\), the corresponding mean energy and mean squared energy are extracted from the models. These parameters contribute to the construction of the energy spectrum \(f(E,t)\), as elucidated in this paper.
                                                                                          4. -
                                                                                        4. The energy of the neutrino/antineutrino \(E_\nu\) is sampled from \(f(E,t)\). If the energy falls below the IBD threshold, the algorithm reverts to the second step.
                                                                                          5. -
                                                                                        5. From \(E_\nu\), the angular cross section is devised. This informs the sampling of the angle \(\theta\) between the incoming neutrino and the resulting \(e^-/e^+\). The \(\phi\) direction is randomly generated within the range of \(0\) to \(2\pi\).
                                                                                          6. -
                                                                                        6. The energy of \(e^-/e^+\) is deduced from \(\theta\) and \(E_\nu\). The interaction probability for such an event is ascertained using the total cross section, facilitating the computation of the interaction weight, as further described below.
                                                                                          7. -
                                                                                        7. The \(e^-/e^+\) is manifested at a random position within the ice volume.
                                                                                          8. -
                                                                                        -

                                                                                        -Input Parameters

                                                                                        -

                                                                                        Execute ./OMSim_supernova --help to display all possible input parameters.

                                                                                        -

                                                                                        A typical command to run the simulation is:

                                                                                        -

                                                                                        ./OMSim_supernova -n 100 --wheight 20 --wradius 20 --depth_pos 75 -o outputfilename --SNgun 0 --SNtype 0

                                                                                        -

                                                                                        -General Parameters

                                                                                        -

                                                                                        -n: Number of particles to be generated. --depth_pos: Index of the vector determining the depth of the simulated modules. Notable values include DustLayer=65, MeanICUProperties(approx)=75, and CleanestIce=88. The data is located in "common/data/Materials/IceCubeICE.dat". The "jDepth_spice" vector provides the depth, with depth_pos serving as the index. This selection affects the effective scattering and absorption lengths of the ice at the specified depth. -o: Output file name. By default, two output files are created: one containing the simulated event information, and another with detection data.

                                                                                        -

                                                                                        -SN Framework Parameters

                                                                                        -

                                                                                        --wheight: Height of the ice's simulated world cylinder. --wradius: Radius of the ice's simulated world cylinder. --SNgun: Chooses the interaction type (0 for IBD, 1 for ENES). --SNtype: Selects the CCSN model. Two models are currently available, provided by the Garching group. These models represent the expected fluxes from two CCSNs resulting in neutron stars, with different progenitor masses (27 and 9.6 solar masses). Simulations yielding this data can be found at https://arxiv.org/abs/1510.04643

                                                                                        -

                                                                                        -Fixed Energy Studies

                                                                                        -

                                                                                        This section allows users to manually set the mean energy of generated events by providing specific input parameters. For instance:

                                                                                        -

                                                                                        --SNfixEnergy --SNmeanE 10.0 --SNalpha 3.0

                                                                                        -

                                                                                        --SNfixEnergy: Acts as a flag parameter. When invoked, the simulation disregards the actual mean energy of neutrinos corresponding to the burst time. Instead, it adopts the mean energy and the pinching parameter specified by the subsequent two parameters. --SNmeanE: Specifies the mean energy of the neutrinos. --SNalpha: Defines the pinching parameter of the energy distribution (see this paper).

                                                                                        -

                                                                                        Consequently, the neutrinos' energy is sampled from the distribution, derived from these two parameters and the previously mentioned model.

                                                                                        -

                                                                                        -Output Files

                                                                                        -

                                                                                        Information regarding the files that contain data outputs and insights derived from the simulated neutrino events.

                                                                                        -

                                                                                        -X_info.dat

                                                                                        -

                                                                                        This file encapsulates data concerning each generated neutrino event. Each entry contains:

                                                                                        -

                                                                                        Time of the neutrino burst. Corresponding mean energy derived from the model. Sampled neutrino energy \(E_\nu\). \(\cos(\theta)\), where \(\theta\) is the angle between the incoming neutrino and the outgoing particle (e- or e+). Energy of the outgoing particle (e- or e+). Interaction weight, calculated using the formula:

                                                                                        -\[ W_{\mathrm{int}}(E_\nu) = \sigma(E) \cdot n_{\mathrm{target}} \cdot l, \] -

                                                                                        -

                                                                                        where: ** \(\sigma(E)\) is the total cross section for the interaction, ** \(n_{\mathrm{target}}\) is the number of targets available for the interaction in the ice, ** \(l\) is the length of the simulated cylindrical world.

                                                                                        -

                                                                                        -X_data.dat

                                                                                        -

                                                                                        This file contains the detection information. Its structure is designed to facilitate various trigger studies, allowing the examination of different time windows. Users might evaluate its structure for convenience, particularly if the trigger check is integrated within the simulation (requiring a predefined time window).

                                                                                        -

                                                                                        The default content structure is as follows:

                                                                                        -\[ \text{Total hits | Modules hit | PMTs hit | "...for each PMT hit..." | Module number | PMT number | Hits in that PMT | "...for each Hit..." | hit time |} \] -

                                                                                        -

                                                                                        Note that the number of columns varies per line, contingent on the number of photons detected for the simulated neutrinos.

                                                                                        -

                                                                                        -Weights

                                                                                        -

                                                                                        The output files contain the interaction weight. However, users should also consider a weight factor depending on the total flux and the number of simulated events. In the most general case of simulating a single depth and then extrapolating the results to the entire detector, another weight factor is needed. This factor accounts for the ice properties of the simulated depth with respect to the whole detector. This last factor decreases in importance when using high multiplicity conditions, since these events generally interact closer to the module, making the photons less sensitive to changes in the optical properties.

                                                                                        -

                                                                                        These weight factors can be added similarly as explained in this thesis, section 6.4.2.

                                                                                        -

                                                                                        The total weight is composed of 3 components: the interaction probability, the SN flux through the simulated volume, and the different optical properties of the modules at different depths:

                                                                                        -

                                                                                        \begin{equation} \label{eq:sn_weights} W = W_{\mathrm{int}}(E) \cdot W_{\mathrm{flux}}(d) \cdot W_{\mathrm{eff}}. \end{equation}

                                                                                        -

                                                                                        Each component is explained as follows:

                                                                                        -

                                                                                        -Interaction Probability Weight:

                                                                                        -

                                                                                        \begin{equation} \label{eq:sn_weight_int} W_{\mathrm{int}}(E_\nu) = \sigma(E) \cdot n_{\mathrm{target}} \cdot l, \end{equation} where \(\sigma(E_\nu)\) is the total cross section for the interaction, \(n_{\mathrm{target}}\) is the number of targets per unit of volume for such interaction, and \(l=40\,m\) is the length of the generation volume along the neutrino direction axis. This is the length of the cylinder facing the CCSN.

                                                                                        -

                                                                                        -Flux Weight:

                                                                                        -

                                                                                        \begin{equation} \label{eq:sn_weight_flux} W_{\mathrm{flux}}(d) = \frac{1}{N_{\mathrm{gen}}} \cdot \frac{r^2}{d^2} \cdot \int \frac{L(t)}{<E(t)>} dt, \end{equation} where \(r\) is the cylindrical generation volume’s radius, \(d\) is the distance from Earth where the CCSN is assumed to occur, and \(N_{\mathrm{gen}}\) is the number of generated events.

                                                                                        -

                                                                                        -Effective Weight:

                                                                                        -

                                                                                        \begin{equation} \label{eq:sn_weight_eff} W_{\mathrm{eff}} = N_{\mathrm{modules}} \cdot \frac{<V_{\mathrm{eff}}(m)>}{V_{\mathrm{eff}}(m,z_{\mathrm{sim}})}, \end{equation} where \(N_{\mathrm{modules}}\) is the total modules in the simulated detector, \(V_{\mathrm{eff}}(m, z_{\mathrm{sim}})\) is the effective volume at the simulation depth, and \(<V_{\mathrm{eff}}(m)>\) is the mean effective volume for all modules in simulated detector. The term \(m\) represents multiplicity, defined as the count of different PMTs within a single module that detected the event within a specific time window.

                                                                                        -

                                                                                        The effective volume can be calculated in different ways. Old simulations of the mDOM, described in this thesis, section 6.3, were used in past studies. A linear regression of the effective volume concerning the absorption length, derived from various depths, provides each depth's effective volume. Although it is advisable to redo these simulations with a current mDOM model, users can temporarily use the old data with a regression line of \(V_{\mathrm{eff}} = b \cdot x + c\), where \(x = 1/a\) is the inverse of the absorption length. The coefficients \(b\) and \(c\), depending on the event's multiplicity, were obtained as follows:

                                                                                        -
                                                                                        *  | multiplicity |     b (slope, m^2)         |      c (m^3)     |
-*  |--------------|----------------------------|------------------|
-*  |      1       |          15.1843           |       0.000      |
-*  |      2       |           0.1352           |      47.005      |
-*  |      3       |           0.0306           |      16.170      |
-*  |      4       |           0.0095           |       8.680      |
-*  |      5       |           0.0039           |       5.105      |
-*  |     >= 6     |           0.0026           |       2.909      |
-*

                                                                                        Note that, for more than 5 PMTs, the same fit line is employed due to insufficient statistics at higher PMTs in the effective volume simulation. Additionally, since the absorption length depends on the wavelength, the fits above were obtained assuming a wavelength of \(\lambda = 400\,nm\).

                                                                                        Files

                                                                                        @@ -238,7 +160,7 @@

                                                                                        diff --git a/hierarchy.html b/hierarchy.html index 2cabc8a0ba..cdeccde5ca 100644 --- a/hierarchy.html +++ b/hierarchy.html @@ -234,7 +234,7 @@ diff --git a/image.png b/image.png deleted file mode 100644 index 43e413d2ce..0000000000 Binary files a/image.png and /dev/null differ diff --git a/index.html b/index.html index d5edb40903..1449f63572 100644 --- a/index.html +++ b/index.html @@ -5,7 +5,7 @@ -OMSim: OMSim +OMSim: OMSim Geant4 Framework @@ -114,38 +114,38 @@
                                                                                        -
                                                                                        OMSim
                                                                                        +
                                                                                        OMSim Geant4 Framework

                                                                                        Table of Contents

                                                                                        -

                                                                                        Under construction. If you want to use OMSim contact martin.u in IC-slack...

                                                                                        OMSim is a Geant4 framework for the simulation of optical modules of the IceCube Observatory. It has been mostly developed by the Münster IceCube Group during different master and PhD theses. The project is separated into different modules depending on the study (e.g. background investigations with radioactive decays, or sensitivity studies). These modules share common files (in the "common" folder) which, for example, define geometries from modules and PMTs or also material properties.

                                                                                        Please check the different Modules in the documentation for further details and examples.

                                                                                        -

                                                                                        +

                                                                                        Installation

                                                                                        -

                                                                                        +

                                                                                        Installing Geant4

                                                                                        First you should install Geant4 following the guide provided by cern. OMSim is currently optimised for Geant4-11.1.1. If you want to use the visualisation tools of Geant, you should include the following cmake options:

                                                                                        -DGEANT4_INSTALL_DATA=ON -DGEANT4_USE_GDML=ON -DGEANT4_USE_OPENGL_X11=ON -DGEANT4_USE_QT=ON -DGEANT4_USE_RAYTRACER_X11=ON -DGEANT4_USE_XM=ON

                                                                                        Do not change "GEANT4_BUILD_MULTITHREADED" to OFF, as OMSim supports multithreading.

                                                                                        -

                                                                                        +

                                                                                        Requirements

                                                                                        There are a few dependencies. You can install them using the following command:

                                                                                        apt-get -y install libxerces-c-dev libxmu-dev libxpm-dev libglu1-mesa-dev qtbase5-dev libmotif-dev libargtable2-0 libboost-all-dev libqt53dextras5 libspdlog-dev libfmt-dev

                                                                                        If you needed to install more, add a comment it in the Git project, so we can complete the above command 😊

                                                                                        Also you will need ROOT. Download the last binary (e.g. at time of writing latest version is 6.28/04 https://root.cern/releases/release-62804/), or compile the source distribution. For simplicity add the source in your .bashrc (or you will have to source it yourself manually every time you run or compile OMSim):

                                                                                        export ROOTSYS= YOUR_ROOT_PATH
                                                                                        source $ROOTSYS/bin/thisroot.sh
                                                                                        -

                                                                                        +

                                                                                        Compiling OMSim

                                                                                        • Clone this branch.
                                                                                          • @@ -160,14 +160,13 @@

                                                                                        • Finally, just run make or make -j N where N is number of cores you want to use for the compilation.
                                                                                        -

                                                                                        +

                                                                                        Available studies

                                                                                        OMSim has been utilized in a range of studies, each simulating unique physics, thereby necessitating distinct Physicslist/analysis setups. In this repository, we have compiled a selection of these studies, each contained within its own folder and accompanied by its own main file. Currently available:

                                                                                        • Effective area: calculates the effective area of the optical modules/PMTs.
                                                                                        • Radioactive decays: simulates radioactive decays within the glass of the pressure vessel and the PMT glass. Essential for understanding the primary background of optical modules.
                                                                                        • Supernova studies: used for the development of an improved SN trigger for IceCube using multi-PMT modules.
                                                                                          • -
                                                                                        • Bubble column: used for investigating the capability of the mDOM flashers in determining bubble column parameters.

                                                                                        Most users will likely utilize just one of these studies, meaning there's no need to compile all of them. If you wish to exclude certain studies from compilation, you can comment out the undesired ones in the CMakeLists.txt between lines 41-43 (where the add_subdirectory commands are located).

                                                                                        @@ -176,7 +175,7 @@

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all documented files with brief descriptions\+:\begin{DoxyCompactList} -\item\contentsline{section}{{\bfseries 0common.\+h} }{\pageref{0common_8h}}{} -\item\contentsline{section}{{\bfseries 1effective\+Area.\+h} }{\pageref{1effective_area_8h}}{} -\item\contentsline{section}{{\bfseries 2radioactive.\+h} }{\pageref{2radioactive_8h}}{} -\item\contentsline{section}{{\bfseries 3\+SN.\+h} }{\pageref{3_s_n_8h}}{} -\item\contentsline{section}{{\bfseries 4bubble.\+h} }{\pageref{4bubble_8h}}{} +\item\contentsline{section}{{\bfseries 5\+\_\+group\+\_\+definitions.\+h} }{\pageref{5__group__definitions_8h}}{} \item\contentsline{section}{\mbox{\hyperlink{abc_detector_component_8hh}{abc\+Detector\+Component.\+hh}} \\*Provides helper base class \mbox{\hyperlink{classabc_detector_component}{abc\+Detector\+Component}} for constructing and managing detector components in \mbox{\hyperlink{class_o_m_sim}{OMSim}} }{\pageref{abc_detector_component_8hh}}{} \item\contentsline{section}{{\bfseries CADMesh.\+hh} }{\pageref{_c_a_d_mesh_8hh}}{} \item\contentsline{section}{\mbox{\hyperlink{_o_m_sim_8cc}{OMSim.\+cc}} \\*Implementation of the \mbox{\hyperlink{class_o_m_sim}{OMSim}} class }{\pageref{_o_m_sim_8cc}}{} diff --git a/latex/group___effective_area.pdf b/latex/group___effective_area.pdf index 7db234f7d0..44b3980bcb 100644 Binary files a/latex/group___effective_area.pdf and b/latex/group___effective_area.pdf differ diff --git a/latex/group___effective_area.tex b/latex/group___effective_area.tex index a7045ad1d5..62e179a1b7 100644 --- a/latex/group___effective_area.tex +++ b/latex/group___effective_area.tex @@ -16,55 +16,7 @@ \doxysubsection{Detailed Description} -\begin{DoxyNote}{Note} -In the following a short introduction of an effective area study is made with the \mbox{\hyperlink{classm_d_o_m}{m\+DOM}} as an example. For further details see Chapter 10 of \href{https://www.uni-muenster.de/imperia/md/content/physik_kp/agkappes/abschlussarbeiten/doktorarbeiten/1702-phd_lclassen.pdf}{\texttt{ Lew Classen\textquotesingle{}s thesis}} or Section 9.\+3.\+5 of \href{https://zenodo.org/record/8121321}{\texttt{ Martin Unland\textquotesingle{}s thesis}}. -\end{DoxyNote} -During the design of a module its sensitivity is optimised by considering the optical properties of various materials and altering the geometry and positioning of the mechanical components in the Geant4 simulation. The metric to optimise the module\textquotesingle{}s sensitivity is the effective area $A_{\mathrm{eff}}(\theta, \phi)$. This represents the area that is detected from a plane wave of incidence angle of $\theta$ (zenith) and $\phi$ (azimuth) with respect to the module. This parameter is calculated with \mbox{\hyperlink{class_o_m_sim}{OMSim}} by simulating a disk emitting mono-\/energetic photons perpendicular to its surface with a uniform density profile. The photon generation is made with the module \mbox{\hyperlink{class_angular_scan}{Angular\+Scan}}, running the method \mbox{\hyperlink{class_angular_scan_a465f642ebbe30fc94f9ed8ec6e554ef4}{Angular\+Scan\+::run\+Single\+Angular\+Scan}} once for each direction to be investigated ~\newline - Figure 1\+: {\itshape Screenshot of an \mbox{\hyperlink{classm_d_o_m}{m\+DOM}} illuminated by a disk emitter simulating the incidence of a plane wave from the direction $\theta$ (zenith) and $\phi$ (azimuth) using the Geant4 visualiser. The photon trajectories are represented by orange lines, and yellow dots mark the locations of physical interactions. Image from \href{https://zenodo.org/record/8121321}{\texttt{ this thesis}}.} - -After simulating \$N\$ photons from a plane of area $A_{\mathrm{rad}}$ (which has to be larger than the projected area of the \mbox{\hyperlink{classm_d_o_m}{m\+DOM}}), the effective area is calculated as \[ A_{\mathrm{eff}}(\theta, \phi) = \frac{N_{\mathrm{det}}(\theta, \phi)}{N}\cdot A_{\mathrm{rad}}, \] where $N_{\mathrm{det}}$ is the number of photons detected by the module. To optimise the sensitivity over multiple directions, $A_{\mathrm{eff}}(\theta, \phi)$ is calculated for various angle pairs, and the mean effective area, $\overline{A}_{\mathrm{eff}}$, is determined. The $n$ angle pairs are chosen using healpix, which separates a sphere into $n$ pixels of equal area. Thus, \[ \overline{A}_{\mathrm{eff}} = \frac{1}{n}\sum_{i=1}^n A_{\mathrm{eff}}(\theta_i, \phi_i). \] - -Since the effective area is wavelength dependent, the calculation must be repeated for different wavelengths. Wavelengths shorter than 300nm are absorbed by the pressure vessel, whereas the QE of the PMT approaches zero at wavelengths longer than 700nm.\hypertarget{group___effective_area_exampleEA}{}\doxysubsubsection{Example using healpy}\label{group___effective_area_exampleEA} -In the following a toy example of the usage of the effective area module is given. Although there are c++ healpix libraries, in my opinion the easiest way of getting the angle pair coordinates is using Healpy in python. - -In principle for short simulations you could run the program directly from python using the angles from healpy as input parameters\+: -\begin{DoxyCode}{0} -\DoxyCodeLine{\textcolor{keyword}{import} healpy \textcolor{keyword}{as} hp} -\DoxyCodeLine{\textcolor{keyword}{import} numpy \textcolor{keyword}{as} np} -\DoxyCodeLine{\textcolor{keyword}{from} os \textcolor{keyword}{import} system} -\DoxyCodeLine{} -\DoxyCodeLine{NSIDE = 8 \textcolor{comment}{\#only powers of 2 allowed, the larger, the more pixels are calculated}} -\DoxyCodeLine{NPIX = hp.nside2npix(NSIDE)} -\DoxyCodeLine{thetas, phis = np.degrees(hp.pix2ang(nside=NSIDE, ipix=np.arange(NPIX)))} -\DoxyCodeLine{} -\DoxyCodeLine{\textcolor{keywordflow}{for} i, (theta, phi) \textcolor{keywordflow}{in} enumerate(zip(thetas, phis)):} -\DoxyCodeLine{ \textcolor{keywordflow}{if} i==0:} -\DoxyCodeLine{ system(f\textcolor{stringliteral}{"{}./OMSim\_effective\_area -\/n 10000 -\/-\/environment 1 -\/r 300 -\/t \{theta\} -\/f \{phi\} -\/-\/output\_file output"{}})} -\DoxyCodeLine{ \textcolor{keywordflow}{else}:} -\DoxyCodeLine{ system(f\textcolor{stringliteral}{"{}./OMSim\_effective\_area -\/n 10000 -\/-\/environment 1 -\/r 300 -\/t \{theta\} -\/f \{phi\} -\/-\/output\_file output -\/-\/no\_header"{}})} - -\end{DoxyCode} - - -However, this is {\bfseries{very}} inefficient. The best is to save the angle pairs into a file and pass it as argument. If you give a file as argument, the arg theta and phi are ignored. - - -\begin{DoxyCode}{0} -\DoxyCodeLine{\textcolor{keyword}{import} healpy \textcolor{keyword}{as} hp} -\DoxyCodeLine{\textcolor{keyword}{import} numpy \textcolor{keyword}{as} np} -\DoxyCodeLine{\textcolor{keyword}{from} os \textcolor{keyword}{import} system} -\DoxyCodeLine{} -\DoxyCodeLine{NSIDE = 8 \textcolor{comment}{\#only powers of 2 allowed, the larger, the more pixels are calculated}} -\DoxyCodeLine{NPIX = hp.nside2npix(NSIDE)} -\DoxyCodeLine{thetas, phis = np.degrees(hp.pix2ang(nside=NSIDE, ipix=np.arange(NPIX)))} -\DoxyCodeLine{fname = \textcolor{stringliteral}{"{}angle\_pairs.txt"{}}} -\DoxyCodeLine{np.savetxt(fname, np.column\_stack((thetas, phis)))} -\DoxyCodeLine{system(f\textcolor{stringliteral}{"{}./OMSim\_effective\_area -\/n 10000 -\/-\/environment 1 -\/r 300 -\/-\/angles\_file \{fname\} -\/-\/output\_file output"{}})} - -\end{DoxyCode} - - -In my PC the first code block needs 51 seconds (tested with NSIDE=2) , the second block only 14 seconds (as simulation has to be initialised only once). \doxysubsection*{Files} +\doxysubsection*{Files} \begin{DoxyCompactItemize} \item file \mbox{\hyperlink{_o_m_sim_angular_scan_8hh}{OMSim\+Angular\+Scan.\+hh}} diff --git a/latex/group__bubble.tex b/latex/group__bubble.tex deleted file mode 100644 index 504a13dc2e..0000000000 --- a/latex/group__bubble.tex +++ /dev/null @@ -1,10 +0,0 @@ -\hypertarget{group__bubble}{}\doxysection{Bubble column} -\label{group__bubble}\index{Bubble column@{Bubble column}} - - -~\newline - - - - ~\newline - {\itshape Figure\+: A brief description of the image} \ No newline at end of file diff --git a/latex/group__common.tex b/latex/group__common.tex index 03a4162872..bce2c18f4e 100644 --- a/latex/group__common.tex +++ b/latex/group__common.tex @@ -1,5 +1,5 @@ -\hypertarget{group__common}{}\doxysection{OMSim framework and geometry} -\label{group__common}\index{OMSim framework and geometry@{OMSim framework and geometry}} +\hypertarget{group__common}{}\doxysection{Common framework} +\label{group__common}\index{Common framework@{Common framework}} These files define the geometry and materials common to all studies. @@ -8,65 +8,7 @@ \doxysubsection{Detailed Description} -\hypertarget{group__common_framework}{}\doxysubsubsection{OMSim framework}\label{group__common_framework} -\hypertarget{group__common_data}{}\doxyparagraph{Materials and User Data}\label{group__common_data} -User-\/defined material data are stored in JSON files under {\ttfamily /common/data} to minimize file length (the original detector construction had over 4,000 lines, mainly due to material properties!). The {\ttfamily \mbox{\hyperlink{class_input_data_manager}{Input\+Data\+Manager}}} (\mbox{\hyperlink{_o_m_sim_input_data_8hh}{OMSim\+Input\+Data.\+hh}}) loads these properties directly into the Geant4 framework. Materials loaded via this class can be retrieved using Geant4\textquotesingle{}s conventional method {\ttfamily G4\+Material\+::\+Get\+Material}, but the framework also provides the wrapper {\ttfamily \mbox{\hyperlink{class_input_data_manager_a970eddaab6756e6288504390454a38f4}{Input\+Data\+Manager\+::get\+Material}}} to handle default parameters. The class also provides an analogue method for optical surfaces {\ttfamily \mbox{\hyperlink{class_input_data_manager_ae6ae987535a442a42ad47d53394ade56}{Input\+Data\+Manager\+::get\+Optical\+Surface}}} which does not exists in Geant4. - -Since different materials have different type of properties, the data is loaded in multiple ways. These different material types are defined in \mbox{\hyperlink{_o_m_sim_data_file_types_8hh}{OMSim\+Data\+File\+Types.\+hh}}. Additionally, geometry data used during PMT construction are also stored in JSON files ({\ttfamily /common/data/\+PMTs}). These are saved in a \char`\"{}tree\char`\"{} (essentially a dictionary containing the JSON file\textquotesingle{}s keys and values) in {\ttfamily \mbox{\hyperlink{class_parameter_table_a749bc840cf2aea18fb5b63da8b68c23c}{Input\+Data\+Manager\+::m\+Table}}}. This approach was adopted because various PMTs are constructed similarly, eliminating the need to define a unique class for each PMT type, as is done for the optical modules. Thus, an instance of {\ttfamily \mbox{\hyperlink{class_input_data_manager}{Input\+Data\+Manager}}} is passed always to all classes related to geometry construction (see \mbox{\hyperlink{group__common_geometry}{geometry}}). - -If you wish to load additional data, you can either define a new type in OMSim\+Data\+File\+Types or load it into a tree as previously mentioned. For simpler tasks, use the static method {\ttfamily \mbox{\hyperlink{class_input_data_manager_a3a233522b61c65875ebb7b274ff31507}{Input\+Data\+Manager\+::loadtxt}}}, which operates similarly to Python\textquotesingle{}s numpy.\+loadtxt. For example\+: -\begin{DoxyCode}{0} -\DoxyCodeLine{std::vector data = \mbox{\hyperlink{class_input_data_manager_a3a233522b61c65875ebb7b274ff31507}{InputDataManager::loadtxt}}(\textcolor{stringliteral}{"{}path/file\_name.txt"{}});} -\DoxyCodeLine{std::vector first\_column = data.at(0);} -\DoxyCodeLine{std::vector second\_column = data.at(1);} -\DoxyCodeLine{\textcolor{comment}{// ...}} - -\end{DoxyCode} -\hypertarget{group__common_geometry}{}\doxyparagraph{Geometry construction}\label{group__common_geometry} -Each optical module and harness is defined in its respective class, located in the {\ttfamily /common/geometry\+\_\+construction/} folder. These inherit from the virtual base class {\ttfamily \mbox{\hyperlink{class_o_m_sim_optical_module}{OMSim\+Optical\+Module}}}. This inheritance ensures the definition of functions to retrieve the pressure vessel\textquotesingle{}s weight (necessary for radioactive decay studies) and the count of PMTs inside the module. The {\ttfamily \mbox{\hyperlink{class_o_m_sim_optical_module}{OMSim\+Optical\+Module}}} interface inherits from {\ttfamily \mbox{\hyperlink{classabc_detector_component}{abc\+Detector\+Component}}}, a general helper class simplifying construction. Most \mbox{\hyperlink{class_o_m_sim}{OMSim}} geometries inherit from this class, as illustrated in the dependency diagram below\+: - -The {\ttfamily \mbox{\hyperlink{class_o_m_sim_p_m_t_construction}{OMSim\+PMTConstruction}}} class constructs PMTs. There are two PMT construction approaches. The first is simple, with a solid photocathode where all entering photons are recorded. The second type simulates the photocathode as a thin layer, also representing the internal components accounting for internal reflections. For more information, refer to Chapter 9 of \href{https://zenodo.org/record/8121321}{\texttt{ Martin Unland\textquotesingle{}s thesis}}. The construction of different PMT models (e.\+g. the 3\textquotesingle{}\textquotesingle{} or 10\textquotesingle{}\textquotesingle{} PMTs) is quite similar. However, the frontal window shape varies among models, leading to diverse combinations of ellipsoids and spheres. - - ~\newline - Figure 1\+: {\itshape Cross section of simple \mbox{\hyperlink{classm_d_o_m}{m\+DOM}} PMT model. Image from \href{https://zenodo.org/record/8121321}{\texttt{ M. Unland\textquotesingle{}s thesis}}.} - - ~\newline - Figure 2\+: {\itshape Side view of complex \mbox{\hyperlink{classm_d_o_m}{m\+DOM}} PMT model. Image from \href{https://zenodo.org/record/8121321}{\texttt{ M. Unland\textquotesingle{}s thesis}}.} - -In the complex PMT model the photocathode has an absorption length that matches the measured quantum efficiency of the \mbox{\hyperlink{classm_d_o_m}{m\+DOM}} PMTs. For the other PMT models this matching has to be still be performed. - - ~\newline - Figure 3\+: {\itshape QE of simulation with the absorption length currently used compared to measurements. Image from \href{https://zenodo.org/record/8121321}{\texttt{ M. Unland\textquotesingle{}s thesis}}.} \hypertarget{group__common_response}{}\doxyparagraph{PMT Response and Saving Hits}\label{group__common_response} -\begin{DoxyWarning}{Warning} -Only the \mbox{\hyperlink{classm_d_o_m}{m\+DOM}} PMT currently supports a detailed PMT response. -\end{DoxyWarning} -For photon detection in both simple and complex geometries, the photons must be absorbed within the photocathode volume. The PMTs\textquotesingle{} photocathodes are made sensitive through the \mbox{\hyperlink{class_o_m_sim_sensitive_detector}{OMSim\+Sensitive\+Detector}} class, following Geant4\textquotesingle{}s G4\+VSensitive\+Detector pattern. This configuration is achieved by invoking {\ttfamily OMSim\+Optical\+Module\+::configure\+Sensitive\+Volume} (or {\ttfamily OMSim\+PMTConstruction\+::configure\+Sensitive\+Volume} when simulating a single PMT). It is essential to invoke this method in the detector construction, as it needs the instance of {\ttfamily \mbox{\hyperlink{class_o_m_sim_detector_construction}{OMSim\+Detector\+Construction}}} to call {\ttfamily G4\+VUser\+Detector\+Construction\+::\+Set\+Sensitive\+Detector} for successful operation in Geant4 (refer to {\ttfamily OMSim\+Detector\+Construction\+::register\+Sensitive\+Detector}). - -Every step of a particle through the photocathode triggers the {\ttfamily \mbox{\hyperlink{class_o_m_sim_sensitive_detector_a2d12fa5869b30eee35a85793522e98f4}{OMSim\+Sensitive\+Detector\+::\+Process\+Hits}}} method. It verifies if the particle is a photon and whether it was absorbed. For a deeper understanding of Geant4\textquotesingle{}s philosophy concerning G4\+VSensitive\+Detector, consult the \href{https://geant4-userdoc.web.cern.ch/UsersGuides/ForApplicationDeveloper/html/Detector/hit.html?highlight=g4vsensitivedetector\#g4vsensitivedetector}{\texttt{ Geant4 guide for application developers}}. - -In {\ttfamily OMSim\+PMTConstruction\+::configure\+Sensitive\+Volume}, PMTs are associated with an instance of {\ttfamily \mbox{\hyperlink{class_o_m_sim_p_m_t_response}{OMSim\+PMTResponse}}}, contingent on the PMT under simulation. This class offers a precise PMT simulation by sampling from real measurements, obtaining the relative transit time, charge (in PE), and detection probability (using the measured scans from \href{https://zenodo.org/record/8121321}{\texttt{ M. Unland\textquotesingle{}s thesis}}). For detailes, refer to Section 9.\+3.\+4 of the linked thesis. This sampling is performed for every absorbed photon in {\ttfamily \mbox{\hyperlink{class_o_m_sim_sensitive_detector_a2d12fa5869b30eee35a85793522e98f4}{OMSim\+Sensitive\+Detector\+::\+Process\+Hits}}} invoking {\ttfamily \mbox{\hyperlink{class_o_m_sim_p_m_t_response_a55aabd8f8fd9be58eca3ba0753974d08}{OMSim\+PMTResponse\+::process\+Photocathode\+Hit}}}. ~\newline - Figure 4\+: {\itshape PMT response compared to measurement for different light sources. Image from \href{https://zenodo.org/record/8121321}{\texttt{ M. Unland\textquotesingle{}s thesis}}.} The data of absorbed photons is managed by the {\ttfamily \mbox{\hyperlink{class_o_m_sim_hit_manager}{OMSim\+Hit\+Manager}}} singleton. To analyse and export this data, consult example methods like {\ttfamily \mbox{\hyperlink{class_o_m_sim_effective_area_analyisis_af2f7ac6a789bb50ec7d0d8a81487ec20}{OMSim\+Effective\+Area\+Analyisis\+::write\+Scan}}} and {\ttfamily OMSim\+Decays\+Analysis\+::write\+Hit\+Information} for direction. - -An additional feature allows for the direct application of a QE cut. This ensures that only absorbed photons passing the QE test are retained in {\ttfamily \mbox{\hyperlink{class_o_m_sim_hit_manager}{OMSim\+Hit\+Manager}}}. To enable this feature, provide the \char`\"{}\+QE\+\_\+cut\char`\"{} argument via the command line. In this case {\ttfamily \mbox{\hyperlink{class_o_m_sim_sensitive_detector_a2d12fa5869b30eee35a85793522e98f4}{OMSim\+Sensitive\+Detector\+::\+Process\+Hits}}} will call {\ttfamily \mbox{\hyperlink{class_o_m_sim_p_m_t_response_a2447b2f9eb62a1e99f410bfeda917d5c}{OMSim\+PMTResponse\+::pass\+QE}}} and break early if it returns false, without storing the photon information. - -\begin{DoxyNote}{Note} -In most scenarios, it\textquotesingle{}s not recommended to use --QE\+\_\+cut since it reduces your statistics. Its presence in \mbox{\hyperlink{class_o_m_sim}{OMSim}} is primarily for testing purposes. It\textquotesingle{}s generally better to perform post-\/analysis using the saved {\ttfamily \mbox{\hyperlink{struct_o_m_sim_p_m_t_response_1_1_p_m_t_pulse_a87f21652e10a0bc82870ded9697b57f2}{OMSim\+PMTResponse\+::\+PMTPulse\+::detection\+Probability}}} for each absorbed photon. -\end{DoxyNote} -\hypertarget{group__common_dummyresponse}{}\doxyparagraph{Making other volumes sensitive to photons}\label{group__common_dummyresponse} -For some studies you might want a volume to detect photons, without this being necessarely a PMT. For such cases, the framework has a provision in place\+: use the {\ttfamily \mbox{\hyperlink{class_o_m_sim_sensitive_detector}{OMSim\+Sensitive\+Detector}}} and pass {\ttfamily Detector\+Type\+::\+General\+Photon\+Detector} as its constructor argument. In this case the {\ttfamily \mbox{\hyperlink{class_o_m_sim_sensitive_detector_a2d12fa5869b30eee35a85793522e98f4}{OMSim\+Sensitive\+Detector\+::\+Process\+Hits}}} will use an instance {\ttfamily \mbox{\hyperlink{class_no_response}{No\+Response}}} as PMT response, which is just a dummy placeholder. ~\newline - Remember to inform the {\ttfamily \mbox{\hyperlink{class_o_m_sim_hit_manager}{OMSim\+Hit\+Manager}}} that this detector is equivalent to \char`\"{}a single PMT\char`\"{}, ensuring internal vector sizes adjust accordingly. This approach ensures a smooth integration of the photosensitive volume within the current system. Below is an example illustrating how this can be incorporated within the detector construction\+: - - -\begin{DoxyCode}{0} -\DoxyCodeLine{\textcolor{preprocessor}{\#include "{}OMSimSensitiveDetector.hh"{}}} -\DoxyCodeLine{\textcolor{comment}{//... Assume the logical volume of your detector has been defined and is referred to as "{}lDetectorLV"{}}} -\DoxyCodeLine{\mbox{\hyperlink{class_o_m_sim_sensitive_detector}{OMSimSensitiveDetector}}* lSensitiveDetector = \textcolor{keyword}{new} \mbox{\hyperlink{class_o_m_sim_sensitive_detector}{OMSimSensitiveDetector}}(\textcolor{stringliteral}{"{}myDetector"{}}, DetectorType::GeneralPhotonDetector); } -\DoxyCodeLine{\mbox{\hyperlink{class_o_m_sim_hit_manager}{OMSimHitManager}} lHitManager = \mbox{\hyperlink{class_o_m_sim_hit_manager_aaa3e7a28d658d8e2e6db704b910cc35c}{OMSimHitManager::getInstance}}();} -\DoxyCodeLine{lHitManager.\mbox{\hyperlink{class_o_m_sim_hit_manager_ab4a1060283a53660e52626d08a77ebc8}{setNumberOfPMTs}}(1, lHitManager.getNextDetectorIndex());} -\DoxyCodeLine{registerSensitiveDetector(lDetectorLV, lSensitiveDetector);} - -\end{DoxyCode} - In this case, {\ttfamily \mbox{\hyperlink{class_o_m_sim_sensitive_detector_a2d12fa5869b30eee35a85793522e98f4}{OMSim\+Sensitive\+Detector\+::\+Process\+Hits}}} will store all absorbed photons. The number of photons absorbed will depend on the absorption length of the material connected to the logical volume. If there\textquotesingle{}s a need to make a volume sensitive to particles other than photons, add a new entry to the {\ttfamily Detector\+Type} enum (in {\ttfamily \mbox{\hyperlink{_o_m_sim_sensitive_detector_8hh_source}{OMSim\+Sensitive\+Detector.\+hh}}}) and incorporate a new method that handles this scenario in {\ttfamily \mbox{\hyperlink{class_o_m_sim_sensitive_detector_a2d12fa5869b30eee35a85793522e98f4}{OMSim\+Sensitive\+Detector\+::\+Process\+Hits}}}. You might also track these particles in {\ttfamily \mbox{\hyperlink{class_o_m_sim_tracking_action}{OMSim\+Tracking\+Action}}} or {\ttfamily \mbox{\hyperlink{class_o_m_sim_stepping_action}{OMSim\+Stepping\+Action}}}, but using a class derived from {\ttfamily G4\+VSensitive\+Detector} aligns with the philosophy of Geant4. \doxysubsection*{Files} +\doxysubsection*{Files} \begin{DoxyCompactItemize} \item file \mbox{\hyperlink{_o_m_sim_8hh}{OMSim.\+hh}} diff --git a/latex/group__radioactive.pdf b/latex/group__radioactive.pdf index 117854e9b9..15ed0dc6a2 100644 Binary files a/latex/group__radioactive.pdf and b/latex/group__radioactive.pdf differ diff --git a/latex/group__radioactive.tex b/latex/group__radioactive.tex index 7ff32d7a45..660d1242ef 100644 --- a/latex/group__radioactive.tex +++ b/latex/group__radioactive.tex @@ -16,24 +16,7 @@ \doxysubsection{Detailed Description} -\begin{DoxyWarning}{Warning} -This study has been tested only for Vitrovex glass (m\+DOM/\+LOM16) and the 80mm \mbox{\hyperlink{classm_d_o_m}{m\+DOM}} PMTs. Okamoto glass (D-\/\+Egg/\+LOM18) is currently under investigation. -\end{DoxyWarning} -The simulation considers the measured scintillation parameters and the specific activity of the isotopes to provide insights into the behavior of OMs in both air and ice environments over a time window $t_{w}$. The number of time windows simulated is given by the argument --numevents. The primary output is a timestamped list of detected photons, which can be utilized to compute parameters such as the module\textquotesingle{}s expected dark rate. The simulation steps can be summarized as\+: -\begin{DoxyItemize} -\item Determining the number of decays within $t_{w}$ based on measured data. -\item Initiating decay chains for each event by positioning an isotope randomly in the pressure vessel. -\item Assigning decay times from a uniform distribution within \mbox{[}0, $t_{w}$\mbox{]}, in case the time difference between mother-\/daughter decay times surpasses $t_{w}$. -\item Capturing photons detected by the PMTs for downstream analysis. -\end{DoxyItemize} - -Important customizations in the simulation involve the extension of Geant4\textquotesingle{}s original scintillation class, facilitating the simulation of more complex decay processes (8 lifetimes), and the modification the \mbox{\hyperlink{class_g4_radioactive_decay}{G4\+Radioactive\+Decay}} class which amends default decay time of isotopes. The scintillation properties of the \mbox{\hyperlink{classm_d_o_m}{m\+DOM}} glass were measured in the scope of several theses. For a summary check section 11.\+2 of \href{https://zenodo.org/record/8121321}{\texttt{ this thesis}}. - -Currently, there are two analysis modes\+: -\begin{DoxyItemize} -\item With the \textquotesingle{}--multiplicity\+\_\+study\textquotesingle{} argument\+: After each $t_{w}$ time window, the multiplicity is calculated and saved to a file. Raw data isn\textquotesingle{}t stored, as multiplicity studies generally involve extended simulation durations, leading to large volumes of photon data. -\item Without the \textquotesingle{}--multiplicity\+\_\+study\textquotesingle{} argument\+: Data pertaining to photons and decayed isotopes is saved to files. -\end{DoxyItemize}\doxysubsection*{Files} +\doxysubsection*{Files} \begin{DoxyCompactItemize} \item file \mbox{\hyperlink{_o_m_sim_decays_analysis_8hh}{OMSim\+Decays\+Analysis.\+hh}} diff --git a/latex/group__sngroup.tex b/latex/group__sngroup.tex index 5966591201..0d4913e4ec 100644 --- a/latex/group__sngroup.tex +++ b/latex/group__sngroup.tex @@ -8,83 +8,7 @@ \doxysubsection{Detailed Description} -This simulation is designed to emulate the detection of Core Collapse Supernova (CCSN or simply SN in the following) neutrinos using segmented sensors. It directly generates particles resulting from Inverse Beta Decay (IBD) and Electron Neutrino-\/\+Electron Elastic Scattering (ENES). - - -\begin{DoxyItemize} -\item IBD\+: $\bar{\nu}_e + p \rightarrow n + e^+$ -\item ENES\+: $\nu_e + e^- \rightarrow \nu_e + e^-$ -\end{DoxyItemize} - -In the IBD case, the outgoing neutron is not simulated; hence, the neutron capture process that might be detected is not included in the simulation. Each event is assigned a weight based on the interaction probability, detailed later on this page. By default, the surrounding ice is represented as a cylinder facing the CCSN, simplifying the weight calculations. - -Although CCSN models incorporate neutrino oscillations, the default simulation does not include any oscillation scenario in the weight calculations. - - ~\newline - Figure 1\+: {\itshape Diagram of the steps involved to generate the events for the simulation of CCSN neutrinos. The scheme is valid for both IBD and ENES, except for the threshold check. Here, stands for both electron from ENES or positron from IBD, and ν (este simbolo se vera bien?) for both electronic neutrino from ENES or electronic antineutrino from IBD.. Image from \href{https://zenodo.org/record/8107177}{\texttt{ this thesis}}.} - -The detailed procedure for this simulation is comprehensively described in \href{https://zenodo.org/record/8107177}{\texttt{ this thesis}}, specifically in section 6.\+4. Below is a summary extracted from this source, outlining the steps taken to generate the events\+: - - -\begin{DoxyEnumerate} -\item Utilizing the models, the expected flux per area is calculated from the luminosity $L(t)$ and the mean energy $$ according to \textbackslash{}begin\{equation\} \textbackslash{}label\{eq\+:fluxes\} \textbackslash{}\+Phi (t) = \textbackslash{}frac\{1\}\{4\textbackslash{}pi d$^\wedge$2\} \textbackslash{}cdot \textbackslash{}frac\{L(t)\}\{$<$E(t)$>$\}. \textbackslash{}end\{equation\} -\item The distribution of $\Phi (t)$ is used to sample a time $t$ of the burst via the inverse CDF (Cumulative Distribution Function) method. All other sampling from distributions within this simulation also employs the inverse CDF method. -\item For the sampled time $t$, the corresponding mean energy and mean squared energy are extracted from the models. These parameters contribute to the construction of the energy spectrum $f(E,t)$, as elucidated in \href{https://arxiv.org/pdf/1211.3920.pdf}{\texttt{ this paper}}. -\item The energy of the neutrino/antineutrino $E_\nu$ is sampled from $f(E,t)$. If the energy falls below the IBD threshold, the algorithm reverts to the second step. -\item From $E_\nu$, the angular cross section is devised. This informs the sampling of the angle $\theta$ between the incoming neutrino and the resulting $e^-/e^+$. The $\phi$ direction is randomly generated within the range of $0$ to $2\pi$. -\item The energy of $e^-/e^+$ is deduced from $\theta$ and $E_\nu$. The interaction probability for such an event is ascertained using the total cross section, facilitating the computation of the interaction weight, as further described below. -\item The $e^-/e^+$ is manifested at a random position within the ice volume. -\end{DoxyEnumerate}\hypertarget{group__sngroup_InputParameters}{}\doxysubsection{Input Parameters}\label{group__sngroup_InputParameters} -Execute {\ttfamily ./\+OMSim\+\_\+supernova -\/-\/help} to display all possible input parameters. - -A typical command to run the simulation is\+: - -{\ttfamily ./\+OMSim\+\_\+supernova -\/n 100 -\/-\/wheight 20 -\/-\/wradius 20 -\/-\/depth\+\_\+pos 75 -\/o outputfilename -\/-\/SNgun 0 -\/-\/SNtype 0}\hypertarget{group__sngroup_GenParam}{}\doxysubsubsection{General Parameters}\label{group__sngroup_GenParam} -{\ttfamily -\/n}\+: Number of particles to be generated. {\ttfamily -\/-\/depth\+\_\+pos}\+: Index of the vector determining the depth of the simulated modules. Notable values include Dust\+Layer=65, Mean\+ICUProperties(approx)=75, and Cleanest\+Ice=88. The data is located in \char`\"{}common/data/\+Materials/\+Ice\+Cube\+ICE.\+dat\char`\"{}. The \char`\"{}j\+Depth\+\_\+spice\char`\"{} vector provides the depth, with depth\+\_\+pos serving as the index. This selection affects the effective scattering and absorption lengths of the ice at the specified depth. {\ttfamily -\/o}\+: Output file name. By default, two output files are created\+: one containing the simulated event information, and another with detection data.\hypertarget{group__sngroup_SNParam}{}\doxysubsubsection{SN Framework Parameters}\label{group__sngroup_SNParam} -{\ttfamily -\/-\/wheight}\+: Height of the ice\textquotesingle{}s simulated world cylinder. {\ttfamily -\/-\/wradius}\+: Radius of the ice\textquotesingle{}s simulated world cylinder. {\ttfamily -\/-\/SNgun}\+: Chooses the interaction type (0 for IBD, 1 for ENES). {\ttfamily -\/-\/SNtype}\+: Selects the CCSN model. Two models are currently available, provided by the Garching group. These models represent the expected fluxes from two CCSNs resulting in neutron stars, with different progenitor masses (27 and 9.\+6 solar masses). Simulations yielding this data can be found at \href{https://arxiv.org/abs/1510.04643}{\texttt{ https\+://arxiv.\+org/abs/1510.\+04643}}\hypertarget{group__sngroup_SNParamFixE}{}\doxysubsubsection{Fixed Energy Studies}\label{group__sngroup_SNParamFixE} -This section allows users to manually set the mean energy of generated events by providing specific input parameters. For instance\+: - -{\ttfamily -\/-\/SNfix\+Energy -\/-\/SNmeanE 10.\+0 -\/-\/SNalpha 3.\+0} - -{\ttfamily -\/-\/SNfix\+Energy}\+: Acts as a flag parameter. When invoked, the simulation disregards the actual mean energy of neutrinos corresponding to the burst time. Instead, it adopts the mean energy and the pinching parameter specified by the subsequent two parameters. {\ttfamily -\/-\/SNmeanE}\+: Specifies the mean energy of the neutrinos. {\ttfamily -\/-\/SNalpha}\+: Defines the pinching parameter of the energy distribution (see \href{https://arxiv.org/pdf/1211.3920.pdf}{\texttt{ this paper}}). - -Consequently, the neutrinos\textquotesingle{} energy is sampled from the distribution, derived from these two parameters and the previously mentioned model.\hypertarget{group__sngroup_OutputFiles}{}\doxysubsection{Output Files}\label{group__sngroup_OutputFiles} -Information regarding the files that contain data outputs and insights derived from the simulated neutrino events.\hypertarget{group__sngroup_InfoOutfile}{}\doxysubsubsection{X\+\_\+info.\+dat}\label{group__sngroup_InfoOutfile} -This file encapsulates data concerning each generated neutrino event. Each entry contains\+: - -Time of the neutrino burst. Corresponding mean energy derived from the model. Sampled neutrino energy $E_\nu$. $\cos(\theta)$, where $\theta$ is the angle between the incoming neutrino and the outgoing particle (e-\/ or e+). Energy of the outgoing particle (e-\/ or e+). Interaction weight, calculated using the formula\+: \[ W_{\mathrm{int}}(E_\nu) = \sigma(E) \cdot n_{\mathrm{target}} \cdot l, \] where\+: $\ast$$\ast$ $\sigma(E)$ is the total cross section for the interaction, $\ast$$\ast$ $n_{\mathrm{target}}$ is the number of targets available for the interaction in the ice, $\ast$$\ast$ $l$ is the length of the simulated cylindrical world.\hypertarget{group__sngroup_DataOutfile}{}\doxyparagraph{X\+\_\+data.\+dat}\label{group__sngroup_DataOutfile} -This file contains the detection information. Its structure is designed to facilitate various trigger studies, allowing the examination of different time windows. Users might evaluate its structure for convenience, particularly if the trigger check is integrated within the simulation (requiring a predefined time window). - -The default content structure is as follows\+: \[ \text{Total hits | Modules hit | PMTs hit | "...for each PMT hit..." | Module number | PMT number | Hits in that PMT | "...for each Hit..." | hit time |} \] - -Note that the number of columns varies per line, contingent on the number of photons detected for the simulated neutrinos.\hypertarget{group__sngroup_Weights}{}\doxysubsection{Weights}\label{group__sngroup_Weights} -The output files contain the interaction weight. However, users should also consider a weight factor depending on the total flux and the number of simulated events. In the most general case of simulating a single depth and then extrapolating the results to the entire detector, another weight factor is needed. This factor accounts for the ice properties of the simulated depth with respect to the whole detector. This last factor decreases in importance when using high multiplicity conditions, since these events generally interact closer to the module, making the photons less sensitive to changes in the optical properties. - -These weight factors can be added similarly as explained in \href{https://zenodo.org/record/8107177}{\texttt{ this thesis, section 6.\+4.\+2}}. - -The total weight is composed of 3 components\+: the interaction probability, the SN flux through the simulated volume, and the different optical properties of the modules at different depths\+: - -\textbackslash{}begin\{equation\} \textbackslash{}label\{eq\+:sn\+\_\+weights\} W = W\+\_\+\{\textbackslash{}mathrm\{int\}\}(E) \textbackslash{}cdot W\+\_\+\{\textbackslash{}mathrm\{flux\}\}(d) \textbackslash{}cdot W\+\_\+\{\textbackslash{}mathrm\{eff\}\}. \textbackslash{}end\{equation\} - -Each component is explained as follows\+:\hypertarget{group__sngroup_IntWeight}{}\doxysubsubsection{Interaction Probability Weight\+:}\label{group__sngroup_IntWeight} -\textbackslash{}begin\{equation\} \textbackslash{}label\{eq\+:sn\+\_\+weight\+\_\+int\} W\+\_\+\{\textbackslash{}mathrm\{int\}\}(E\+\_\+\textbackslash{}nu) = \textbackslash{}sigma(E) \textbackslash{}cdot n\+\_\+\{\textbackslash{}mathrm\{target\}\} \textbackslash{}cdot l, \textbackslash{}end\{equation\} where $\sigma(E_\nu)$ is the total cross section for the interaction, $n_{\mathrm{target}}$ is the number of targets per unit of volume for such interaction, and $l=40\,m$ is the length of the generation volume along the neutrino direction axis. This is the length of the cylinder facing the CCSN.\hypertarget{group__sngroup_FluxWeight}{}\doxysubsubsection{Flux Weight\+:}\label{group__sngroup_FluxWeight} -\textbackslash{}begin\{equation\} \textbackslash{}label\{eq\+:sn\+\_\+weight\+\_\+flux\} W\+\_\+\{\textbackslash{}mathrm\{flux\}\}(d) = \textbackslash{}frac\{1\}\{N\+\_\+\{\textbackslash{}mathrm\{gen\}\}\} \textbackslash{}cdot \textbackslash{}frac\{r$^\wedge$2\}\{d$^\wedge$2\} \textbackslash{}cdot \textbackslash{}int \textbackslash{}frac\{L(t)\}\{$<$E(t)$>$\} dt, \textbackslash{}end\{equation\} where $r$ is the cylindrical generation volume’s radius, $d$ is the distance from Earth where the CCSN is assumed to occur, and $N_{\mathrm{gen}}$ is the number of generated events.\hypertarget{group__sngroup_EffWeight}{}\doxysubsubsection{Effective Weight\+:}\label{group__sngroup_EffWeight} -\textbackslash{}begin\{equation\} \textbackslash{}label\{eq\+:sn\+\_\+weight\+\_\+eff\} W\+\_\+\{\textbackslash{}mathrm\{eff\}\} = N\+\_\+\{\textbackslash{}mathrm\{modules\}\} \textbackslash{}cdot \textbackslash{}frac\{$<$V\+\_\+\{\textbackslash{}mathrm\{eff\}\}(m)$>$\}\{V\+\_\+\{\textbackslash{}mathrm\{eff\}\}(m,z\+\_\+\{\textbackslash{}mathrm\{sim\}\})\}, \textbackslash{}end\{equation\} where $N_{\mathrm{modules}}$ is the total modules in the simulated detector, $V_{\mathrm{eff}}(m, z_{\mathrm{sim}})$ is the effective volume at the simulation depth, and $$ is the mean effective volume for all modules in simulated detector. The term $m$ represents multiplicity, defined as the count of different PMTs within a single module that detected the event within a specific time window. - -The effective volume can be calculated in different ways. Old simulations of the \mbox{\hyperlink{classm_d_o_m}{m\+DOM}}, described in \href{https://zenodo.org/record/8107177}{\texttt{ this thesis, section 6.\+3}}, were used in past studies. A linear regression of the effective volume concerning the absorption length, derived from various depths, provides each depth\textquotesingle{}s effective volume. Although it is advisable to redo these simulations with a current \mbox{\hyperlink{classm_d_o_m}{m\+DOM}} model, users can temporarily use the old data with a regression line of $V_{\mathrm{eff}} = b \cdot x + c$, where $x = 1/a$ is the inverse of the absorption length. The coefficients $b$ and $c$, depending on the event\textquotesingle{}s multiplicity, were obtained as follows\+: - -\begin{DoxyVerb}* | multiplicity | b (slope, m^2) | c (m^3) | -* |--------------|----------------------------|------------------| -* | 1 | 15.1843 | 0.000 | -* | 2 | 0.1352 | 47.005 | -* | 3 | 0.0306 | 16.170 | -* | 4 | 0.0095 | 8.680 | -* | 5 | 0.0039 | 5.105 | -* | >= 6 | 0.0026 | 2.909 | -* \end{DoxyVerb} - - -Note that, for more than 5 PMTs, the same fit line is employed due to insufficient statistics at higher PMTs in the effective volume simulation. Additionally, since the absorption length depends on the wavelength, the fits above were obtained assuming a wavelength of $\lambda = 400\,nm$. \doxysubsection*{Files} +\doxysubsection*{Files} \begin{DoxyCompactItemize} \item file \mbox{\hyperlink{_o_m_sim_s_n_particle_generators_8hh}{OMSim\+SNParticle\+Generators.\+hh}} diff --git a/latex/index.tex b/latex/index.tex index 26c44ac2e3..0d0da68d75 100644 --- a/latex/index.tex +++ b/latex/index.tex @@ -6,8 +6,8 @@ {\bfseries{\mbox{\hyperlink{class_o_m_sim}{OMSim}}}} is a Geant4 framework for the simulation of optical modules of the Ice\+Cube Observatory. It has been mostly developed by the Münster Ice\+Cube Group during different master and PhD theses. The project is separated into different modules depending on the study (e.\+g. background investigations with radioactive decays, or sensitivity studies). These modules share common files (in the \char`\"{}common\char`\"{} folder) which, for example, define geometries from modules and PMTs or also material properties. -Please check the different Modules in the \href{https://icecube.github.io/OMSim/}{\texttt{ documentation}} for further details and examples.\hypertarget{index_autotoc_md8}{}\doxysection{Installation}\label{index_autotoc_md8} -\hypertarget{index_autotoc_md9}{}\doxysubsubsection{Installing Geant4}\label{index_autotoc_md9} +Please check the different Modules in the \href{https://icecube.github.io/OMSim/}{\texttt{ documentation}} for further details and examples.\hypertarget{index_autotoc_md29}{}\doxysection{Installation}\label{index_autotoc_md29} +\hypertarget{index_autotoc_md30}{}\doxysubsubsection{Installing Geant4}\label{index_autotoc_md30} First you should install Geant4 following \href{https://geant4-userdoc.web.cern.ch/UsersGuides/InstallationGuide/html/installguide.html}{\texttt{ the guide provided by cern}}. \mbox{\hyperlink{class_o_m_sim}{OMSim}} is currently optimised for Geant4-\/11.\+1.\+1. If you want to use the visualisation tools of Geant, you should include the following cmake options\+: @@ -15,7 +15,7 @@ \DoxyCodeLine{-\/DGEANT4\_INSTALL\_DATA=ON -\/DGEANT4\_USE\_GDML=ON -\/DGEANT4\_USE\_OPENGL\_X11=ON -\/DGEANT4\_USE\_QT=ON -\/DGEANT4\_USE\_RAYTRACER\_X11=ON -\/DGEANT4\_USE\_XM=ON} \end{DoxyCode} - Do not change \char`\"{}\+GEANT4\+\_\+\+BUILD\+\_\+\+MULTITHREADED\char`\"{} to OFF, as \mbox{\hyperlink{class_o_m_sim}{OMSim}} supports multithreading.\hypertarget{index_autotoc_md10}{}\doxysubsubsection{Requirements}\label{index_autotoc_md10} + Do not change \char`\"{}\+GEANT4\+\_\+\+BUILD\+\_\+\+MULTITHREADED\char`\"{} to OFF, as \mbox{\hyperlink{class_o_m_sim}{OMSim}} supports multithreading.\hypertarget{index_autotoc_md31}{}\doxysubsubsection{Requirements}\label{index_autotoc_md31} There are a few dependencies. You can install them using the following command\+: @@ -31,7 +31,7 @@ \DoxyCodeLine{source \$ROOTSYS/bin/thisroot.sh} \end{DoxyCode} -\hypertarget{index_autotoc_md11}{}\doxysubsubsection{Compiling OMSim}\label{index_autotoc_md11} +\hypertarget{index_autotoc_md32}{}\doxysubsubsection{Compiling OMSim}\label{index_autotoc_md32} \begin{DoxyItemize} \item Clone this branch. @@ -61,7 +61,7 @@ \begin{DoxyItemize} \item Finally, just run {\ttfamily make} or {\ttfamily make -\/j N} where N is number of cores you want to use for the compilation. -\end{DoxyItemize}\hypertarget{index_autotoc_md12}{}\doxysection{Available studies}\label{index_autotoc_md12} +\end{DoxyItemize}\hypertarget{index_autotoc_md33}{}\doxysection{Available studies}\label{index_autotoc_md33} \mbox{\hyperlink{class_o_m_sim}{OMSim}} has been utilized in a range of studies, each simulating unique physics, thereby necessitating distinct Physicslist/analysis setups. In this repository, we have compiled a selection of these studies, each contained within its own folder and accompanied by its own main file. Currently available\+: @@ -69,7 +69,6 @@ \item \href{https://icecube.github.io/OMSim/group___effective_area.html}{\texttt{ Effective area}}\+: calculates the effective area of the optical modules/\+PMTs. \item \href{https://icecube.github.io/OMSim/group__radioactive.html}{\texttt{ Radioactive decays}}\+: simulates radioactive decays within the glass of the pressure vessel and the PMT glass. Essential for understanding the primary background of optical modules. \item \href{https://icecube.github.io/OMSim/group__sngroup.html}{\texttt{ Supernova studies}}\+: used for the development of an improved SN trigger for Ice\+Cube using multi-\/\+PMT modules. -\item \href{https://icecube.github.io/OMSim/group__bubble.html}{\texttt{ Bubble column}}\+: used for investigating the capability of the \mbox{\hyperlink{classm_d_o_m}{m\+DOM}} flashers in determining bubble column parameters. \end{DoxyItemize} Most users will likely utilize just one of these studies, meaning there\textquotesingle{}s no need to compile all of them. If you wish to exclude certain studies from compilation, you can comment out the undesired ones in the CMake\+Lists.\+txt between lines 41-\/43 (where the {\bfseries{add\+\_\+subdirectory}} commands are located). \ No newline at end of file diff --git a/latex/md_0_common.tex b/latex/md_0_common.tex new file mode 100644 index 0000000000..3116dcbbc9 --- /dev/null +++ b/latex/md_0_common.tex @@ -0,0 +1,94 @@ +This framework offers tools to simplify geometry construction and material definitions, as well as a detailed PMT response mechanism. This page provides a brief introduction to the main features.\hypertarget{md_0_common_autotoc_md1}{}\doxysection{Materials and User Data}\label{md_0_common_autotoc_md1} +User-\/defined material data are stored in JSON files under {\ttfamily /common/data} to minimize file length (the original detector construction had over 4,000 lines, mainly due to material properties!). + +The {\ttfamily \mbox{\hyperlink{class_input_data_manager}{Input\+Data\+Manager}}} (see {\ttfamily \mbox{\hyperlink{_o_m_sim_input_data_8hh}{OMSim\+Input\+Data.\+hh}}}) loads these properties directly into the Geant4 framework. Materials loaded via this class can be retrieved using Geant4\textquotesingle{}s conventional method {\ttfamily G4\+Material\+::\+Get\+Material}, but the framework also provides the wrapper {\ttfamily \mbox{\hyperlink{class_input_data_manager_a970eddaab6756e6288504390454a38f4}{Input\+Data\+Manager\+::get\+Material}}} to handle default parameters. + +The class also provides an analogue method for optical surfaces {\ttfamily \mbox{\hyperlink{class_input_data_manager_ae6ae987535a442a42ad47d53394ade56}{Input\+Data\+Manager\+::get\+Optical\+Surface}}} which does not exist in Geant4. + +Since different materials have different types of properties, the data is loaded in multiple ways. These different material types are defined in {\ttfamily \mbox{\hyperlink{_o_m_sim_data_file_types_8hh}{OMSim\+Data\+File\+Types.\+hh}}}. + +Additionally, geometry data used during PMT construction are also stored in JSON files ({\ttfamily /common/data/\+PMTs}). These are saved in a \char`\"{}tree\char`\"{} (essentially a dictionary containing the JSON file\textquotesingle{}s keys and values) in {\ttfamily \mbox{\hyperlink{class_parameter_table_a749bc840cf2aea18fb5b63da8b68c23c}{Input\+Data\+Manager\+::m\+Table}}}. + +This approach was adopted because various PMTs are constructed similarly, eliminating the need to define a unique class for each PMT type, as is done for the optical modules. + +Thus, an instance of {\ttfamily \mbox{\hyperlink{class_input_data_manager}{Input\+Data\+Manager}}} is always passed to all classes related to geometry construction (see \href{\#geometry-construction}{\texttt{ geometry}}). + +If you wish to load additional data, you can either define a new type in OMSim\+Data\+File\+Types or load it into a tree as previously mentioned. For simpler tasks, use the static method {\ttfamily \mbox{\hyperlink{class_input_data_manager_a3a233522b61c65875ebb7b274ff31507}{Input\+Data\+Manager\+::loadtxt}}}, which operates similarly to Python\textquotesingle{}s numpy.\+loadtxt. For example\+: + + +\begin{DoxyCode}{0} +\DoxyCodeLine{std::vector data = \mbox{\hyperlink{class_input_data_manager_a3a233522b61c65875ebb7b274ff31507}{InputDataManager::loadtxt}}(\textcolor{stringliteral}{"{}path/file\_name.txt"{}});} +\DoxyCodeLine{std::vector first\_column = data.at(0);} +\DoxyCodeLine{std::vector second\_column = data.at(1);} +\DoxyCodeLine{\textcolor{comment}{// ...}} + +\end{DoxyCode} +\hypertarget{md_0_common_autotoc_md2}{}\doxysection{Geometry construction}\label{md_0_common_autotoc_md2} +Each optical module and harness is defined in its respective class, located in the {\ttfamily /common/geometry\+\_\+construction/} folder. These inherit from the virtual base class {\ttfamily \mbox{\hyperlink{class_o_m_sim_optical_module}{OMSim\+Optical\+Module}}}. + +This inheritance ensures the definition of functions to retrieve the pressure vessel\textquotesingle{}s weight (necessary for radioactive decay studies) and the count of PMTs inside the module. The {\ttfamily \mbox{\hyperlink{class_o_m_sim_optical_module}{OMSim\+Optical\+Module}}} interface inherits from {\ttfamily \mbox{\hyperlink{classabc_detector_component}{abc\+Detector\+Component}}}, a general helper class simplifying construction. Most \mbox{\hyperlink{class_o_m_sim}{OMSim}} geometries inherit from this class, as illustrated in the dependency diagram below\+: + + + +The {\ttfamily \mbox{\hyperlink{class_o_m_sim_p_m_t_construction}{OMSim\+PMTConstruction}}} class constructs PMTs. There are two PMT construction approaches. The first is simple, with a solid photocathode where all entering photons are recorded. The second type simulates the photocathode as a thin layer, also representing the internal components accounting for internal reflections. For more information, refer to Chapter 9 of \href{https://zenodo.org/record/8121321}{\texttt{ Martin Unland\textquotesingle{}s thesis}}. + +The construction of different PMT models (e.\+g. the 3\textquotesingle{}\textquotesingle{} or 10\textquotesingle{}\textquotesingle{} PMTs) is quite similar. However, the frontal window shape varies among models, leading to diverse combinations of ellipsoids and spheres. + + ~\newline + Figure 1\+: {\itshape Cross section of simple \mbox{\hyperlink{classm_d_o_m}{m\+DOM}} PMT model. Image from \href{https://zenodo.org/record/8121321}{\texttt{ M. Unland\textquotesingle{}s thesis}}.} + + ~\newline + Figure 2\+: {\itshape Side view of complex \mbox{\hyperlink{classm_d_o_m}{m\+DOM}} PMT model. Image from \href{https://zenodo.org/record/8121321}{\texttt{ M. Unland\textquotesingle{}s thesis}}.} + +In the complex PMT model, the photocathode has an absorption length that matches the measured quantum efficiency of the \mbox{\hyperlink{classm_d_o_m}{m\+DOM}} PMTs. For the other PMT models, this matching still has to be performed. + + ~\newline + Figure 3\+: {\itshape QE of simulation with the absorption length currently used compared to measurements. Image from \href{https://zenodo.org/record/8121321}{\texttt{ M. Unland\textquotesingle{}s thesis}}.} \hypertarget{md_0_common_autotoc_md3}{}\doxysection{PMT Response and Saving Hits}\label{md_0_common_autotoc_md3} +\begin{quote} +{\bfseries{Warning}}\+: Only the \mbox{\hyperlink{classm_d_o_m}{m\+DOM}} PMT currently supports a detailed PMT response. \end{quote} +For photon detection in both simple and complex geometries, the photons must be absorbed within the photocathode volume. The PMTs\textquotesingle{} photocathodes are made sensitive through the \mbox{\hyperlink{class_o_m_sim_sensitive_detector}{OMSim\+Sensitive\+Detector}} class, following Geant4\textquotesingle{}s G4\+VSensitive\+Detector pattern. This configuration is achieved by invoking {\ttfamily OMSim\+Optical\+Module\+::configure\+Sensitive\+Volume} (or {\ttfamily OMSim\+PMTConstruction\+::configure\+Sensitive\+Volume} when simulating a single PMT). + +It is essential to invoke this method in the detector construction, as it needs the instance of {\ttfamily \mbox{\hyperlink{class_o_m_sim_detector_construction}{OMSim\+Detector\+Construction}}} to call {\ttfamily G4\+VUser\+Detector\+Construction\+::\+Set\+Sensitive\+Detector} for successful operation in Geant4 (refer to {\ttfamily OMSim\+Detector\+Construction\+::register\+Sensitive\+Detector}). + +Every step of a particle through the photocathode triggers the {\ttfamily \mbox{\hyperlink{class_o_m_sim_sensitive_detector_a2d12fa5869b30eee35a85793522e98f4}{OMSim\+Sensitive\+Detector\+::\+Process\+Hits}}} method. It verifies if the particle is a photon and whether it was absorbed. For a deeper understanding of Geant4\textquotesingle{}s philosophy concerning G4\+VSensitive\+Detector, consult the \href{https://geant4-userdoc.web.cern.ch/UsersGuides/ForApplicationDeveloper/html/Detector/hit.html?highlight=g4vsensitivedetector\#g4vsensitivedetector}{\texttt{ Geant4 guide for application developers}}. + +In {\ttfamily OMSim\+PMTConstruction\+::configure\+Sensitive\+Volume}, PMTs are associated with an instance of {\ttfamily \mbox{\hyperlink{class_o_m_sim_p_m_t_response}{OMSim\+PMTResponse}}}, contingent on the PMT under simulation. This class offers a precise PMT simulation by sampling from real measurements, obtaining the relative transit time, charge (in PE), and detection probability (using the measured scans from \href{https://zenodo.org/record/8121321}{\texttt{ M. Unland\textquotesingle{}s thesis}}). For details, refer to Section 9.\+3.\+4 of the linked thesis. + +This sampling is performed for every absorbed photon in {\ttfamily \mbox{\hyperlink{class_o_m_sim_sensitive_detector_a2d12fa5869b30eee35a85793522e98f4}{OMSim\+Sensitive\+Detector\+::\+Process\+Hits}}} invoking {\ttfamily \mbox{\hyperlink{class_o_m_sim_p_m_t_response_a55aabd8f8fd9be58eca3ba0753974d08}{OMSim\+PMTResponse\+::process\+Photocathode\+Hit}}}. + + ~\newline + Figure 4\+: {\itshape PMT response compared to measurement for different light sources. Image from \href{https://zenodo.org/record/8121321}{\texttt{ M. Unland\textquotesingle{}s thesis}}.} + +The data of absorbed photons is managed by the {\ttfamily \mbox{\hyperlink{class_o_m_sim_hit_manager}{OMSim\+Hit\+Manager}}} singleton. To analyze and export this data, consult example methods like {\ttfamily \mbox{\hyperlink{class_o_m_sim_effective_area_analyisis_af2f7ac6a789bb50ec7d0d8a81487ec20}{OMSim\+Effective\+Area\+Analyisis\+::write\+Scan}}} and {\ttfamily OMSim\+Decays\+Analysis\+::write\+Hit\+Information} for direction. + +An additional feature allows for the direct application of a QE cut. This ensures that only absorbed photons passing the QE test are retained in {\ttfamily \mbox{\hyperlink{class_o_m_sim_hit_manager}{OMSim\+Hit\+Manager}}}. To enable this feature, provide the \char`\"{}\+QE\+\_\+cut\char`\"{} argument via the command line. In this case {\ttfamily \mbox{\hyperlink{class_o_m_sim_sensitive_detector_a2d12fa5869b30eee35a85793522e98f4}{OMSim\+Sensitive\+Detector\+::\+Process\+Hits}}} will call {\ttfamily \mbox{\hyperlink{class_o_m_sim_p_m_t_response_a2447b2f9eb62a1e99f410bfeda917d5c}{OMSim\+PMTResponse\+::pass\+QE}}} and break early if it returns false, without storing the photon information. + +\begin{quote} +{\bfseries{Note}}\+: In most scenarios, it\textquotesingle{}s not recommended to use --QE\+\_\+cut since it reduces your statistics. Its presence in \mbox{\hyperlink{class_o_m_sim}{OMSim}} is primarily for testing purposes. It\textquotesingle{}s generally better to perform post-\/analysis using the saved {\ttfamily \mbox{\hyperlink{struct_o_m_sim_p_m_t_response_1_1_p_m_t_pulse_a87f21652e10a0bc82870ded9697b57f2}{OMSim\+PMTResponse\+::\+PMTPulse\+::detection\+Probability}}} for each absorbed photon. \end{quote} +\hypertarget{md_0_common_autotoc_md4}{}\doxysection{Making other volumes sensitive to photons}\label{md_0_common_autotoc_md4} +For some studies, you might want a volume to detect photons, without this necessarily being a PMT. For such cases, the framework has a provision in place\+: use the {\ttfamily \mbox{\hyperlink{class_o_m_sim_sensitive_detector}{OMSim\+Sensitive\+Detector}}} and pass {\ttfamily Detector\+Type\+::\+General\+Photon\+Detector} as its constructor argument. + +In this case, the {\ttfamily \mbox{\hyperlink{class_o_m_sim_sensitive_detector_a2d12fa5869b30eee35a85793522e98f4}{OMSim\+Sensitive\+Detector\+::\+Process\+Hits}}} will use an instance {\ttfamily \mbox{\hyperlink{class_no_response}{No\+Response}}} as PMT response, which is just a dummy placeholder. ~\newline + + +Remember to inform the {\ttfamily \mbox{\hyperlink{class_o_m_sim_hit_manager}{OMSim\+Hit\+Manager}}} that this detector is equivalent to \char`\"{}a single PMT\char`\"{}, ensuring internal vector sizes adjust accordingly. + +This approach ensures a smooth integration of the photosensitive volume within the current system. Below is an example illustrating how this can be incorporated within the detector construction\+: + + +\begin{DoxyCode}{0} +\DoxyCodeLine{\textcolor{preprocessor}{\#include "{}OMSimSensitiveDetector.hh"{}}} +\DoxyCodeLine{\textcolor{comment}{//... Assume the logical volume of your detector has been defined and is referred to as "{}lDetectorLV"{}}} +\DoxyCodeLine{\mbox{\hyperlink{class_o_m_sim_sensitive_detector}{OMSimSensitiveDetector}}* lSensitiveDetector = \textcolor{keyword}{new} \mbox{\hyperlink{class_o_m_sim_sensitive_detector}{OMSimSensitiveDetector}}(\textcolor{stringliteral}{"{}myDetector"{}}, DetectorType::GeneralPhotonDetector); } +\DoxyCodeLine{\mbox{\hyperlink{class_o_m_sim_hit_manager}{OMSimHitManager}} lHitManager = \mbox{\hyperlink{class_o_m_sim_hit_manager_aaa3e7a28d658d8e2e6db704b910cc35c}{OMSimHitManager::getInstance}}();} +\DoxyCodeLine{lHitManager.\mbox{\hyperlink{class_o_m_sim_hit_manager_ab4a1060283a53660e52626d08a77ebc8}{setNumberOfPMTs}}(1, lHitManager.getNextDetectorIndex());} +\DoxyCodeLine{registerSensitiveDetector(lDetectorLV, lSensitiveDetector);} + +\end{DoxyCode} + + +In this case, {\ttfamily \mbox{\hyperlink{class_o_m_sim_sensitive_detector_a2d12fa5869b30eee35a85793522e98f4}{OMSim\+Sensitive\+Detector\+::\+Process\+Hits}}} will store all absorbed photons. The number of photons absorbed will depend on the absorption length of the material connected to the logical volume. + +If there\textquotesingle{}s a need to make a volume sensitive to particles other than photons, add a new entry to the {\ttfamily Detector\+Type} enum (in {\ttfamily \mbox{\hyperlink{_o_m_sim_sensitive_detector_8hh_source}{OMSim\+Sensitive\+Detector.\+hh}}}) and incorporate a new method that handles this scenario in {\ttfamily \mbox{\hyperlink{class_o_m_sim_sensitive_detector_a2d12fa5869b30eee35a85793522e98f4}{OMSim\+Sensitive\+Detector\+::\+Process\+Hits}}}. + +You might also track these particles in {\ttfamily \mbox{\hyperlink{class_o_m_sim_tracking_action}{OMSim\+Tracking\+Action}}} or {\ttfamily \mbox{\hyperlink{class_o_m_sim_stepping_action}{OMSim\+Stepping\+Action}}}, but using a class derived from {\ttfamily G4\+VSensitive\+Detector} aligns with the philosophy of Geant4. \ No newline at end of file diff --git a/latex/md_multithreading.tex b/latex/md_1_multithreading.tex similarity index 93% rename from latex/md_multithreading.tex rename to latex/md_1_multithreading.tex index b05db8a69d..0a1db0ea2c 100644 --- a/latex/md_multithreading.tex +++ b/latex/md_1_multithreading.tex @@ -1,4 +1,4 @@ -\hypertarget{md_multithreading_autotoc_md1}{}\doxysection{Introduction}\label{md_multithreading_autotoc_md1} +The OMSim-\/\+Framework allows for multi-\/threading. The number of threads can be controlled with the {\ttfamily -\/-\/threads} argument (default 1). If you specify more threads than available, only the maximum available will be used.\hypertarget{md_1_multithreading_autotoc_md6}{}\doxysection{Introduction}\label{md_1_multithreading_autotoc_md6} Geant4 implements multi-\/threading using a master-\/worker model\+: @@ -12,14 +12,14 @@ \item Geometry and physics tables are shared read-\/only among threads. \item Each thread has its own instance of sensitive detectors, event and tracking managers. \item Random number generators are designed to produce independent streams for each thread. -\end{DoxyItemize}\hypertarget{md_multithreading_autotoc_md2}{}\doxysection{Thread Safety Guidelines}\label{md_multithreading_autotoc_md2} +\end{DoxyItemize}\hypertarget{md_1_multithreading_autotoc_md7}{}\doxysection{Thread Safety Guidelines}\label{md_1_multithreading_autotoc_md7} \begin{DoxyEnumerate} \item {\bfseries{Use Thread-\/\+Local Storage}}\+: For data unique to each thread, use {\ttfamily G4\+Thread\+Local}. \item {\bfseries{Protect Shared Resources}}\+: Use mutex locks when accessing shared resources. \item {\bfseries{Minimize Global Variables}}\+: Prefer class members or local variables instead. \item {\bfseries{Implement Thread-\/\+Safe Containers}}\+: Ensure thread-\/safe access and modification of containers. -\end{DoxyEnumerate}\hypertarget{md_multithreading_autotoc_md3}{}\doxysection{Thread-\/\+Safe Singleton Implementation}\label{md_multithreading_autotoc_md3} +\end{DoxyEnumerate}\hypertarget{md_1_multithreading_autotoc_md8}{}\doxysection{Thread-\/\+Safe Singleton Implementation}\label{md_1_multithreading_autotoc_md8} Both {\ttfamily \mbox{\hyperlink{class_o_m_sim_hit_manager}{OMSim\+Hit\+Manager}}} and {\ttfamily \mbox{\hyperlink{class_o_m_sim_decays_analysis}{OMSim\+Decays\+Analysis}}} utilize the singleton pattern with a thread-\/safe {\ttfamily get\+Instance} method. This method employs a double-\/checked locking pattern to ensure thread safety while minimizing synchronization overhead. The process works as follows\+: @@ -53,7 +53,7 @@ \begin{quote} {\bfseries{Note}}\+: While this singleton implementation is thread-\/safe, consider whether a singleton is the best design choice for your specific use case. Singletons can sometimes lead to issues with testability and create hidden dependencies. \end{quote} -\hypertarget{md_multithreading_autotoc_md4}{}\doxysubsection{Example\+: OMSim\+Hit\+Manager}\label{md_multithreading_autotoc_md4} +\hypertarget{md_1_multithreading_autotoc_md9}{}\doxysubsection{Example\+: OMSim\+Hit\+Manager}\label{md_1_multithreading_autotoc_md9} The {\ttfamily \mbox{\hyperlink{class_o_m_sim_hit_manager}{OMSim\+Hit\+Manager}}} class demonstrates several thread-\/safety techniques\+: @@ -133,7 +133,7 @@ \begin{quote} {\bfseries{Important}}\+: Call {\ttfamily merge\+Thread\+Data} after all threads have finished simulating (after a run has completed). \end{quote} -\hypertarget{md_multithreading_autotoc_md5}{}\doxysubsection{Example\+: Saving Data Per Thread}\label{md_multithreading_autotoc_md5} +\hypertarget{md_1_multithreading_autotoc_md10}{}\doxysubsection{Example\+: Saving Data Per Thread}\label{md_1_multithreading_autotoc_md10} In scenarios where merging data is unnecessary, or the amount of data is too large to wait until end of run, each thread can save its data in separate files. This is demonstrated in the {\ttfamily \mbox{\hyperlink{class_o_m_sim_decays_analysis}{OMSim\+Decays\+Analysis}}} class. @@ -213,7 +213,7 @@ \DoxyCodeLine{ \}} \end{DoxyCode} -\hypertarget{md_multithreading_autotoc_md6}{}\doxysection{Best Practices for Creating New Thread-\/\+Safe Containers}\label{md_multithreading_autotoc_md6} +\hypertarget{md_1_multithreading_autotoc_md11}{}\doxysection{Best Practices for Creating New Thread-\/\+Safe Containers}\label{md_1_multithreading_autotoc_md11} When implementing new thread-\/safe containers in Geant4\+: diff --git a/latex/md_2_effective_area.tex b/latex/md_2_effective_area.tex new file mode 100644 index 0000000000..4c5d3b65fc --- /dev/null +++ b/latex/md_2_effective_area.tex @@ -0,0 +1,63 @@ +In the folder {\ttfamily effective\+\_\+area} you find the files pertinent to the effective area studies.\hypertarget{md_2_effective_area_autotoc_md13}{}\doxysection{Introduction to effective areas}\label{md_2_effective_area_autotoc_md13} +\begin{quote} +{\bfseries{Note}}\+: In the following, a short introduction of an effective area study is made with the \mbox{\hyperlink{classm_d_o_m}{m\+DOM}} as an example. For further details see Chapter 10 of \href{https://www.uni-muenster.de/imperia/md/content/physik_kp/agkappes/abschlussarbeiten/doktorarbeiten/1702-phd_lclassen.pdf}{\texttt{ Lew Classen\textquotesingle{}s thesis}} or Section 9.\+3.\+5 of \href{https://zenodo.org/record/8121321}{\texttt{ Martin Unland\textquotesingle{}s thesis}}. \end{quote} +During the design of a module, its sensitivity is optimised by considering the optical properties of various materials and altering the geometry and positioning of the mechanical components in the Geant4 simulation. + +The metric to optimise the module\textquotesingle{}s sensitivity is the effective area A\+\_\+eff(θ, φ). This represents the area that is detected from a plane wave of incidence angle of θ (zenith) and φ (azimuth) with respect to the module. This parameter is calculated with \mbox{\hyperlink{class_o_m_sim}{OMSim}} by simulating a disk emitting mono-\/energetic photons perpendicular to its surface with a uniform density profile. + +The photon generation is made with the module {\ttfamily \mbox{\hyperlink{class_angular_scan}{Angular\+Scan}}}, running the method {\ttfamily \mbox{\hyperlink{class_angular_scan_a465f642ebbe30fc94f9ed8ec6e554ef4}{Angular\+Scan\+::run\+Single\+Angular\+Scan}}} once for each direction to be investigated. + + ~\newline + Figure 1\+: {\itshape Screenshot of an \mbox{\hyperlink{classm_d_o_m}{m\+DOM}} illuminated by a disk emitter simulating the incidence of a plane wave from the direction θ (zenith) and φ (azimuth) using the Geant4 visualiser. The photon trajectories are represented by orange lines, and yellow dots mark the locations of physical interactions. Image taken from \href{https://zenodo.org/record/8121321}{\texttt{ this thesis}}.} + +After simulating N photons from a plane of area A\+\_\+rad (which has to be larger than the projected area of the \mbox{\hyperlink{classm_d_o_m}{m\+DOM}}), the effective area is calculated as + +\$\$ A\+\_\+\{\textbackslash{}mathrm\{eff\}\}(\textbackslash{}theta, \textbackslash{}phi) = \textbackslash{}frac\{N\+\_\+\{\textbackslash{}mathrm\{det\}\}(\textbackslash{}theta, \textbackslash{}phi)\}\{N\}\textbackslash{}cdot A\+\_\+\{\textbackslash{}mathrm\{rad\}\}, \$\$ + +where N\+\_\+det is the number of photons detected by the module. To optimise the sensitivity over multiple directions, A\+\_\+eff(θ, φ) is calculated for various angle pairs, and the mean effective area, A\+\_\+eff\+\_\+mean, is determined. The n angle pairs are chosen using healpix, which separates a sphere into n pixels of equal area. Thus, + +\$\$ \textbackslash{}overline\{A\}\+\_\+\{\textbackslash{}mathrm\{eff\}\} = \textbackslash{}frac\{1\}\{n\}\textbackslash{}sum\+\_\+\{i=1\}$^\wedge$n A\+\_\+\{\textbackslash{}mathrm\{eff\}\}(\textbackslash{}theta\+\_\+i, \textbackslash{}phi\+\_\+i). \$\$ + +Since the effective area is wavelength dependent, the calculation must be repeated for different wavelengths. Wavelengths shorter than 300nm are absorbed by the pressure vessel, whereas the QE of the PMT approaches zero at wavelengths longer than 700nm.\hypertarget{md_2_effective_area_autotoc_md14}{}\doxysection{Example using healpy}\label{md_2_effective_area_autotoc_md14} +In the following, an example of the usage of the effective area module is given. Although there are C++ healpix libraries, in my opinion, the easiest way of getting the angle pair coordinates is using Healpy in Python. + +In principle, for short simulations, you could run the program directly from Python using the angles from healpy as input parameters\+: + + +\begin{DoxyCode}{0} +\DoxyCodeLine{import healpy as hp} +\DoxyCodeLine{import numpy as np} +\DoxyCodeLine{from os import system} +\DoxyCodeLine{} +\DoxyCodeLine{NSIDE = 8 \#only powers of 2 allowed, the larger, the more pixels are calculated} +\DoxyCodeLine{NPIX = hp.nside2npix(NSIDE)} +\DoxyCodeLine{thetas, phis = np.degrees(hp.pix2ang(nside=NSIDE, ipix=np.arange(NPIX)))} +\DoxyCodeLine{} +\DoxyCodeLine{for i, (theta, phi) in enumerate(zip(thetas, phis)):} +\DoxyCodeLine{ if i==0:} +\DoxyCodeLine{ system(f"{}./OMSim\_effective\_area -\/n 10000 -\/-\/environment 1 -\/r 300 -\/t \{theta\} -\/f \{phi\} -\/-\/output\_file output"{})} +\DoxyCodeLine{ else:} +\DoxyCodeLine{ system(f"{}./OMSim\_effective\_area -\/n 10000 -\/-\/environment 1 -\/r 300 -\/t \{theta\} -\/f \{phi\} -\/-\/output\_file output -\/-\/no\_header"{})} + +\end{DoxyCode} + + +However, this is quite inefficient. The best is to save the angle pairs into a file and pass it as an argument. If you give a file as an argument, the arg theta and phi are ignored. + + +\begin{DoxyCode}{0} +\DoxyCodeLine{import healpy as hp} +\DoxyCodeLine{import numpy as np} +\DoxyCodeLine{from os import system} +\DoxyCodeLine{} +\DoxyCodeLine{NSIDE = 8 \#only powers of 2 allowed, the larger, the more pixels are calculated} +\DoxyCodeLine{NPIX = hp.nside2npix(NSIDE)} +\DoxyCodeLine{thetas, phis = np.degrees(hp.pix2ang(nside=NSIDE, ipix=np.arange(NPIX)))} +\DoxyCodeLine{fname = "{}angle\_pairs.txt"{}} +\DoxyCodeLine{np.savetxt(fname, np.column\_stack((thetas, phis)))} +\DoxyCodeLine{system(f"{}./OMSim\_effective\_area -\/n 10000 -\/-\/environment 1 -\/r 300 -\/-\/angles\_file \{fname\} -\/-\/output\_file output"{})} + +\end{DoxyCode} + + +In my PC, the first code block needs 51 seconds (tested with NSIDE=2), the second block only 14 seconds (as simulation has to be initialised only once). \ No newline at end of file diff --git a/latex/md_3_radioactive_decays.tex b/latex/md_3_radioactive_decays.tex new file mode 100644 index 0000000000..ea9a723ae0 --- /dev/null +++ b/latex/md_3_radioactive_decays.tex @@ -0,0 +1,27 @@ +Study for understanding the background produced by radioactive decays in borosilicate glass of optical modules \& PMTs. + +\begin{quote} +{\bfseries{Warning}}\+: This study has been tested only for Vitrovex glass (m\+DOM/\+LOM16) and the 80mm \mbox{\hyperlink{classm_d_o_m}{m\+DOM}} PMTs. Okamoto glass (D-\/\+Egg/\+LOM18) is currently under investigation. \end{quote} +The simulation considers the measured scintillation parameters and the specific activity of the isotopes to provide insights into the behavior of OMs in both air and ice environments over a time window t\+\_\+w. The number of time windows simulated is given by the argument {\ttfamily -\/-\/numevents}\`{}. + +The primary output is a timestamped list of detected photons, which can be utilized to compute parameters such as the module\textquotesingle{}s expected dark rate. The simulation steps can be summarized as\+: + + +\begin{DoxyItemize} +\item Determining the number of decays within t\+\_\+w based on measured data. +\item Initiating decay chains for each event by positioning an isotope randomly in the pressure vessel. +\item Assigning decay times from a uniform distribution within \mbox{[}0, t\+\_\+w\mbox{]}, in case the time difference between mother-\/daughter decay times surpasses t\+\_\+w. +\item Saving into memory photons detected by the PMTs for downstream analysis. +\end{DoxyItemize} + +Important customizations in the simulation involve the extension of Geant4\textquotesingle{}s original scintillation class, facilitating the simulation of more complex decay processes (8 lifetimes), and the modification of the \mbox{\hyperlink{class_g4_radioactive_decay}{G4\+Radioactive\+Decay}} class which amends default decay time of isotopes. + +The scintillation properties of the \mbox{\hyperlink{classm_d_o_m}{m\+DOM}} glass were measured in the scope of several theses. For a summary check section 11.\+2 of \href{https://zenodo.org/record/8121321}{\texttt{ this thesis}}. + +Currently, there are two analysis modes\+: + + +\begin{DoxyEnumerate} +\item With the {\ttfamily -\/-\/multiplicity\+\_\+study} argument\+: After each t\+\_\+w time window, the multiplicity is calculated and saved to a file. Raw data isn\textquotesingle{}t stored, as multiplicity studies generally involve extended simulation durations, leading to large volumes of photon data. +\item Without the {\ttfamily -\/-\/multiplicity\+\_\+study} argument\+: Data pertaining to photons and decayed isotopes is saved to files. If you are using multithreaded mode, then each thread will produce its own file. +\end{DoxyEnumerate} \ No newline at end of file diff --git a/latex/md_4__s_n.tex b/latex/md_4__s_n.tex new file mode 100644 index 0000000000..14ec8f37d4 --- /dev/null +++ b/latex/md_4__s_n.tex @@ -0,0 +1,161 @@ +This module provides a comprehensive analysis and simulations focusing on the detection of CCSN neutrinos with segmented sensors. + +This simulation is designed to emulate the detection of Core Collapse Supernova (CCSN or simply SN in the following) neutrinos using segmented sensors. It directly generates particles resulting from Inverse Beta Decay (IBD) and Electron Neutrino-\/\+Electron Elastic Scattering (ENES). + + +\begin{DoxyItemize} +\item IBD\+: {\ttfamily ν̄\+\_\+e + p → n + e⁺} +\item ENES\+: {\ttfamily ν\+\_\+e + e⁻ → ν\+\_\+e + e⁻} +\end{DoxyItemize} + +In the IBD case, the outgoing neutron is not simulated; hence, the neutron capture process that might be detected is not included in the simulation. Each event is assigned a weight based on the interaction probability, detailed later on this page. By default, the surrounding ice is represented as a cylinder facing the CCSN, simplifying the weight calculations. + +Although CCSN models incorporate neutrino oscillations, the default simulation does not include any oscillation scenario in the weight calculations. + + ~\newline + Figure 1\+: {\itshape Diagram of the steps involved to generate the events for the simulation of CCSN neutrinos. The scheme is valid for both IBD and ENES, except for the threshold check. Here, {\ttfamily e} stands for both electron from ENES or positron from IBD, and {\ttfamily ν} for both electronic neutrino from ENES or electronic antineutrino from IBD. Image from \href{https://zenodo.org/record/8107177}{\texttt{ this thesis}}.} + +The detailed procedure for this simulation is comprehensively described in \href{https://zenodo.org/record/8107177}{\texttt{ this thesis}}, specifically in section 6.\+4. Below is a summary extracted from this source, outlining the steps taken to generate the events\+: + + +\begin{DoxyEnumerate} +\item Utilizing the models, the expected flux per area is calculated from the luminosity {\ttfamily L(t)} and the mean energy {\ttfamily $<$E(t)$>$} according to {\ttfamily Φ(t) = (1 / (4πd²)) · (L(t) / $<$E(t)$>$)}. +\item The distribution of {\ttfamily Φ(t)} is used to sample a time {\ttfamily t} of the burst via the inverse CDF (Cumulative Distribution Function) method. All other sampling from distributions within this simulation also employs the inverse CDF method. +\item For the sampled time {\ttfamily t}, the corresponding mean energy and mean squared energy are extracted from the models. These parameters contribute to the construction of the energy spectrum {\ttfamily f(\+E,t)}, as elucidated in \href{https://arxiv.org/pdf/1211.3920.pdf}{\texttt{ this paper}}. +\item The energy of the neutrino/antineutrino {\ttfamily E\+\_\+ν} is sampled from {\ttfamily f(\+E,t)}. If the energy falls below the IBD threshold, the algorithm reverts to the second step. +\item From {\ttfamily E\+\_\+ν}, the angular cross section is devised. This informs the sampling of the angle {\ttfamily θ} between the incoming neutrino and the resulting {\ttfamily e⁻/e⁺}. The {\ttfamily φ} direction is randomly generated within the range of {\ttfamily 0} to {\ttfamily 2π}. +\item The energy of {\ttfamily e⁻/e⁺} is deduced from {\ttfamily θ} and {\ttfamily E\+\_\+ν}. The interaction probability for such an event is ascertained using the total cross section, facilitating the computation of the interaction weight, as further described below. +\item The {\ttfamily e⁻/e⁺} is manifested at a random position within the ice volume. +\end{DoxyEnumerate}\hypertarget{md_4__s_n_autotoc_md17}{}\doxysection{Input Parameters}\label{md_4__s_n_autotoc_md17} +Execute {\ttfamily ./\+OMSim\+\_\+supernova -\/-\/help} to display all possible input parameters. + +A typical command to run the simulation is\+: + + +\begin{DoxyCode}{0} +\DoxyCodeLine{./OMSim\_supernova -\/n 100 -\/-\/wheight 20 -\/-\/wradius 20 -\/-\/depth\_pos 75 -\/-\/SNgun 0 -\/-\/SNtype 0} + +\end{DoxyCode} +\hypertarget{md_4__s_n_autotoc_md18}{}\doxysubsection{General Parameters}\label{md_4__s_n_autotoc_md18} + +\begin{DoxyItemize} +\item {\ttfamily -\/-\/depth\+\_\+pos}\+: Index of the vector determining the depth of the simulated modules. Notable values include the dust layer (65), mean ice properties (approx) 75, and the cleanes ice (88). This selection affects the effective scattering and absorption lengths of the ice at the specified depth. +\item {\ttfamily -\/o}\+: Output file name. By default, two output files are created\+: one containing the simulated event information, and another with detection data. +\end{DoxyItemize}\hypertarget{md_4__s_n_autotoc_md19}{}\doxysubsection{SN Framework Parameters}\label{md_4__s_n_autotoc_md19} + +\begin{DoxyItemize} +\item {\ttfamily -\/-\/wheight}\+: Height of the ice\textquotesingle{}s simulated world cylinder. +\item {\ttfamily -\/-\/wradius}\+: Radius of the ice\textquotesingle{}s simulated world cylinder. +\item {\ttfamily -\/-\/SNgun}\+: Chooses the interaction type (0 for IBD, 1 for ENES). +\item {\ttfamily -\/-\/SNtype}\+: Selects the CCSN model. Two models are currently available, provided by the Garching group. These models represent the expected fluxes from two CCSNs resulting in neutron stars, with different progenitor masses (27 and 9.\+6 solar masses). Simulations yielding this data can be found at \href{https://arxiv.org/abs/1510.04643}{\texttt{ https\+://arxiv.\+org/abs/1510.\+04643}} +\end{DoxyItemize}\hypertarget{md_4__s_n_autotoc_md20}{}\doxysubsection{Fixed Energy Studies}\label{md_4__s_n_autotoc_md20} +The user can also manually set the mean energy of generated events by providing specific input parameters. For instance\+: + + +\begin{DoxyCode}{0} +\DoxyCodeLine{-\/-\/SNfixEnergy -\/-\/SNmeanE 10.0 -\/-\/SNalpha 3.0} + +\end{DoxyCode} + + + +\begin{DoxyItemize} +\item {\ttfamily -\/-\/SNfix\+Energy}\+: Acts as a flag parameter. When invoked, the simulation disregards the actual mean energy of neutrinos corresponding to the burst time. Instead, it adopts the mean energy and the pinching parameter specified by the subsequent two parameters. +\item {\ttfamily -\/-\/SNmeanE}\+: Specifies the mean energy of the neutrinos. +\item {\ttfamily -\/-\/SNalpha}\+: Defines the pinching parameter of the energy distribution (see \href{https://arxiv.org/pdf/1211.3920.pdf}{\texttt{ this paper}}). +\end{DoxyItemize} + +Consequently, the neutrinos\textquotesingle{} energy is sampled from the distribution, derived from these two parameters and the previously mentioned model.\hypertarget{md_4__s_n_autotoc_md21}{}\doxysection{Output Files}\label{md_4__s_n_autotoc_md21} +Two files are produced\+:\hypertarget{md_4__s_n_autotoc_md22}{}\doxysubsection{$\ast$\+\_\+info.\+dat}\label{md_4__s_n_autotoc_md22} +This file encapsulates data concerning each generated neutrino event. Each entry contains\+: + + +\begin{DoxyItemize} +\item Time of the neutrino burst. +\item Corresponding mean energy derived from the model. +\item Sampled neutrino energy {\ttfamily E\+\_\+ν}. +\item {\ttfamily cos(θ)}, where {\ttfamily θ} is the angle between the incoming neutrino and the outgoing particle (e-\/ or e+). +\item Energy of the outgoing particle (e-\/ or e+). +\item Interaction weight, calculated using the formula\+: +\end{DoxyItemize} + + +\begin{DoxyCode}{0} +\DoxyCodeLine{W\_int(E\_ν) = σ(E) · n\_target · l,} + +\end{DoxyCode} + + +where\+: +\begin{DoxyItemize} +\item {\ttfamily σ(\+E)} is the total cross section for the interaction, +\item {\ttfamily n\+\_\+target} is the number of targets available for the interaction in the ice, +\item {\ttfamily l} is the length of the simulated cylindrical world. +\end{DoxyItemize}\hypertarget{md_4__s_n_autotoc_md23}{}\doxysubsection{$\ast$\+\_\+data.\+dat}\label{md_4__s_n_autotoc_md23} +This file contains the detection information. Its structure is designed to facilitate various trigger studies, allowing the examination of different time windows. Users might evaluate its structure for convenience, particularly if the trigger check is integrated within the simulation (requiring a predefined time window). + +The default content structure is as follows\+: + + +\begin{DoxyCode}{0} +\DoxyCodeLine{Total hits | Modules hit | PMTs hit | "{}...for each PMT hit..."{} | Module number | PMT number | Hits in that PMT | "{}...for each Hit..."{} | hit time |} + +\end{DoxyCode} + + +Note that the number of columns varies per line, contingent on the number of photons detected for the simulated neutrinos.\hypertarget{md_4__s_n_autotoc_md24}{}\doxysection{Weights}\label{md_4__s_n_autotoc_md24} +The output files contain the interaction weight. However, users should also consider a weight factor depending on the total flux and the number of simulated events. In the most general case of simulating a single depth and then extrapolating the results to the entire detector, another weight factor is needed. This factor accounts for the ice properties of the simulated depth with respect to the whole detector. This last factor decreases in importance when using high multiplicity conditions, since these events generally interact closer to the module, making the photons less sensitive to changes in the optical properties. + +These weight factors can be added similarly as explained in \href{https://zenodo.org/record/8107177}{\texttt{ this thesis, section 6.\+4.\+2}}. + +The total weight is composed of 3 components\+: the interaction probability, the SN flux through the simulated volume, and the different optical properties of the modules at different depths\+: + + +\begin{DoxyCode}{0} +\DoxyCodeLine{W = W\_int(E) · W\_flux(d) · W\_eff.} + +\end{DoxyCode} + + +Each component is explained as follows\+:\hypertarget{md_4__s_n_autotoc_md25}{}\doxysubsection{Interaction Probability Weight\+:}\label{md_4__s_n_autotoc_md25} + +\begin{DoxyCode}{0} +\DoxyCodeLine{W\_int(E\_ν) = σ(E) · n\_target · l,} + +\end{DoxyCode} + where {\ttfamily σ(E\+\_\+ν)} is the total cross section for the interaction, {\ttfamily n\+\_\+target} is the number of targets per unit of volume for such interaction, and {\ttfamily l=40 m} is the length of the generation volume along the neutrino direction axis. This is the length of the cylinder facing the CCSN.\hypertarget{md_4__s_n_autotoc_md26}{}\doxysubsection{Flux Weight\+:}\label{md_4__s_n_autotoc_md26} + +\begin{DoxyCode}{0} +\DoxyCodeLine{W\_flux(d) = (1 / N\_gen) · (r² / d²) · ∫ (L(t) / ) dt,} + +\end{DoxyCode} + where {\ttfamily r} is the cylindrical generation volume\textquotesingle{}s radius, {\ttfamily d} is the distance from Earth where the CCSN is assumed to occur, and {\ttfamily N\+\_\+gen} is the number of generated events.\hypertarget{md_4__s_n_autotoc_md27}{}\doxysubsection{Effective Weight\+:}\label{md_4__s_n_autotoc_md27} + +\begin{DoxyCode}{0} +\DoxyCodeLine{W\_eff = N\_modules · ( / V\_eff(m,z\_sim)),} + +\end{DoxyCode} + where {\ttfamily N\+\_\+modules} is the total modules in the simulated detector, {\ttfamily V\+\_\+eff(m, z\+\_\+sim)} is the effective volume at the simulation depth, and {\ttfamily $<$V\+\_\+eff(m)$>$} is the mean effective volume for all modules in simulated detector. The term {\ttfamily m} represents multiplicity, defined as the count of different PMTs within a single module that detected the event within a specific time window. + +The effective volume can be calculated in different ways. Old simulations of the \mbox{\hyperlink{classm_d_o_m}{m\+DOM}}, described in \href{https://zenodo.org/record/8107177}{\texttt{ this thesis, section 6.\+3}}, were used in past studies. A linear regression of the effective volume concerning the absorption length, derived from various depths, provides each depth\textquotesingle{}s effective volume. Although it is advisable to redo these simulations with a current \mbox{\hyperlink{classm_d_o_m}{m\+DOM}} model, users can temporarily use the old data with a regression line of {\ttfamily V\+\_\+eff = b · x + c}, where {\ttfamily x = 1/a} is the inverse of the absorption length. The coefficients {\ttfamily b} and {\ttfamily c}, depending on the event\textquotesingle{}s multiplicity, were obtained as follows\+: + +\tabulinesep=1mm +\begin{longtabu}spread 0pt [c]{*{3}{|X[-1]}|} +\hline +\PBS\centering \cellcolor{\tableheadbgcolor}\textbf{ Multiplicity }&\PBS\centering \cellcolor{\tableheadbgcolor}\textbf{ b (slope, m²) }&\PBS\centering \cellcolor{\tableheadbgcolor}\textbf{ c (m³) }\\\cline{1-3} +\endfirsthead +\hline +\endfoot +\hline +\PBS\centering \cellcolor{\tableheadbgcolor}\textbf{ Multiplicity }&\PBS\centering \cellcolor{\tableheadbgcolor}\textbf{ b (slope, m²) }&\PBS\centering \cellcolor{\tableheadbgcolor}\textbf{ c (m³) }\\\cline{1-3} +\endhead +1 &15.\+1843 &0.\+000 \\\cline{1-3} +2 &0.\+1352 &47.\+005 \\\cline{1-3} +3 &0.\+0306 &16.\+170 \\\cline{1-3} +4 &0.\+0095 &8.\+680 \\\cline{1-3} +5 &0.\+0039 &5.\+105 \\\cline{1-3} +$>$= 6 &0.\+0026 &2.\+909 \\\cline{1-3} +\end{longtabu} + + +Note that, for more than 5 PMTs, the same fit line is employed due to insufficient statistics at higher PMTs in the effective volume simulation. Additionally, since the absorption length depends on the wavelength, the fits above were obtained assuming a wavelength of {\ttfamily λ = 400 nm}. \ No newline at end of file diff --git a/latex/modules.tex b/latex/modules.tex index 59902ac637..606b615232 100644 --- a/latex/modules.tex +++ b/latex/modules.tex @@ -1,8 +1,7 @@ \doxysection{Modules} Here is a list of all modules\+:\begin{DoxyCompactList} -\item \contentsline{section}{OMSim framework and geometry}{\pageref{group__common}}{} +\item \contentsline{section}{Common framework}{\pageref{group__common}}{} \item \contentsline{section}{Effective area}{\pageref{group___effective_area}}{} \item \contentsline{section}{Radioactive decays}{\pageref{group__radioactive}}{} \item \contentsline{section}{Supernova Studies}{\pageref{group__sngroup}}{} -\item \contentsline{section}{Bubble column}{\pageref{group__bubble}}{} \end{DoxyCompactList} diff --git a/latex/radioactive__decays_2include_2_o_m_sim_event_action_8hh__incl.pdf 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b/latex/radioactive__decays_2include_2_o_m_sim_primary_generator_action_8hh__incl.pdf differ diff --git a/latex/refman.tex b/latex/refman.tex index 1ed74bbf3b..6ec0411b38 100644 --- a/latex/refman.tex +++ b/latex/refman.tex @@ -171,12 +171,28 @@ \hypersetup{pageanchor=true} %--- Begin generated contents --- -\chapter{OMSim} +\chapter{OMSim Geant4 Framework} \label{index}\hypertarget{index}{}\input{index} -\chapter{Multi-\/threading in Geant4} -\label{md_multithreading} -\Hypertarget{md_multithreading} -\input{md_multithreading} +\chapter{Framework functionality} +\label{md_0_common} +\Hypertarget{md_0_common} +\input{md_0_common} +\chapter{Multi-\/threading mode} +\label{md_1_multithreading} +\Hypertarget{md_1_multithreading} +\input{md_1_multithreading} +\chapter{Effective Area Study} +\label{md_2_effective_area} +\Hypertarget{md_2_effective_area} +\input{md_2_effective_area} +\chapter{Radioactive Decays Study} +\label{md_3_radioactive_decays} +\Hypertarget{md_3_radioactive_decays} +\input{md_3_radioactive_decays} +\chapter{Supernova Studies} +\label{md_4__s_n} +\Hypertarget{md_4__s_n} +\input{md_4__s_n} \chapter{Todo List} \label{todo} \Hypertarget{todo} @@ -194,7 +210,6 @@ \chapter{Module Documentation} \input{group___effective_area} \input{group__radioactive} \input{group__sngroup} -\input{group__bubble} \chapter{Class Documentation} \input{struct_c_a_d_mesh_1_1_file_1_1_____final_state} \input{classabc_data_file} diff --git a/latex/struct_c_a_d_mesh_1_1_file_1_1_____final_state__coll__graph.pdf b/latex/struct_c_a_d_mesh_1_1_file_1_1_____final_state__coll__graph.pdf index 15fbb117fc..1d50d788ab 100644 Binary files a/latex/struct_c_a_d_mesh_1_1_file_1_1_____final_state__coll__graph.pdf and b/latex/struct_c_a_d_mesh_1_1_file_1_1_____final_state__coll__graph.pdf differ diff --git a/latex/struct_c_a_d_mesh_1_1_file_1_1_____final_state__inherit__graph.pdf b/latex/struct_c_a_d_mesh_1_1_file_1_1_____final_state__inherit__graph.pdf index 15fbb117fc..1d50d788ab 100644 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                                                                                        +
                                                                                        +

                                                                                        Files

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                                                                                        OMSim +
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                                                                                        Geant4 for IceCube optical module studies
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                                                                                        Framework functionality
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                                                                                        +

                                                                                        Table of Contents

                                                                                        + +
                                                                                        +

                                                                                        This framework offers tools to simplify geometry construction and material definitions, as well as a detailed PMT response mechanism. This page provides a brief introduction to the main features.

                                                                                        +

                                                                                        +Materials and User Data

                                                                                        +

                                                                                        User-defined material data are stored in JSON files under /common/data to minimize file length (the original detector construction had over 4,000 lines, mainly due to material properties!).

                                                                                        +

                                                                                        The InputDataManager (see OMSimInputData.hh) loads these properties directly into the Geant4 framework. Materials loaded via this class can be retrieved using Geant4's conventional method G4Material::GetMaterial, but the framework also provides the wrapper InputDataManager::getMaterial to handle default parameters.

                                                                                        +

                                                                                        The class also provides an analogue method for optical surfaces InputDataManager::getOpticalSurface which does not exist in Geant4.

                                                                                        +

                                                                                        Since different materials have different types of properties, the data is loaded in multiple ways. These different material types are defined in OMSimDataFileTypes.hh.

                                                                                        +

                                                                                        Additionally, geometry data used during PMT construction are also stored in JSON files (/common/data/PMTs). These are saved in a "tree" (essentially a dictionary containing the JSON file's keys and values) in InputDataManager::mTable.

                                                                                        +

                                                                                        This approach was adopted because various PMTs are constructed similarly, eliminating the need to define a unique class for each PMT type, as is done for the optical modules.

                                                                                        +

                                                                                        Thus, an instance of InputDataManager is always passed to all classes related to geometry construction (see geometry).

                                                                                        +

                                                                                        If you wish to load additional data, you can either define a new type in OMSimDataFileTypes or load it into a tree as previously mentioned. For simpler tasks, use the static method InputDataManager::loadtxt, which operates similarly to Python's numpy.loadtxt. For example:

                                                                                        +
                                                                                        std::vector<G4PV2DDataVector> data = InputDataManager::loadtxt("path/file_name.txt");
                                                                                        +
                                                                                        std::vector<G4double> first_column = data.at(0);
                                                                                        +
                                                                                        std::vector<G4double> second_column = data.at(1);
                                                                                        +
                                                                                        // ...
                                                                                        +
                                                                                        InputDataManager::loadtxt
                                                                                        static std::vector< std::vector< double > > loadtxt(const std::string &pFilePath, bool pUnpack=true, size_t pSkipRows=0, char pDelimiter=' ')
                                                                                        Reads numerical data from a file and returns it as a 2D vector. Similar to numpy.loadtxt.
                                                                                        Definition: OMSimInputData.cc:135
                                                                                        +

                                                                                        +Geometry construction

                                                                                        +

                                                                                        Each optical module and harness is defined in its respective class, located in the /common/geometry_construction/ folder. These inherit from the virtual base class OMSimOpticalModule.

                                                                                        +

                                                                                        This inheritance ensures the definition of functions to retrieve the pressure vessel's weight (necessary for radioactive decay studies) and the count of PMTs inside the module. The OMSimOpticalModule interface inherits from abcDetectorComponent, a general helper class simplifying construction. Most OMSim geometries inherit from this class, as illustrated in the dependency diagram below:

                                                                                        +

                                                                                        Inheritance diagram

                                                                                        +

                                                                                        The OMSimPMTConstruction class constructs PMTs. There are two PMT construction approaches. The first is simple, with a solid photocathode where all entering photons are recorded. The second type simulates the photocathode as a thin layer, also representing the internal components accounting for internal reflections. For more information, refer to Chapter 9 of Martin Unland's thesis.

                                                                                        +

                                                                                        The construction of different PMT models (e.g. the 3'' or 10'' PMTs) is quite similar. However, the frontal window shape varies among models, leading to diverse combinations of ellipsoids and spheres.

                                                                                        +
                                                                                        Cross section of simple mDOM PMT model

                                                                                        + Figure 1: Cross section of simple mDOM PMT model. Image from M. Unland's thesis.
                                                                                        Side view of complex mDOM PMT model

                                                                                        + Figure 2: Side view of complex mDOM PMT model. Image from M. Unland's thesis.

                                                                                        In the complex PMT model, the photocathode has an absorption length that matches the measured quantum efficiency of the mDOM PMTs. For the other PMT models, this matching still has to be performed.

                                                                                        +
                                                                                        QE of simulation compared to measurements

                                                                                        + Figure 3: QE of simulation with the absorption length currently used compared to measurements. Image from M. Unland's thesis.

                                                                                        +PMT Response and Saving Hits

                                                                                        +
                                                                                        +

                                                                                        Warning: Only the mDOM PMT currently supports a detailed PMT response.

                                                                                        +
                                                                                        +

                                                                                        For photon detection in both simple and complex geometries, the photons must be absorbed within the photocathode volume. The PMTs' photocathodes are made sensitive through the OMSimSensitiveDetector class, following Geant4's G4VSensitiveDetector pattern. This configuration is achieved by invoking OMSimOpticalModule::configureSensitiveVolume (or OMSimPMTConstruction::configureSensitiveVolume when simulating a single PMT).

                                                                                        +

                                                                                        It is essential to invoke this method in the detector construction, as it needs the instance of OMSimDetectorConstruction to call G4VUserDetectorConstruction::SetSensitiveDetector for successful operation in Geant4 (refer to OMSimDetectorConstruction::registerSensitiveDetector).

                                                                                        +

                                                                                        Every step of a particle through the photocathode triggers the OMSimSensitiveDetector::ProcessHits method. It verifies if the particle is a photon and whether it was absorbed. For a deeper understanding of Geant4's philosophy concerning G4VSensitiveDetector, consult the Geant4 guide for application developers.

                                                                                        +

                                                                                        In OMSimPMTConstruction::configureSensitiveVolume, PMTs are associated with an instance of OMSimPMTResponse, contingent on the PMT under simulation. This class offers a precise PMT simulation by sampling from real measurements, obtaining the relative transit time, charge (in PE), and detection probability (using the measured scans from M. Unland's thesis). For details, refer to Section 9.3.4 of the linked thesis.

                                                                                        +

                                                                                        This sampling is performed for every absorbed photon in OMSimSensitiveDetector::ProcessHits invoking OMSimPMTResponse::processPhotocathodeHit.

                                                                                        +
                                                                                        PMT response compared to measurement

                                                                                        + Figure 4: PMT response compared to measurement for different light sources. Image from M. Unland's thesis.

                                                                                        The data of absorbed photons is managed by the OMSimHitManager singleton. To analyze and export this data, consult example methods like OMSimEffectiveAreaAnalyisis::writeScan and OMSimDecaysAnalysis::writeHitInformation for direction.

                                                                                        +

                                                                                        An additional feature allows for the direct application of a QE cut. This ensures that only absorbed photons passing the QE test are retained in OMSimHitManager. To enable this feature, provide the "QE_cut" argument via the command line. In this case OMSimSensitiveDetector::ProcessHits will call OMSimPMTResponse::passQE and break early if it returns false, without storing the photon information.

                                                                                        +
                                                                                        +

                                                                                        Note: In most scenarios, it's not recommended to use –QE_cut since it reduces your statistics. Its presence in OMSim is primarily for testing purposes. It's generally better to perform post-analysis using the saved OMSimPMTResponse::PMTPulse::detectionProbability for each absorbed photon.

                                                                                        +
                                                                                        +

                                                                                        +Making other volumes sensitive to photons

                                                                                        +

                                                                                        For some studies, you might want a volume to detect photons, without this necessarily being a PMT. For such cases, the framework has a provision in place: use the OMSimSensitiveDetector and pass DetectorType::GeneralPhotonDetector as its constructor argument.

                                                                                        +

                                                                                        In this case, the OMSimSensitiveDetector::ProcessHits will use an instance NoResponse as PMT response, which is just a dummy placeholder.
                                                                                        +

                                                                                        +

                                                                                        Remember to inform the OMSimHitManager that this detector is equivalent to "a single PMT", ensuring internal vector sizes adjust accordingly.

                                                                                        +

                                                                                        This approach ensures a smooth integration of the photosensitive volume within the current system. Below is an example illustrating how this can be incorporated within the detector construction:

                                                                                        +
                                                                                        #include "OMSimSensitiveDetector.hh"
                                                                                        +
                                                                                        //... Assume the logical volume of your detector has been defined and is referred to as "lDetectorLV"
                                                                                        +
                                                                                        OMSimSensitiveDetector* lSensitiveDetector = new OMSimSensitiveDetector("myDetector", DetectorType::GeneralPhotonDetector);
                                                                                        +
                                                                                        OMSimHitManager lHitManager = OMSimHitManager::getInstance();
                                                                                        +
                                                                                        lHitManager.setNumberOfPMTs(1, lHitManager.getNextDetectorIndex());
                                                                                        +
                                                                                        registerSensitiveDetector(lDetectorLV, lSensitiveDetector);
                                                                                        +
                                                                                        OMSimHitManager
                                                                                        Manages detected photon information.
                                                                                        Definition: OMSimHitManager.hh:57
                                                                                        +
                                                                                        OMSimHitManager::getInstance
                                                                                        static OMSimHitManager & getInstance()
                                                                                        Returns the singleton instance of the OMSimHitManager.
                                                                                        Definition: OMSimHitManager.cc:17
                                                                                        +
                                                                                        OMSimHitManager::setNumberOfPMTs
                                                                                        void setNumberOfPMTs(int pNumberOfPMTs, int pModuleIndex=0)
                                                                                        Stores the number of PMTs in a module for correct data handling.
                                                                                        Definition: OMSimHitManager.cc:127
                                                                                        +
                                                                                        OMSimSensitiveDetector
                                                                                        Represents a sensitive detector.
                                                                                        Definition: OMSimSensitiveDetector.hh:51
                                                                                        +

                                                                                        In this case, OMSimSensitiveDetector::ProcessHits will store all absorbed photons. The number of photons absorbed will depend on the absorption length of the material connected to the logical volume.

                                                                                        +

                                                                                        If there's a need to make a volume sensitive to particles other than photons, add a new entry to the DetectorType enum (in OMSimSensitiveDetector.hh) and incorporate a new method that handles this scenario in OMSimSensitiveDetector::ProcessHits.

                                                                                        +

                                                                                        You might also track these particles in OMSimTrackingAction or OMSimSteppingAction, but using a class derived from G4VSensitiveDetector aligns with the philosophy of Geant4.

                                                                                        +
                                                                                        +
                                                                                        +
                                                                                        + + + + diff --git a/md_multithreading.html b/md_1_multithreading.html similarity index 96% rename from md_multithreading.html rename to md_1_multithreading.html index d1e229d77b..470714c468 100644 --- a/md_multithreading.html +++ b/md_1_multithreading.html @@ -5,7 +5,7 @@ -OMSim: Multi-threading in Geant4 +OMSim: Multi-threading mode @@ -94,7 +94,7 @@
                                                                                        @@ -114,20 +114,21 @@
                                                                                        -
                                                                                        Multi-threading in Geant4
                                                                                        +
                                                                                        Multi-threading mode

                                                                                        Table of Contents

                                                                                        -
                                                                                        -

                                                                                        +

                                                                                        The OMSim-Framework allows for multi-threading. The number of threads can be controlled with the --threads argument (default 1). If you specify more threads than available, only the maximum available will be used.

                                                                                        +

                                                                                        Introduction

                                                                                        Geant4 implements multi-threading using a master-worker model:

                                                                                          @@ -139,7 +140,7 @@
                                                                                        1. Each thread has its own instance of sensitive detectors, event and tracking managers.
                                                                                        2. Random number generators are designed to produce independent streams for each thread.

                                                                                      -

                                                                                      +

                                                                                      Thread Safety Guidelines

                                                                                      1. Use Thread-Local Storage: For data unique to each thread, use G4ThreadLocal.
                                                                                        2. @@ -147,7 +148,7 @@

                                                                                      2. Minimize Global Variables: Prefer class members or local variables instead.
                                                                                      3. Implement Thread-Safe Containers: Ensure thread-safe access and modification of containers.

                                                                                      -

                                                                                      +

                                                                                      Thread-Safe Singleton Implementation

                                                                                      Both OMSimHitManager and OMSimDecaysAnalysis utilize the singleton pattern with a thread-safe getInstance method. This method employs a double-checked locking pattern to ensure thread safety while minimizing synchronization overhead. The process works as follows:

                                                                                        @@ -173,7 +174,7 @@

                                                                                        Note: While this singleton implementation is thread-safe, consider whether a singleton is the best design choice for your specific use case. Singletons can sometimes lead to issues with testability and create hidden dependencies.

                                                                                        -

                                                                                        +

                                                                                        Example: OMSimHitManager

                                                                                        The OMSimHitManager class demonstrates several thread-safety techniques:

                                                                                        class OMSimHitManager
                                                                                        @@ -234,7 +235,7 @@

                                                                                        Important: Call mergeThreadData after all threads have finished simulating (after a run has completed).

                                                                                        -

                                                                                        +

                                                                                        Example: Saving Data Per Thread

                                                                                        In scenarios where merging data is unnecessary, or the amount of data is too large to wait until end of run, each thread can save its data in separate files. This is demonstrated in the OMSimDecaysAnalysis class.

                                                                                          @@ -299,7 +300,7 @@

                                                                                          lAnalysisManager.reset();
                                                                                          }
                                                                                          OMSimDecaysAnalysis::writeMultiplicity
                                                                                          void writeMultiplicity(G4double pTimeWindow)
                                                                                          Calls calculateMultiplicity and writes the results to the output file.
                                                                                          Definition: OMSimDecaysAnalysis.cc:60
                                                                                          -

                                                                                          +

                                                                                          Best Practices for Creating New Thread-Safe Containers

                                                                                          When implementing new thread-safe containers in Geant4:

                                                                                            @@ -334,7 +335,7 @@

                                                                                            diff --git a/1effective_area_8h_source.html b/md_2_effective_area.html similarity index 50% rename from 1effective_area_8h_source.html rename to md_2_effective_area.html index ccd8c745ab..9b4aadc6aa 100644 --- a/1effective_area_8h_source.html +++ b/md_2_effective_area.html @@ -5,7 +5,7 @@ -OMSim: 1effectiveArea.h Source File +OMSim: Effective Area Study @@ -94,7 +94,7 @@
                                                                                            @@ -112,19 +112,67 @@
                                                                                            -
                                                                                            +
                                                                                            -
                                                                                            1effectiveArea.h
                                                                                            +
                                                                                            Effective Area Study
                                                                                            -
                                                                                            1 
                                                                                            -
                                                                                            +

                                                                                            Table of Contents

                                                                                            + +
                                                                                            +

                                                                                            In the folder effective_area you find the files pertinent to the effective area studies.

                                                                                            +

                                                                                            +Introduction to effective areas

                                                                                            +
                                                                                            +

                                                                                            Note: In the following, a short introduction of an effective area study is made with the mDOM as an example. For further details see Chapter 10 of Lew Classen's thesis or Section 9.3.5 of Martin Unland's thesis.

                                                                                            +
                                                                                            +

                                                                                            During the design of a module, its sensitivity is optimised by considering the optical properties of various materials and altering the geometry and positioning of the mechanical components in the Geant4 simulation.

                                                                                            +

                                                                                            The metric to optimise the module's sensitivity is the effective area A_eff(θ, φ). This represents the area that is detected from a plane wave of incidence angle of θ (zenith) and φ (azimuth) with respect to the module. This parameter is calculated with OMSim by simulating a disk emitting mono-energetic photons perpendicular to its surface with a uniform density profile.

                                                                                            +

                                                                                            The photon generation is made with the module AngularScan, running the method AngularScan::runSingleAngularScan once for each direction to be investigated.

                                                                                            +
                                                                                            mDOM illuminated by a disk emitter

                                                                                            + Figure 1: Screenshot of an mDOM illuminated by a disk emitter simulating the incidence of a plane wave from the direction θ (zenith) and φ (azimuth) using the Geant4 visualiser. The photon trajectories are represented by orange lines, and yellow dots mark the locations of physical interactions. Image taken from this thesis.

                                                                                            After simulating N photons from a plane of area A_rad (which has to be larger than the projected area of the mDOM), the effective area is calculated as

                                                                                            +

                                                                                            $$ A_{\mathrm{eff}}(\theta, \phi) = \frac{N_{\mathrm{det}}(\theta, \phi)}{N}\cdot A_{\mathrm{rad}}, $$

                                                                                            +

                                                                                            where N_det is the number of photons detected by the module. To optimise the sensitivity over multiple directions, A_eff(θ, φ) is calculated for various angle pairs, and the mean effective area, A_eff_mean, is determined. The n angle pairs are chosen using healpix, which separates a sphere into n pixels of equal area. Thus,

                                                                                            +

                                                                                            $$ \overline{A}_{\mathrm{eff}} = \frac{1}{n}\sum_{i=1}^n A_{\mathrm{eff}}(\theta_i, \phi_i). $$

                                                                                            +

                                                                                            Since the effective area is wavelength dependent, the calculation must be repeated for different wavelengths. Wavelengths shorter than 300nm are absorbed by the pressure vessel, whereas the QE of the PMT approaches zero at wavelengths longer than 700nm.

                                                                                            +

                                                                                            +Example using healpy

                                                                                            +

                                                                                            In the following, an example of the usage of the effective area module is given. Although there are C++ healpix libraries, in my opinion, the easiest way of getting the angle pair coordinates is using Healpy in Python.

                                                                                            +

                                                                                            In principle, for short simulations, you could run the program directly from Python using the angles from healpy as input parameters:

                                                                                            +
                                                                                            import healpy as hp
                                                                                            +
                                                                                            import numpy as np
                                                                                            +
                                                                                            from os import system
                                                                                            +
                                                                                            +
                                                                                            NSIDE = 8 #only powers of 2 allowed, the larger, the more pixels are calculated
                                                                                            +
                                                                                            NPIX = hp.nside2npix(NSIDE)
                                                                                            +
                                                                                            thetas, phis = np.degrees(hp.pix2ang(nside=NSIDE, ipix=np.arange(NPIX)))
                                                                                            +
                                                                                            +
                                                                                            for i, (theta, phi) in enumerate(zip(thetas, phis)):
                                                                                            +
                                                                                            if i==0:
                                                                                            +
                                                                                            system(f"./OMSim_effective_area -n 10000 --environment 1 -r 300 -t {theta} -f {phi} --output_file output")
                                                                                            +
                                                                                            else:
                                                                                            +
                                                                                            system(f"./OMSim_effective_area -n 10000 --environment 1 -r 300 -t {theta} -f {phi} --output_file output --no_header")
                                                                                            +

                                                                                            However, this is quite inefficient. The best is to save the angle pairs into a file and pass it as an argument. If you give a file as an argument, the arg theta and phi are ignored.

                                                                                            +
                                                                                            import healpy as hp
                                                                                            +
                                                                                            import numpy as np
                                                                                            +
                                                                                            from os import system
                                                                                            +
                                                                                            +
                                                                                            NSIDE = 8 #only powers of 2 allowed, the larger, the more pixels are calculated
                                                                                            +
                                                                                            NPIX = hp.nside2npix(NSIDE)
                                                                                            +
                                                                                            thetas, phis = np.degrees(hp.pix2ang(nside=NSIDE, ipix=np.arange(NPIX)))
                                                                                            +
                                                                                            fname = "angle_pairs.txt"
                                                                                            +
                                                                                            np.savetxt(fname, np.column_stack((thetas, phis)))
                                                                                            +
                                                                                            system(f"./OMSim_effective_area -n 10000 --environment 1 -r 300 --angles_file {fname} --output_file output")
                                                                                            +

                                                                                            In my PC, the first code block needs 51 seconds (tested with NSIDE=2), the second block only 14 seconds (as simulation has to be initialised only once).

                                                                                            +
                                                                                            + diff --git a/group__bubble.html b/md_3_radioactive_decays.html similarity index 69% rename from group__bubble.html rename to md_3_radioactive_decays.html index 35a358c3f6..d83795347b 100644 --- a/group__bubble.html +++ b/md_3_radioactive_decays.html @@ -5,7 +5,7 @@ -OMSim: Bubble column +OMSim: Radioactive Decays Study @@ -94,7 +94,7 @@
                                                                                            @@ -112,22 +112,37 @@
                                                                                            -
                                                                                            +
                                                                                            -
                                                                                            Bubble column
                                                                                            +
                                                                                            Radioactive Decays Study
                                                                                            - -


                                                                                            - -

                                                                                            -

                                                                                            - Figure: A brief description of the image
                                                                                            +

                                                                                            Study for understanding the background produced by radioactive decays in borosilicate glass of optical modules & PMTs.

                                                                                            +
                                                                                            +

                                                                                            Warning: This study has been tested only for Vitrovex glass (mDOM/LOM16) and the 80mm mDOM PMTs. Okamoto glass (D-Egg/LOM18) is currently under investigation.

                                                                                            +
                                                                                            +

                                                                                            The simulation considers the measured scintillation parameters and the specific activity of the isotopes to provide insights into the behavior of OMs in both air and ice environments over a time window t_w. The number of time windows simulated is given by the argument --numevents`.

                                                                                            +

                                                                                            The primary output is a timestamped list of detected photons, which can be utilized to compute parameters such as the module's expected dark rate. The simulation steps can be summarized as:

                                                                                            +
                                                                                              +
                                                                                            • Determining the number of decays within t_w based on measured data.
                                                                                              • +
                                                                                            • Initiating decay chains for each event by positioning an isotope randomly in the pressure vessel.
                                                                                              • +
                                                                                            • Assigning decay times from a uniform distribution within [0, t_w], in case the time difference between mother-daughter decay times surpasses t_w.
                                                                                              • +
                                                                                            • Saving into memory photons detected by the PMTs for downstream analysis.
                                                                                              • +
                                                                                            +

                                                                                            Important customizations in the simulation involve the extension of Geant4's original scintillation class, facilitating the simulation of more complex decay processes (8 lifetimes), and the modification of the G4RadioactiveDecay class which amends default decay time of isotopes.

                                                                                            +

                                                                                            The scintillation properties of the mDOM glass were measured in the scope of several theses. For a summary check section 11.2 of this thesis.

                                                                                            +

                                                                                            Currently, there are two analysis modes:

                                                                                            +
                                                                                              +
                                                                                            1. With the --multiplicity_study argument: After each t_w time window, the multiplicity is calculated and saved to a file. Raw data isn't stored, as multiplicity studies generally involve extended simulation durations, leading to large volumes of photon data.
                                                                                              2. +
                                                                                            2. Without the --multiplicity_study argument: Data pertaining to photons and decayed isotopes is saved to files. If you are using multithreaded mode, then each thread will produce its own file.
                                                                                              3. +
                                                                                            +
                                                                                            + diff --git a/md_4__s_n.html b/md_4__s_n.html new file mode 100644 index 0000000000..0050075d4f --- /dev/null +++ b/md_4__s_n.html @@ -0,0 +1,258 @@ + + + + + + + +OMSim: Supernova Studies + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                                                                                            +
                                                                                            + + + + + + + +
                                                                                            +
                                                                                            OMSim +
                                                                                            +
                                                                                            Geant4 for IceCube optical module studies
                                                                                            +
                                                                                            +
                                                                                            + + + + + + + +
                                                                                            +
                                                                                            + +
                                                                                            +
                                                                                            +
                                                                                            + +
                                                                                            + +
                                                                                            +
                                                                                            + + +
                                                                                            + +
                                                                                            + +
                                                                                            +
                                                                                            +
                                                                                            Supernova Studies
                                                                                            +
                                                                                            +
                                                                                            +

                                                                                            Table of Contents

                                                                                            + +
                                                                                            +

                                                                                            This module provides a comprehensive analysis and simulations focusing on the detection of CCSN neutrinos with segmented sensors.

                                                                                            +

                                                                                            This simulation is designed to emulate the detection of Core Collapse Supernova (CCSN or simply SN in the following) neutrinos using segmented sensors. It directly generates particles resulting from Inverse Beta Decay (IBD) and Electron Neutrino-Electron Elastic Scattering (ENES).

                                                                                            +
                                                                                              +
                                                                                            • IBD: ν̄_e + p → n + e⁺
                                                                                              • +
                                                                                            • ENES: ν_e + e⁻ → ν_e + e⁻
                                                                                              • +
                                                                                            +

                                                                                            In the IBD case, the outgoing neutron is not simulated; hence, the neutron capture process that might be detected is not included in the simulation. Each event is assigned a weight based on the interaction probability, detailed later on this page. By default, the surrounding ice is represented as a cylinder facing the CCSN, simplifying the weight calculations.

                                                                                            +

                                                                                            Although CCSN models incorporate neutrino oscillations, the default simulation does not include any oscillation scenario in the weight calculations.

                                                                                            +
                                                                                            Diagram of CCSN neutrino simulation steps

                                                                                            + Figure 1: Diagram of the steps involved to generate the events for the simulation of CCSN neutrinos. The scheme is valid for both IBD and ENES, except for the threshold check. Here, e stands for both electron from ENES or positron from IBD, and ν for both electronic neutrino from ENES or electronic antineutrino from IBD. Image from this thesis.

                                                                                            The detailed procedure for this simulation is comprehensively described in this thesis, specifically in section 6.4. Below is a summary extracted from this source, outlining the steps taken to generate the events:

                                                                                            +
                                                                                              +
                                                                                            1. Utilizing the models, the expected flux per area is calculated from the luminosity L(t) and the mean energy <E(t)> according to Φ(t) = (1 / (4πd²)) · (L(t) / <E(t)>).
                                                                                              2. +
                                                                                            2. The distribution of Φ(t) is used to sample a time t of the burst via the inverse CDF (Cumulative Distribution Function) method. All other sampling from distributions within this simulation also employs the inverse CDF method.
                                                                                              3. +
                                                                                            3. For the sampled time t, the corresponding mean energy and mean squared energy are extracted from the models. These parameters contribute to the construction of the energy spectrum f(E,t), as elucidated in this paper.
                                                                                              4. +
                                                                                            4. The energy of the neutrino/antineutrino E_ν is sampled from f(E,t). If the energy falls below the IBD threshold, the algorithm reverts to the second step.
                                                                                              5. +
                                                                                            5. From E_ν, the angular cross section is devised. This informs the sampling of the angle θ between the incoming neutrino and the resulting e⁻/e⁺. The φ direction is randomly generated within the range of 0 to 2π.
                                                                                              6. +
                                                                                            6. The energy of e⁻/e⁺ is deduced from θ and E_ν. The interaction probability for such an event is ascertained using the total cross section, facilitating the computation of the interaction weight, as further described below.
                                                                                              7. +
                                                                                            7. The e⁻/e⁺ is manifested at a random position within the ice volume.
                                                                                              8. +
                                                                                            +

                                                                                            +Input Parameters

                                                                                            +

                                                                                            Execute ./OMSim_supernova --help to display all possible input parameters.

                                                                                            +

                                                                                            A typical command to run the simulation is:

                                                                                            +
                                                                                            ./OMSim_supernova -n 100 --wheight 20 --wradius 20 --depth_pos 75 --SNgun 0 --SNtype 0
                                                                                            +

                                                                                            +General Parameters

                                                                                            +
                                                                                              +
                                                                                            • --depth_pos: Index of the vector determining the depth of the simulated modules. Notable values include the dust layer (65), mean ice properties (approx) 75, and the cleanes ice (88). This selection affects the effective scattering and absorption lengths of the ice at the specified depth.
                                                                                              • +
                                                                                            • -o: Output file name. By default, two output files are created: one containing the simulated event information, and another with detection data.
                                                                                              • +
                                                                                            +

                                                                                            +SN Framework Parameters

                                                                                            +
                                                                                              +
                                                                                            • --wheight: Height of the ice's simulated world cylinder.
                                                                                              • +
                                                                                            • --wradius: Radius of the ice's simulated world cylinder.
                                                                                              • +
                                                                                            • --SNgun: Chooses the interaction type (0 for IBD, 1 for ENES).
                                                                                              • +
                                                                                            • --SNtype: Selects the CCSN model. Two models are currently available, provided by the Garching group. These models represent the expected fluxes from two CCSNs resulting in neutron stars, with different progenitor masses (27 and 9.6 solar masses). Simulations yielding this data can be found at https://arxiv.org/abs/1510.04643
                                                                                              • +
                                                                                            +

                                                                                            +Fixed Energy Studies

                                                                                            +

                                                                                            The user can also manually set the mean energy of generated events by providing specific input parameters. For instance:

                                                                                            +
                                                                                            --SNfixEnergy --SNmeanE 10.0 --SNalpha 3.0
                                                                                            +
                                                                                              +
                                                                                            • --SNfixEnergy: Acts as a flag parameter. When invoked, the simulation disregards the actual mean energy of neutrinos corresponding to the burst time. Instead, it adopts the mean energy and the pinching parameter specified by the subsequent two parameters.
                                                                                              • +
                                                                                            • --SNmeanE: Specifies the mean energy of the neutrinos.
                                                                                              • +
                                                                                            • --SNalpha: Defines the pinching parameter of the energy distribution (see this paper).
                                                                                              • +
                                                                                            +

                                                                                            Consequently, the neutrinos' energy is sampled from the distribution, derived from these two parameters and the previously mentioned model.

                                                                                            +

                                                                                            +Output Files

                                                                                            +

                                                                                            Two files are produced:

                                                                                            +

                                                                                            +*_info.dat

                                                                                            +

                                                                                            This file encapsulates data concerning each generated neutrino event. Each entry contains:

                                                                                            +
                                                                                              +
                                                                                            • Time of the neutrino burst.
                                                                                              • +
                                                                                            • Corresponding mean energy derived from the model.
                                                                                              • +
                                                                                            • Sampled neutrino energy E_ν.
                                                                                              • +
                                                                                            • cos(θ), where θ is the angle between the incoming neutrino and the outgoing particle (e- or e+).
                                                                                              • +
                                                                                            • Energy of the outgoing particle (e- or e+).
                                                                                              • +
                                                                                            • Interaction weight, calculated using the formula:
                                                                                              • +
                                                                                            +
                                                                                            W_int(E_ν) = σ(E) · n_target · l,
                                                                                            +

                                                                                            where:

                                                                                              +
                                                                                            • σ(E) is the total cross section for the interaction,
                                                                                              • +
                                                                                            • n_target is the number of targets available for the interaction in the ice,
                                                                                              • +
                                                                                            • l is the length of the simulated cylindrical world.
                                                                                              • +
                                                                                            +

                                                                                            +*_data.dat

                                                                                            +

                                                                                            This file contains the detection information. Its structure is designed to facilitate various trigger studies, allowing the examination of different time windows. Users might evaluate its structure for convenience, particularly if the trigger check is integrated within the simulation (requiring a predefined time window).

                                                                                            +

                                                                                            The default content structure is as follows:

                                                                                            +
                                                                                            Total hits | Modules hit | PMTs hit | "...for each PMT hit..." | Module number | PMT number | Hits in that PMT | "...for each Hit..." | hit time |
                                                                                            +

                                                                                            Note that the number of columns varies per line, contingent on the number of photons detected for the simulated neutrinos.

                                                                                            +

                                                                                            +Weights

                                                                                            +

                                                                                            The output files contain the interaction weight. However, users should also consider a weight factor depending on the total flux and the number of simulated events. In the most general case of simulating a single depth and then extrapolating the results to the entire detector, another weight factor is needed. This factor accounts for the ice properties of the simulated depth with respect to the whole detector. This last factor decreases in importance when using high multiplicity conditions, since these events generally interact closer to the module, making the photons less sensitive to changes in the optical properties.

                                                                                            +

                                                                                            These weight factors can be added similarly as explained in this thesis, section 6.4.2.

                                                                                            +

                                                                                            The total weight is composed of 3 components: the interaction probability, the SN flux through the simulated volume, and the different optical properties of the modules at different depths:

                                                                                            +
                                                                                            W = W_int(E) · W_flux(d) · W_eff.
                                                                                            +

                                                                                            Each component is explained as follows:

                                                                                            +

                                                                                            +Interaction Probability Weight:

                                                                                            +
                                                                                            W_int(E_ν) = σ(E) · n_target · l,
                                                                                            +

                                                                                            where σ(E_ν) is the total cross section for the interaction, n_target is the number of targets per unit of volume for such interaction, and l=40 m is the length of the generation volume along the neutrino direction axis. This is the length of the cylinder facing the CCSN.

                                                                                            +

                                                                                            +Flux Weight:

                                                                                            +
                                                                                            W_flux(d) = (1 / N_gen) · (r² / d²) · ∫ (L(t) / <E(t)>) dt,
                                                                                            +

                                                                                            where r is the cylindrical generation volume's radius, d is the distance from Earth where the CCSN is assumed to occur, and N_gen is the number of generated events.

                                                                                            +

                                                                                            +Effective Weight:

                                                                                            +
                                                                                            W_eff = N_modules · (<V_eff(m)> / V_eff(m,z_sim)),
                                                                                            +

                                                                                            where N_modules is the total modules in the simulated detector, V_eff(m, z_sim) is the effective volume at the simulation depth, and <V_eff(m)> is the mean effective volume for all modules in simulated detector. The term m represents multiplicity, defined as the count of different PMTs within a single module that detected the event within a specific time window.

                                                                                            +

                                                                                            The effective volume can be calculated in different ways. Old simulations of the mDOM, described in this thesis, section 6.3, were used in past studies. A linear regression of the effective volume concerning the absorption length, derived from various depths, provides each depth's effective volume. Although it is advisable to redo these simulations with a current mDOM model, users can temporarily use the old data with a regression line of V_eff = b · x + c, where x = 1/a is the inverse of the absorption length. The coefficients b and c, depending on the event's multiplicity, were obtained as follows:

                                                                                            + + + + + + + + + + + + + + + +
                                                                                            Multiplicity b (slope, m²) c (m³)
                                                                                            1 15.1843 0.000
                                                                                            2 0.1352 47.005
                                                                                            3 0.0306 16.170
                                                                                            4 0.0095 8.680
                                                                                            5 0.0039 5.105
                                                                                            >= 6 0.0026 2.909
                                                                                            +

                                                                                            Note that, for more than 5 PMTs, the same fit line is employed due to insufficient statistics at higher PMTs in the effective volume simulation. Additionally, since the absorption length depends on the wavelength, the fits above were obtained assuming a wavelength of λ = 400 nm.

                                                                                            +
                                                                                            +
                                                                                            +
                                                                                            + + + + diff --git a/modules.html b/modules.html index bb95aa52b4..aab8f5c8a4 100644 --- a/modules.html +++ b/modules.html @@ -119,12 +119,10 @@
                                                                                            Here is a list of all modules:
                                                                                            - + -
                                                                                             OMSim framework and geometryThese files define the geometry and materials common to all studies
                                                                                             Common frameworkThese files define the geometry and materials common to all studies
                                                                                             Effective areaAll specific to the effective area studies of the optical modules
                                                                                             Radioactive decaysSimulations for understanding the background produced by radioactive decays in borosilicate glass of optical modules & PMTs
                                                                                             Supernova StudiesComprehensive analysis and simulations focusing on the detection of CCSN neutrinos with segmented sensors
                                                                                             Bubble column
                                                                                            -
                                                                                            @@ -132,7 +130,7 @@ diff --git a/modules.js b/modules.js index 914468b5be..6ea838ec70 100644 --- a/modules.js +++ b/modules.js @@ -1,8 +1,7 @@ var modules = [ - [ "OMSim framework and geometry", "group__common.html", "group__common" ], + [ "Common framework", "group__common.html", "group__common" ], [ "Effective area", "group___effective_area.html", "group___effective_area" ], [ "Radioactive decays", "group__radioactive.html", "group__radioactive" ], - [ "Supernova Studies", "group__sngroup.html", "group__sngroup" ], - [ "Bubble column", "group__bubble.html", null ] + [ "Supernova Studies", "group__sngroup.html", "group__sngroup" ] ]; \ No newline at end of file diff --git a/navtreedata.js b/navtreedata.js index 3062f96bb9..1c9ba098b1 100644 --- a/navtreedata.js +++ b/navtreedata.js @@ -25,19 +25,45 @@ var NAVTREE = [ [ "OMSim", "index.html", [ - [ "Installation", "index.html#autotoc_md8", null ], - [ "Available studies", "index.html#autotoc_md12", null ], - [ "Multi-threading in Geant4", "md_multithreading.html", [ - [ "Introduction", "md_multithreading.html#autotoc_md1", null ], - [ "Thread Safety Guidelines", "md_multithreading.html#autotoc_md2", null ], - [ "Thread-Safe Singleton Implementation", "md_multithreading.html#autotoc_md3", [ - [ "Installing Geant4", "index.html#autotoc_md9", null ], - [ "Requirements", "index.html#autotoc_md10", null ], - [ "Compiling OMSim", "index.html#autotoc_md11", null ], - [ "Example: OMSimHitManager", "md_multithreading.html#autotoc_md4", null ], - [ "Example: Saving Data Per Thread", "md_multithreading.html#autotoc_md5", null ] + [ "OMSim Geant4 Framework", "index.html", [ + [ "Installation", "index.html#autotoc_md29", null ], + [ "Available studies", "index.html#autotoc_md33", null ] + ] ], + [ "Framework functionality", "md_0_common.html", [ + [ "Materials and User Data", "md_0_common.html#autotoc_md1", null ], + [ "Geometry construction", "md_0_common.html#autotoc_md2", null ], + [ "PMT Response and Saving Hits", "md_0_common.html#autotoc_md3", null ], + [ "Making other volumes sensitive to photons", "md_0_common.html#autotoc_md4", null ] + ] ], + [ "Multi-threading mode", "md_1_multithreading.html", [ + [ "Introduction", "md_1_multithreading.html#autotoc_md6", null ], + [ "Thread Safety Guidelines", "md_1_multithreading.html#autotoc_md7", null ], + [ "Thread-Safe Singleton Implementation", "md_1_multithreading.html#autotoc_md8", [ + [ "Example: OMSimHitManager", "md_1_multithreading.html#autotoc_md9", null ], + [ "Example: Saving Data Per Thread", "md_1_multithreading.html#autotoc_md10", null ] ] ], - [ "Best Practices for Creating New Thread-Safe Containers", "md_multithreading.html#autotoc_md6", null ] + [ "Best Practices for Creating New Thread-Safe Containers", "md_1_multithreading.html#autotoc_md11", null ] + ] ], + [ "Effective Area Study", "md_2_effective_area.html", [ + [ "Introduction to effective areas", "md_2_effective_area.html#autotoc_md13", null ], + [ "Example using healpy", "md_2_effective_area.html#autotoc_md14", null ] + ] ], + [ "Radioactive Decays Study", "md_3_radioactive_decays.html", null ], + [ "Supernova Studies", "md_4__s_n.html", [ + [ "Input Parameters", "md_4__s_n.html#autotoc_md17", [ + [ "General Parameters", "md_4__s_n.html#autotoc_md18", null ], + [ "SN Framework Parameters", "md_4__s_n.html#autotoc_md19", null ], + [ "Fixed Energy Studies", "md_4__s_n.html#autotoc_md20", null ] + ] ], + [ "Output Files", "md_4__s_n.html#autotoc_md21", [ + [ "*_info.dat", "md_4__s_n.html#autotoc_md22", null ], + [ "*_data.dat", "md_4__s_n.html#autotoc_md23", null ] + ] ], + [ "Weights", "md_4__s_n.html#autotoc_md24", [ + [ "Interaction Probability Weight:", "md_4__s_n.html#autotoc_md25", null ], + [ "Flux Weight:", "md_4__s_n.html#autotoc_md26", null ], + [ "Effective Weight:", "md_4__s_n.html#autotoc_md27", null ] + ] ] ] ], [ "Todo List", "todo.html", null ], 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                                                                                            Here is a list of all related documentation pages:
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                                                                                             Multi-threading in Geant4
                                                                                             Todo List
                                                                                             Framework functionality
                                                                                             Multi-threading mode
                                                                                             Effective Area Study
                                                                                             Radioactive Decays Study
                                                                                             Supernova Studies
                                                                                             Todo List
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                                                                                            HitStats Struct Reference
                                                                                            Common framework
                                                                                            @@ -180,7 +180,7 @@ diff --git a/struct_o_m_sim_detector_construction_1_1_s_d_info-members.html b/struct_o_m_sim_detector_construction_1_1_s_d_info-members.html index 965e55e0c5..67d48a142d 100644 --- a/struct_o_m_sim_detector_construction_1_1_s_d_info-members.html +++ b/struct_o_m_sim_detector_construction_1_1_s_d_info-members.html @@ -127,7 +127,7 @@ diff --git a/struct_o_m_sim_detector_construction_1_1_s_d_info.html b/struct_o_m_sim_detector_construction_1_1_s_d_info.html index cebd05a365..d8f7af1a3a 100644 --- a/struct_o_m_sim_detector_construction_1_1_s_d_info.html +++ b/struct_o_m_sim_detector_construction_1_1_s_d_info.html @@ -139,7 +139,7 @@ diff --git a/struct_o_m_sim_hit_manager_1_1_thread_local_data-members.html b/struct_o_m_sim_hit_manager_1_1_thread_local_data-members.html index 8256c4c45a..2642fa9545 100644 --- a/struct_o_m_sim_hit_manager_1_1_thread_local_data-members.html +++ b/struct_o_m_sim_hit_manager_1_1_thread_local_data-members.html @@ -126,7 +126,7 @@ diff --git a/struct_o_m_sim_hit_manager_1_1_thread_local_data.html b/struct_o_m_sim_hit_manager_1_1_thread_local_data.html index eda317eea9..499624a83f 100644 --- a/struct_o_m_sim_hit_manager_1_1_thread_local_data.html +++ b/struct_o_m_sim_hit_manager_1_1_thread_local_data.html @@ -136,7 +136,7 @@ diff --git a/struct_o_m_sim_p_m_t_response_1_1_p_m_t_pulse-members.html b/struct_o_m_sim_p_m_t_response_1_1_p_m_t_pulse-members.html index 9caffd5019..39800abfff 100644 --- a/struct_o_m_sim_p_m_t_response_1_1_p_m_t_pulse-members.html +++ b/struct_o_m_sim_p_m_t_response_1_1_p_m_t_pulse-members.html @@ -128,7 +128,7 @@ diff --git a/struct_o_m_sim_p_m_t_response_1_1_p_m_t_pulse.html b/struct_o_m_sim_p_m_t_response_1_1_p_m_t_pulse.html index f0c06d27ec..703ae837dd 100644 --- a/struct_o_m_sim_p_m_t_response_1_1_p_m_t_pulse.html +++ b/struct_o_m_sim_p_m_t_response_1_1_p_m_t_pulse.html @@ -148,7 +148,7 @@ diff --git a/struct_photon_info-members.html b/struct_photon_info-members.html index 546d94c359..2480028ccc 100644 --- a/struct_photon_info-members.html +++ b/struct_photon_info-members.html @@ -137,7 +137,7 @@ diff --git a/struct_photon_info.html b/struct_photon_info.html index a5253149ef..9bb0a132c4 100644 --- a/struct_photon_info.html +++ b/struct_photon_info.html @@ -190,7 +190,7 @@ diff --git a/structabc_detector_component_1_1_component-members.html b/structabc_detector_component_1_1_component-members.html index 616ce85902..1790c69f53 100644 --- a/structabc_detector_component_1_1_component-members.html +++ b/structabc_detector_component_1_1_component-members.html @@ -130,7 +130,7 @@ diff --git a/structabc_detector_component_1_1_component.html b/structabc_detector_component_1_1_component.html index dd15e4f856..a1e4768c68 100644 --- a/structabc_detector_component_1_1_component.html +++ b/structabc_detector_component_1_1_component.html @@ -158,7 +158,7 @@ diff --git a/structeffective_area_result-members.html b/structeffective_area_result-members.html index fa82542b3b..699d1f91fb 100644 --- a/structeffective_area_result-members.html +++ b/structeffective_area_result-members.html @@ -127,7 +127,7 @@ diff --git a/structeffective_area_result.html b/structeffective_area_result.html index 8871a09b03..a1c14534c8 100644 --- a/structeffective_area_result.html +++ b/structeffective_area_result.html @@ -144,7 +144,7 @@ diff --git a/supernova_2include_2_o_m_sim_event_action_8hh_source.html b/supernova_2include_2_o_m_sim_event_action_8hh_source.html index a4855e88ae..3f1b0a1bc0 100644 --- a/supernova_2include_2_o_m_sim_event_action_8hh_source.html +++ b/supernova_2include_2_o_m_sim_event_action_8hh_source.html @@ -172,7 +172,7 @@ diff --git a/supernova_2include_2_o_m_sim_physics_list_8hh_source.html b/supernova_2include_2_o_m_sim_physics_list_8hh_source.html index 6ecdedf069..537fc3219e 100644 --- a/supernova_2include_2_o_m_sim_physics_list_8hh_source.html +++ b/supernova_2include_2_o_m_sim_physics_list_8hh_source.html @@ -150,7 +150,7 @@ diff --git a/supernova_2include_2_o_m_sim_primary_generator_action_8hh_source.html b/supernova_2include_2_o_m_sim_primary_generator_action_8hh_source.html index 18c633f0b6..9992fe0b63 100644 --- a/supernova_2include_2_o_m_sim_primary_generator_action_8hh_source.html +++ b/supernova_2include_2_o_m_sim_primary_generator_action_8hh_source.html @@ -180,7 +180,7 @@ diff --git a/todo.html b/todo.html index f63b100a8b..c6f0a31e8f 100644 --- a/todo.html +++ b/todo.html @@ -161,7 +161,7 @@