Merge changes from dev to master (#1092)

Co-authored-by: GitHub Nightly Merge Action <[email protected]> Co-authored-by: Mudit Pandey <[email protected]> Co-authored-by: Christina Lee <[email protected]> Co-authored-by: Romain Moyard <[email protected]> Co-authored-by: Matthew Silverman <[email protected]> Co-authored-by: lillian542 <[email protected]> Co-authored-by: Tom Bromley <[email protected]> Co-authored-by: Josh Izaac <[email protected]> Co-authored-by: Rashid N H M <[email protected]> Co-authored-by: Guillermo Alonso-Linaje <[email protected]> Co-authored-by: soranjh <[email protected]> Co-authored-by: CatalinaAlbornoz <[email protected]> Co-authored-by: Jay Soni <[email protected]> Co-authored-by: soranjh <[email protected]> Co-authored-by: ixfoduap <[email protected]> Co-authored-by: Diego <[email protected]> Co-authored-by: Utkarsh <[email protected]> Co-authored-by: Stepan Fomichev <[email protected]> Co-authored-by: soranjh <[email protected]> Co-authored-by: Alvaro Ballon <[email protected]> Co-authored-by: Diego <[email protected]> Co-authored-by: Lee J. O'Riordan <[email protected]> Co-authored-by: Korbinian Kottmann <[email protected]> Co-authored-by: DanielNino27 <[email protected]> Co-authored-by: Paul Finlay <[email protected]> Co-authored-by: ashishks0522 <[email protected]> Co-authored-by: Mikhail Andrenkov <[email protected]> Co-authored-by: David Wierichs <[email protected]> Co-authored-by: Diksha Dhawan <[email protected]>
PennyLaneAI · May 7, 2024 · 1555d29 · 1555d29
1 parent 6ebb9fa
commit 1555d29
Show file tree

Hide file tree

Showing 59 changed files with 1,716 additions and 199 deletions.
diff --git a/.github/workflows/update-metadata-reminder.yml b/.github/workflows/update-metadata-reminder.yml
@@ -18,7 +18,7 @@ jobs:
             repo: context.repo.repo,
             body: `👋 Hey, looks like you've updated some demos!
 
-            🐘 Don't forget to update the \`dateOfLastModification\` in the associated metadata files so your changes show up on [pennylane.ai](https://pennylane.ai).
+            🐘 Don't forget to update the \`dateOfLastModification\` in the associated metadata files so your changes are reflected in Glass Onion (search and recommendations).
 
             Please hide this comment once the field(s) are updated. Thanks!`
           })
diff --git a/Makefile b/Makefile
@@ -77,5 +77,6 @@ environment:
 			$$PYTHON_VENV_PATH/bin/python -m pip install --upgrade git+https://github.com/PennyLaneAI/pennylane-cirq.git#egg=pennylane-cirq;\
 			$$PYTHON_VENV_PATH/bin/python -m pip install --upgrade git+https://github.com/PennyLaneAI/pennylane-qiskit.git#egg=pennylane-qiskit;\
 			$$PYTHON_VENV_PATH/bin/python -m pip install --upgrade git+https://github.com/PennyLaneAI/pennylane-qulacs.git#egg=pennylane-qulacs;\
+			$$PYTHON_VENV_PATH/bin/python -m pip install -i https://test.pypi.org/simple/ PennyLane-Lightning --pre --upgrade;\
 		fi;\
 	fi
diff --git a/_static/authors/diksha_dhawan.png b/_static/authors/diksha_dhawan.png
diff --git a/_static/authors/diksha_dhawan.txt b/_static/authors/diksha_dhawan.txt
@@ -0,0 +1,4 @@
+.. bio:: Diksha Dhawan
+   :photo: ../_static/authors/diksha_dhawan.png
+
+   Diksha is a quantum software developer at Xanadu. Her work is focused on implementing quantum computing algorithms for quantum chemistry.
diff --git a/_static/demonstration_assets/barren_gadgets/barren_gadgets.py b/_static/demonstration_assets/barren_gadgets/barren_gadgets.py
@@ -1,6 +1,8 @@
 import pennylane as qml
 from pennylane import numpy as np
 
+def non_identity_obs(obs):
+    return [o for o in obs if not isinstance(o, qml.Identity)]
 
 class PerturbativeGadgets:
     """ Class to generate the gadget Hamiltonian corresponding to a given
@@ -28,12 +30,13 @@ def gadgetize(self, Hamiltonian, target_locality=3):
         # checking for unaccounted for situations
         self.run_checks(Hamiltonian, target_locality)
         computational_qubits, computational_locality, computational_terms = self.get_params(Hamiltonian)
+        Hamiltonian_coeffs, Hamiltonian_ops = Hamiltonian.terms()
 
         # total qubit count, updated progressively when adding ancillaries
         total_qubits = computational_qubits
         #TODO: check proper convergence guarantee
         gap = 1
-        perturbation_norm = np.sum(np.abs(Hamiltonian.coeffs)) \
+        perturbation_norm = np.sum(np.abs(Hamiltonian_coeffs)) \
                           + computational_terms * (computational_locality - 1)
         lambda_max = gap / (4 * perturbation_norm)
         l = self.perturbation_factor * lambda_max
@@ -44,7 +47,7 @@ def gadgetize(self, Hamiltonian, target_locality=3):
         obs_anc = []
         obs_pert = []
         ancillary_register_size = int(computational_locality / (target_locality - 2))
-        for str_count, string in enumerate(Hamiltonian.ops):
+        for str_count, string in enumerate(Hamiltonian_ops):
             previous_total = total_qubits
             total_qubits += ancillary_register_size
             # Generating the ancillary part
@@ -54,10 +57,10 @@ def gadgetize(self, Hamiltonian, target_locality=3):
             # Generating the perturbative part
             for anc_q in range(ancillary_register_size):
                 term = qml.PauliX(previous_total+anc_q) @ qml.PauliX(previous_total+(anc_q+1)%ancillary_register_size)
-                term = qml.operation.Tensor(term, *string.non_identity_obs[
+                term = qml.prod(term, *non_identity_obs(string.operands)[
                     (target_locality-2)*anc_q:(target_locality-2)*(anc_q+1)])
                 obs_pert.append(term)
-            coeffs_pert += [l * sign_correction * Hamiltonian.coeffs[str_count]] \
+            coeffs_pert += [l * sign_correction * Hamiltonian_coeffs[str_count]] \
                         + [l] * (ancillary_register_size - 1)
         coeffs = coeffs_anc + coeffs_pert
         obs = obs_anc + obs_pert
@@ -77,12 +80,13 @@ def get_params(self, Hamiltonian):
             computational_terms (int)     : number of terms in the sum 
                                             composing the Hamiltonian
         """
+        _, Hamiltonian_ops = Hamiltonian.terms()
         # checking how many qubits the Hamiltonian acts on
         computational_qubits = len(Hamiltonian.wires)
         # getting the number of terms in the Hamiltonian
-        computational_terms = len(Hamiltonian.ops)
+        computational_terms = len(Hamiltonian_ops)
         # getting the locality, assuming all terms have the same
-        computational_locality = max([len(Hamiltonian.ops[s].non_identity_obs) 
+        computational_locality = max([len(non_identity_obs(Hamiltonian_ops[s])) 
                                       for s in range(computational_terms)])
         return computational_qubits, computational_locality, computational_terms
 
@@ -96,6 +100,7 @@ def run_checks(self, Hamiltonian, target_locality):
         Returns:
             None
         """
+        _, Hamiltonian_ops = Hamiltonian.terms()
         computational_qubits, computational_locality, _ = self.get_params(Hamiltonian)
         computational_qubits = len(Hamiltonian.wires)
         if computational_qubits != Hamiltonian.wires[-1] + 1:
@@ -104,8 +109,8 @@ def run_checks(self, Hamiltonian, target_locality):
                             'Decomposition not implemented for this case')
         # Check for same string lengths
         localities=[]
-        for string in Hamiltonian.ops:
-            localities.append(len(string.non_identity_obs))
+        for string in Hamiltonian_ops:
+            localities.append(len(non_identity_obs(string)))
         if len(np.unique(localities)) > 1:
             raise Exception('The given Hamiltonian has terms with different locality.' +
                             ' Gadgetization not implemented for this case')

diff --git a/...tic/demonstration_assets/error_prop/OGthumbnail_large_error-prop_2024-05-01.png b/...tic/demonstration_assets/error_prop/OGthumbnail_large_error-prop_2024-05-01.png
diff --git a/_static/demonstration_assets/error_prop/thumbnail_error-prop_2024-05-01.png b/_static/demonstration_assets/error_prop/thumbnail_error-prop_2024-05-01.png
diff --git a/...ate_dynamic_mcm_circuits/socialthumbnail_how_to_create_dynamic_mcm_circuits.png b/...ate_dynamic_mcm_circuits/socialthumbnail_how_to_create_dynamic_mcm_circuits.png
diff --git a/...amplitude_amplification/OGthumbnail_large_AmplitudeAmplification_2024-04-29.png b/...amplitude_amplification/OGthumbnail_large_AmplitudeAmplification_2024-04-29.png
diff --git a/_static/demonstration_assets/intro_amplitude_amplification/ampamp1.jpeg b/_static/demonstration_assets/intro_amplitude_amplification/ampamp1.jpeg
diff --git a/_static/demonstration_assets/intro_amplitude_amplification/ampamp2.jpeg b/_static/demonstration_assets/intro_amplitude_amplification/ampamp2.jpeg
diff --git a/_static/demonstration_assets/intro_amplitude_amplification/ampamp3.jpeg b/_static/demonstration_assets/intro_amplitude_amplification/ampamp3.jpeg
diff --git a/_static/demonstration_assets/intro_amplitude_amplification/overcook.gif b/_static/demonstration_assets/intro_amplitude_amplification/overcook.gif
diff --git a/_static/demonstration_assets/intro_amplitude_amplification/sum_zero.jpeg b/_static/demonstration_assets/intro_amplitude_amplification/sum_zero.jpeg
diff --git a/...s/intro_amplitude_amplification/thumbnail_AmplitudeAmplification_2024-04-29.png b/...s/intro_amplitude_amplification/thumbnail_AmplitudeAmplification_2024-04-29.png
diff --git a/_static/demonstration_assets/mapping/OGthumbnail_large_mapping_2024-05-01.png b/_static/demonstration_assets/mapping/OGthumbnail_large_mapping_2024-05-01.png
diff --git a/_static/demonstration_assets/mapping/thumbnail_mapping_2024-05-01.png b/_static/demonstration_assets/mapping/thumbnail_mapping_2024-05-01.png
diff --git a/...assets/regular_demo_thumbnails/thumbnail_how_to_create_dynamic_mcm_circuits.png b/...assets/regular_demo_thumbnails/thumbnail_how_to_create_dynamic_mcm_circuits.png
diff --git a/...tic/large_demo_thumbnails/thumbnail_large_AmplitudeAmplification_2024-04-29.png b/...tic/large_demo_thumbnails/thumbnail_large_AmplitudeAmplification_2024-04-29.png
diff --git a/_static/large_demo_thumbnails/thumbnail_large_error-prop_2024-05-01.png b/_static/large_demo_thumbnails/thumbnail_large_error-prop_2024-05-01.png
diff --git a/...ic/large_demo_thumbnails/thumbnail_large_how_to_create_dynamic_mcm_circuits.png b/...ic/large_demo_thumbnails/thumbnail_large_how_to_create_dynamic_mcm_circuits.png
diff --git a/_static/large_demo_thumbnails/thumbnail_large_mapping_2024-05-01.png b/_static/large_demo_thumbnails/thumbnail_large_mapping_2024-05-01.png
diff --git a/demonstrations/barren_gadgets/barren_gadgets.py b/demonstrations/barren_gadgets/barren_gadgets.py
@@ -1,6 +1,8 @@
 import pennylane as qml
 from pennylane import numpy as np
 
+def non_identity_obs(obs):
+    return [o for o in obs if not isinstance(o, qml.Identity)]
 
 class PerturbativeGadgets:
     """ Class to generate the gadget Hamiltonian corresponding to a given
@@ -28,12 +30,13 @@ def gadgetize(self, Hamiltonian, target_locality=3):
         # checking for unaccounted for situations
         self.run_checks(Hamiltonian, target_locality)
         computational_qubits, computational_locality, computational_terms = self.get_params(Hamiltonian)
+        Hamiltonian_coeffs, Hamiltonian_ops = Hamiltonian.terms()
 
         # total qubit count, updated progressively when adding ancillaries
         total_qubits = computational_qubits
         #TODO: check proper convergence guarantee
         gap = 1
-        perturbation_norm = np.sum(np.abs(Hamiltonian.coeffs)) \
+        perturbation_norm = np.sum(np.abs(Hamiltonian_coeffs)) \
                           + computational_terms * (computational_locality - 1)
         lambda_max = gap / (4 * perturbation_norm)
         l = self.perturbation_factor * lambda_max
@@ -44,7 +47,7 @@ def gadgetize(self, Hamiltonian, target_locality=3):
         obs_anc = []
         obs_pert = []
         ancillary_register_size = int(computational_locality / (target_locality - 2))
-        for str_count, string in enumerate(Hamiltonian.ops):
+        for str_count, string in enumerate(Hamiltonian_ops):
             previous_total = total_qubits
             total_qubits += ancillary_register_size
             # Generating the ancillary part
@@ -54,10 +57,10 @@ def gadgetize(self, Hamiltonian, target_locality=3):
             # Generating the perturbative part
             for anc_q in range(ancillary_register_size):
                 term = qml.PauliX(previous_total+anc_q) @ qml.PauliX(previous_total+(anc_q+1)%ancillary_register_size)
-                term = qml.operation.Tensor(term, *string.non_identity_obs[
+                term = qml.prod(term, *non_identity_obs(string.operands)[
                     (target_locality-2)*anc_q:(target_locality-2)*(anc_q+1)])
                 obs_pert.append(term)
-            coeffs_pert += [l * sign_correction * Hamiltonian.coeffs[str_count]] \
+            coeffs_pert += [l * sign_correction * Hamiltonian_coeffs[str_count]] \
                         + [l] * (ancillary_register_size - 1)
         coeffs = coeffs_anc + coeffs_pert
         obs = obs_anc + obs_pert
@@ -77,12 +80,13 @@ def get_params(self, Hamiltonian):
             computational_terms (int)     : number of terms in the sum 
                                             composing the Hamiltonian
         """
+        _, Hamiltonian_ops = Hamiltonian.terms()
         # checking how many qubits the Hamiltonian acts on
         computational_qubits = len(Hamiltonian.wires)
         # getting the number of terms in the Hamiltonian
-        computational_terms = len(Hamiltonian.ops)
+        computational_terms = len(Hamiltonian_ops)
         # getting the locality, assuming all terms have the same
-        computational_locality = max([len(Hamiltonian.ops[s].non_identity_obs) 
+        computational_locality = max([len(non_identity_obs(Hamiltonian_ops[s])) 
                                       for s in range(computational_terms)])
         return computational_qubits, computational_locality, computational_terms
 
@@ -96,6 +100,7 @@ def run_checks(self, Hamiltonian, target_locality):
         Returns:
             None
         """
+        _, Hamiltonian_ops = Hamiltonian.terms()
         computational_qubits, computational_locality, _ = self.get_params(Hamiltonian)
         computational_qubits = len(Hamiltonian.wires)
         if computational_qubits != Hamiltonian.wires[-1] + 1:
@@ -104,8 +109,8 @@ def run_checks(self, Hamiltonian, target_locality):
                             'Decomposition not implemented for this case')
         # Check for same string lengths
         localities=[]
-        for string in Hamiltonian.ops:
-            localities.append(len(string.non_identity_obs))
+        for string in Hamiltonian_ops:
+            localities.append(len(non_identity_obs(string)))
         if len(np.unique(localities)) > 1:
             raise Exception('The given Hamiltonian has terms with different locality.' +
                             ' Gadgetization not implemented for this case')

diff --git a/demonstrations/braket-parallel-gradients.py b/demonstrations/braket-parallel-gradients.py
@@ -138,7 +138,7 @@ def circuit(params):
 
     # Measure all qubits to make sure all's good with Braket
     observables = [qml.PauliZ(n_wires - 1)] + [qml.Identity(i) for i in range(n_wires - 1)]
-    return qml.expval(qml.operation.Tensor(*observables))
+    return qml.expval(qml.prod(*observables))
 
 
 ##############################################################################

diff --git a/demonstrations/tutorial_barren_gadgets.py b/demonstrations/tutorial_barren_gadgets.py
@@ -202,7 +202,7 @@
 
 gadgetizer = PerturbativeGadgets()
 H_gadget = gadgetizer.gadgetize(H_target)
-print(H_gadget)
+H_gadget
 
 ##############################################################################
 # So, let's see what we got.

diff --git a/demonstrations/tutorial_block_encoding.metadata.json b/demonstrations/tutorial_block_encoding.metadata.json
@@ -12,7 +12,7 @@
         }
     ],
     "dateOfPublication": "2023-11-28T00:00:00+00:00",
-    "dateOfLastModification": "2024-01-01T00:00:00+00:00",
+    "dateOfLastModification": "2024-04-26T00:00:00+00:00",
     "categories": [
         "Quantum Computing",
         "Algorithms"

diff --git a/demonstrations/tutorial_block_encoding.py b/demonstrations/tutorial_block_encoding.py
@@ -79,7 +79,9 @@
 be obtained with the :func:`~.pennylane.templates.state_preparations.mottonen.compute_theta`
 function of PennyLane.
 
-Let's now construct the FABLE block encoding circuit for a structured matrix.
+The :class:`~.pennylane.FABLE` circuit is implemented in PennyLane and
+can be easily used to block encode matrices of any given shape. Here, we manually construct the
+circuit for a structured :math:`4 \times 4` matrix.
 """
 
 import pennylane as qml
@@ -116,7 +118,7 @@
 # Finally, we obtain the control wires for the C-NOT gates and a wire map that we later use to
 # translate the control wires into the wire registers we prepared.
 
-code = gray_code(2*np.sqrt(len(A)))
+code = gray_code(2 * np.log2(len(A)))
 n_selections = len(code)
 
 control_wires = [int(np.log2(int(code[i], 2) ^ int(code[(i + 1) %
@@ -173,7 +175,9 @@ def circuit():
 ##############################################################################
 # You can easily confirm that the circuit block encodes the original matrix defined above. Note that
 # the dimension of :math:`A` should be :math:`2^n` where :math:`n` is an integer. For matrices with
-# an arbitrary size, we can add zeros to reach the correct dimension.
+# an arbitrary size, we can add zeros to reach the correct dimension. The padding will be
+# automatically applied in :class:`~.pennylane.FABLE` implemented in
+# PennyLane.
 #
 # The interesting point about the FABLE method is that we can eliminate those rotation gates that
 # have an angle smaller than a defined threshold. This leaves a sequence of C-NOT gates that in

diff --git a/demonstrations/tutorial_classical_shadows.py b/demonstrations/tutorial_classical_shadows.py
@@ -512,8 +512,8 @@ def estimate_shadow_obervable(shadow, observable, k=10):
         ), np.array([observable.wires[0]])
     else:
         target_obs, target_locs = np.array(
-            [map_name_to_int[o.name] for o in observable.obs]
-        ), np.array([o.wires[0] for o in observable.obs])
+            [map_name_to_int[o.name] for o in observable.operands]
+        ), np.array([o.wires[0] for o in observable.operands])
 
     # classical values
     b_lists, obs_lists = shadow

diff --git a/demonstrations/tutorial_clifford_circuit_simulations.py b/demonstrations/tutorial_clifford_circuit_simulations.py
@@ -332,8 +332,9 @@ def clifford_tableau(op):
     for pauli in pauli_ops:
         conjugate = qml.prod(qml.adjoint(op), pauli, op).simplify()
         decompose = qml.pauli_decompose(conjugate.matrix(), wire_order=op.wires)
-        phase = "+" if list(decompose.coeffs)[0] >= 0 else "-"
-        print(pauli, "-—>", phase, list(decompose.ops)[0])
+        decompose_coeffs, decompose_ops = decompose.terms()
+        phase = "+" if list(decompose_coeffs)[0] >= 0 else "-"
+        print(pauli, "-—>", phase, list(decompose_ops)[0])
 
 clifford_tableau(qml.X(0))
 

diff --git a/demonstrations/tutorial_diffable_shadows.py b/demonstrations/tutorial_diffable_shadows.py
@@ -376,7 +376,7 @@ def qnode_shadow():
     method="pyscf",
 )
 
-coeffs, obs = H.coeffs, H.ops
+coeffs, obs = H.terms()
 H_qwc = qml.Hamiltonian(coeffs, obs, grouping_type="qwc")
 
 groups = qml.pauli.group_observables(obs)
@@ -421,6 +421,7 @@ def circuit():
 
         # execute qwc measurements
         dev_finite = qml.device("default.qubit", wires=range(n_wires), shots=int(shots))
+
         @qml.qnode(dev_finite, interface="autograd")
         def qnode_finite(H):
             circuit()