From a87a0aeb0c69d1a26e684eb730a12cca381ca317 Mon Sep 17 00:00:00 2001 From: Mikhail Andrenkov Date: Tue, 8 Oct 2024 13:51:42 -0400 Subject: [PATCH 1/2] Remove canonical URLs from demo metadata (#1232) **Title:** Remove the `canonicalURL` field from demo metadata. **Summary:** This PR removes the `canonicalURL` field from existing demo metadata. The `canonicalURL` field has been superseded by the (autogenerated) `slug` field as of #1228. **Relevant references:** None. **Possible Drawbacks:** None. **Related GitHub Issues:** None. --- **Detailed Changes:** 1. Fixed the `$id` reference in `demo.metadata.schema.0.1.3.json`. 2. Added `demo.metadata.schema.0.1.4.json` which removes the `canonicalURL` field. 3. Updated the example metadata in `demonstrations_metadata.md`. 4. Removed the `canonicalURL` field from existing demo metadata (and adjusted `dateOfLastModification`). 5. Deleted the obsolete `update_metadata.py` script. **Merge Checklist:** * [x] Delete the "Build Website - Text (Test)" GHA workflow which was added for testing purposes. **Verification:** The generated `metadata.json` file in the Glass Onion bucket no longer has any `canonicalURL` fields:
metadata.json Snippet

```json [ { "authors": [ { "username": "whatsis" } ], "basedOnPapers": [], "categories": [ "Quantum Computing", "How-to" ], "dateOfLastModification": "2024-10-07T00:00:00+00:00", "dateOfPublication": "2024-10-01T00:00:00+00:00", "doi": "", "previewImages": [ { "type": "thumbnail", "uri": "/_static/demo_thumbnails/regular_demo_thumbnails/thumbnail_how_to_use_noise_models.png" }, { "type": "large_thumbnail", "uri": "/_static/demo_thumbnails/large_demo_thumbnails/thumbnail_large_how_to_use_noise_models.png" } ], "referencedByPapers": [], "references": [], "relatedContent": [ { "id": "tutorial_noisy_circuits", "type": "demonstration", "weight": 1 } ], "seoDescription": "Learn how noise models can be built and inserted into a quantum circuit in PennyLane.", "slug": "tutorial_how_to_use_noise_models", "tags": [], "title": "How to use noise models in PennyLane" }, ... ] ```

--- .github/workflows/validate-demo-metadata.yml | 2 +- .../adjoint_diff_benchmarking.metadata.json | 3 +- demonstrations/ahs_aquila.metadata.json | 5 +- .../braket-parallel-gradients.metadata.json | 5 +- .../circuits_as_fourier_series.metadata.json | 3 +- .../covalent_cloud_gpu.metadata.json | 3 +- .../ensemble_multi_qpu.metadata.json | 3 +- .../function_fitting_qsp.metadata.json | 3 +- demonstrations/gbs.metadata.json | 5 +- ...ing_started_with_hybrid_jobs.metadata.json | 5 +- demonstrations/gqe_training.metadata.json | 7 +- ...o_use_qiskit1_with_pennylane.metadata.json | 3 +- demonstrations/ibm_pennylane.metadata.json | 3 +- demonstrations/learning2learn.metadata.json | 5 +- .../ml_classical_shadows.metadata.json | 3 +- demonstrations/oqc_pulse.metadata.json | 5 +- demonstrations/plugins_hybrid.metadata.json | 5 +- demonstrations/pytorch_noise.metadata.json | 3 +- demonstrations/qnspsa.metadata.json | 5 +- demonstrations/qonn.metadata.json | 3 +- demonstrations/qrack.metadata.json | 3 +- .../qsim_beyond_classical.metadata.json | 3 +- .../quantum_neural_net.metadata.json | 3 +- demonstrations/quantum_volume.metadata.json | 5 +- ...L_model_using_JAX_and_JAXopt.metadata.json | 5 +- ...ML_model_using_JAX_and_Optax.metadata.json | 5 +- ...using_JAX_catalyst_and_Optax.metadata.json | 3 +- ...ircuits_with_tensor_networks.metadata.json | 3 +- demonstrations/tutorial_QGAN.metadata.json | 3 +- demonstrations/tutorial_QUBO.metadata.json | 5 +- .../tutorial_adaptive_circuits.metadata.json | 3 +- .../tutorial_adjoint_diff.metadata.json | 3 +- ...rial_adversarial_attacks_QML.metadata.json | 5 +- .../tutorial_apply_qsvt.metadata.json | 3 +- .../tutorial_backprop.metadata.json | 3 +- .../tutorial_barren_gadgets.metadata.json | 3 +- .../tutorial_barren_plateaus.metadata.json | 3 +- .../tutorial_block_encoding.metadata.json | 3 +- .../tutorial_bluequbit.metadata.json | 5 +- .../tutorial_chemical_reactions.metadata.json | 3 +- ...tutorial_circuit_compilation.metadata.json | 5 +- ..._classical_expval_estimation.metadata.json | 5 +- .../tutorial_classical_kernels.metadata.json | 3 +- .../tutorial_classical_shadows.metadata.json | 3 +- ...rial_classically_boosted_vqe.metadata.json | 3 +- ...clifford_circuit_simulations.metadata.json | 7 +- .../tutorial_coherent_vqls.metadata.json | 3 +- .../tutorial_contextuality.metadata.json | 5 +- ..._data_reuploading_classifier.metadata.json | 5 +- ...tutorial_diffable-mitigation.metadata.json | 3 +- .../tutorial_diffable_shadows.metadata.json | 3 +- .../tutorial_differentiable_HF.metadata.json | 3 +- .../tutorial_doubly_stochastic.metadata.json | 3 +- .../tutorial_eqnn_force_field.metadata.json | 5 +- ..._equivariant_graph_embedding.metadata.json | 5 +- .../tutorial_error_mitigation.metadata.json | 5 +- .../tutorial_error_prop.metadata.json | 3 +- ..._expressivity_fourier_series.metadata.json | 5 +- demonstrations/tutorial_falqon.metadata.json | 3 +- ...tutorial_fermionic_operators.metadata.json | 5 +- ...rial_gaussian_transformation.metadata.json | 3 +- .../tutorial_general_parshift.metadata.json | 3 +- .../tutorial_geometric_qml.metadata.json | 5 +- .../tutorial_givens_rotations.metadata.json | 3 +- .../tutorial_grovers_algorithm.metadata.json | 9 +- ..._to_pennylane_knowing_qiskit.metadata.json | 3 +- .../tutorial_haar_measure.metadata.json | 3 +- .../tutorial_here_comes_the_sun.metadata.json | 5 +- ...ial_how_to_collect_mcm_stats.metadata.json | 3 +- ..._create_dynamic_mcm_circuits.metadata.json | 3 +- ...in_time_compile_vqe_catalyst.metadata.json | 3 +- ...rial_how_to_use_noise_models.metadata.json | 3 +- ...utorial_how_to_use_registers.metadata.json | 3 +- ...implicit_diff_susceptibility.metadata.json | 5 +- ...al_initial_state_preparation.metadata.json | 5 +- ...ntro_amplitude_amplification.metadata.json | 5 +- .../tutorial_intro_qrom.metadata.json | 5 +- .../tutorial_intro_qsvt.metadata.json | 5 +- .../tutorial_isingmodel_PyTorch.metadata.json | 3 +- ...tutorial_jax_transformations.metadata.json | 5 +- ...torial_kernel_based_training.metadata.json | 3 +- .../tutorial_kernels_module.metadata.json | 3 +- .../tutorial_lcu_blockencoding.metadata.json | 3 +- ...arning_dynamics_incoherently.metadata.json | 7 +- .../tutorial_learning_few_data.metadata.json | 3 +- ...al_learning_from_experiments.metadata.json | 3 +- .../tutorial_learningshallow.metadata.json | 4 +- .../tutorial_liealgebra.metadata.json | 4 +- demonstrations/tutorial_liesim.metadata.json | 3 +- .../tutorial_liesim_extension.metadata.json | 3 +- ...utorial_local_cost_functions.metadata.json | 3 +- ...ial_magic_state_distillation.metadata.json | 3 +- demonstrations/tutorial_mapping.metadata.json | 3 +- demonstrations/tutorial_mbqc.metadata.json | 3 +- .../tutorial_mcm_introduction.metadata.json | 3 +- ...utorial_measurement_optimize.metadata.json | 3 +- ...utorial_mitigation_advantage.metadata.json | 5 +- .../tutorial_mol_geo_opt.metadata.json | 3 +- demonstrations/tutorial_mps.metadata.json | 3 +- ...al_multiclass_classification.metadata.json | 3 +- .../tutorial_neutral_atoms.metadata.json | 5 +- ...l_noisy_circuit_optimization.metadata.json | 3 +- .../tutorial_noisy_circuits.metadata.json | 3 +- demonstrations/tutorial_odegen.metadata.json | 4 +- .../tutorial_optimal_control.metadata.json | 5 +- demonstrations/tutorial_pasqal.metadata.json | 3 +- .../tutorial_phase_kickback.metadata.json | 5 +- .../tutorial_photonics.metadata.json | 3 +- ...onal_quantum_neural_networks.metadata.json | 3 +- ...utorial_pulse_programming101.metadata.json | 5 +- .../tutorial_qaoa_intro.metadata.json | 3 +- .../tutorial_qaoa_maxcut.metadata.json | 3 +- demonstrations/tutorial_qcbm.metadata.json | 5 +- .../tutorial_qchem_external.metadata.json | 3 +- demonstrations/tutorial_qft.metadata.json | 5 +- .../tutorial_qft_arithmetics.metadata.json | 3 +- demonstrations/tutorial_qgrnn.metadata.json | 3 +- .../tutorial_qnn_module_tf.metadata.json | 3 +- .../tutorial_qnn_module_torch.metadata.json | 5 +- ..._qnn_multivariate_regression.metadata.json | 3 +- demonstrations/tutorial_qpe.metadata.json | 5 +- .../tutorial_qsvt_hardware.metadata.json | 5 +- ...ial_quantum_analytic_descent.metadata.json | 3 +- .../tutorial_quantum_chemistry.metadata.json | 3 +- ...rial_quantum_circuit_cutting.metadata.json | 3 +- .../tutorial_quantum_dropout.metadata.json | 5 +- .../tutorial_quantum_gans.metadata.json | 3 +- .../tutorial_quantum_metrology.metadata.json | 3 +- ...ial_quantum_natural_gradient.metadata.json | 3 +- ...al_quantum_transfer_learning.metadata.json | 3 +- .../tutorial_quanvolution.metadata.json | 3 +- .../tutorial_qubit_rotation.metadata.json | 3 +- .../tutorial_qubit_tapering.metadata.json | 3 +- .../tutorial_qubitization.metadata.json | 5 +- ...l_qutrits_bernstein_vazirani.metadata.json | 5 +- ...tutorial_resource_estimation.metadata.json | 3 +- .../tutorial_rl_pulse.metadata.json | 5 +- demonstrations/tutorial_rosalin.metadata.json | 3 +- .../tutorial_rotoselect.metadata.json | 3 +- .../tutorial_sc_qubits.metadata.json | 3 +- ...hadow_hamiltonian_simulation.metadata.json | 3 +- demonstrations/tutorial_spsa.metadata.json | 5 +- .../tutorial_state_preparation.metadata.json | 3 +- ...l_stochastic_parameter_shift.metadata.json | 3 +- .../tutorial_teleportation.metadata.json | 3 +- .../tutorial_testing_symmetry.metadata.json | 3 +- .../tutorial_tn_circuits.metadata.json | 3 +- .../tutorial_toric_code.metadata.json | 3 +- .../tutorial_trapped_ions.metadata.json | 3 +- .../tutorial_unitary_designs.metadata.json | 3 +- .../tutorial_univariate_qvr.metadata.json | 3 +- ...orial_variational_classifier.metadata.json | 3 +- demonstrations/tutorial_vqe.metadata.json | 3 +- demonstrations/tutorial_vqe_qng.metadata.json | 3 +- .../tutorial_vqe_spin_sectors.metadata.json | 3 +- demonstrations/tutorial_vqe_vqd.metadata.json | 3 +- demonstrations/tutorial_vqls.metadata.json | 3 +- demonstrations/tutorial_vqt.metadata.json | 3 +- .../tutorial_zx_calculus.metadata.json | 5 +- demonstrations/vqe_parallel.metadata.json | 3 +- demonstrations_metadata.md | 21 ++- .../demo.metadata.schema.0.1.3.json | 2 +- .../demo.metadata.schema.0.1.4.json | 135 ++++++++++++++++++ update_metadata.py | 133 ----------------- 164 files changed, 360 insertions(+), 525 deletions(-) create mode 100644 metadata_schemas/demo.metadata.schema.0.1.4.json delete mode 100644 update_metadata.py diff --git a/.github/workflows/validate-demo-metadata.yml b/.github/workflows/validate-demo-metadata.yml index 5e4540bdb7..ed5f617b76 100644 --- a/.github/workflows/validate-demo-metadata.yml +++ b/.github/workflows/validate-demo-metadata.yml @@ -101,7 +101,7 @@ jobs: METADATA_FILE_LIST: ${{ needs.generate-metadata-file-list.outputs.metadata_files }} run: | cd metadata_schemas - ${{ steps.poetry.outputs.bin }} run check-jsonschema -v --traceback-mode full --schemafile demo.metadata.schema.0.1.3.json $METADATA_FILE_LIST + ${{ steps.poetry.outputs.bin }} run check-jsonschema -v --traceback-mode full --schemafile demo.metadata.schema.0.1.4.json $METADATA_FILE_LIST validate-metadata-preview-images: runs-on: ubuntu-latest diff --git a/demonstrations/adjoint_diff_benchmarking.metadata.json b/demonstrations/adjoint_diff_benchmarking.metadata.json index b5089d616c..6ad29f53dc 100644 --- a/demonstrations/adjoint_diff_benchmarking.metadata.json +++ b/demonstrations/adjoint_diff_benchmarking.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2021-11-23T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [], "tags": [], "previewImages": [ @@ -17,7 +17,6 @@ ], "seoDescription": "Benchmarking file for adjoint diff demonstration.", "doi": "", - "canonicalURL": "/qml/demos/adjoint_diff_benchmarking", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/ahs_aquila.metadata.json b/demonstrations/ahs_aquila.metadata.json index 5a59fbf611..fc530f8d99 100644 --- a/demonstrations/ahs_aquila.metadata.json +++ b/demonstrations/ahs_aquila.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2023-05-16T00:00:00+00:00", - "dateOfLastModification": "2024-09-04T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": ["Quantum Hardware", "Devices and Performance", "Quantum Computing"], "tags": [], "previewImages": [ @@ -17,7 +17,6 @@ ], "seoDescription": "Perform measurements on neutral atom hardware through PennyLane", "doi": "", - "canonicalURL": "/qml/demos/ahs_aquila", "references": [ { "id": "Semeghini", @@ -76,4 +75,4 @@ "logo": "/_static/hardware_logos/aws.png" } ] -} \ No newline at end of file +} diff --git a/demonstrations/braket-parallel-gradients.metadata.json b/demonstrations/braket-parallel-gradients.metadata.json index 11e4e396e6..16ba4b00c5 100644 --- a/demonstrations/braket-parallel-gradients.metadata.json +++ b/demonstrations/braket-parallel-gradients.metadata.json @@ -12,7 +12,7 @@ } ], "dateOfPublication": "2020-12-08T00:00:00+00:00", - "dateOfLastModification": "2024-08-14T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Devices and Performance" ], @@ -25,7 +25,6 @@ ], "seoDescription": "Parallelize gradient calculations with Amazon Braket", "doi": "", - "canonicalURL": "/qml/demos/braket-parallel-gradients", "references": [], "basedOnPapers": [], "referencedByPapers": [], @@ -48,4 +47,4 @@ "logo": "/_static/hardware_logos/aws.png" } ] -} \ No newline at end of file +} diff --git a/demonstrations/circuits_as_fourier_series.metadata.json b/demonstrations/circuits_as_fourier_series.metadata.json index 3e3591d8d6..a1eb0efa46 100644 --- a/demonstrations/circuits_as_fourier_series.metadata.json +++ b/demonstrations/circuits_as_fourier_series.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2023-09-11T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization", "Quantum Machine Learning" @@ -24,7 +24,6 @@ ], "seoDescription": "Learn with this interactive, code-free introduction to the idea of quantum circuits as Fourier series.", "doi": "", - "canonicalURL": "/qml/demos/circuits_as_fourier_series", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/covalent_cloud_gpu.metadata.json b/demonstrations/covalent_cloud_gpu.metadata.json index eb9d465149..65e4fefd12 100644 --- a/demonstrations/covalent_cloud_gpu.metadata.json +++ b/demonstrations/covalent_cloud_gpu.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2024-05-24T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning" ], @@ -26,7 +26,6 @@ ], "seoDescription": "Explore the process of running GPU-accelerated quantum circuit simulations on Covalent Cloud using PennyLane.", "doi": "", - "canonicalURL": "/qml/demos/covalent_cloud_gpu", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/ensemble_multi_qpu.metadata.json b/demonstrations/ensemble_multi_qpu.metadata.json index 72a2d07692..2163c50b80 100644 --- a/demonstrations/ensemble_multi_qpu.metadata.json +++ b/demonstrations/ensemble_multi_qpu.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2020-02-14T00:00:00+00:00", - "dateOfLastModification": "2024-08-14T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning" ], @@ -19,7 +19,6 @@ ], "seoDescription": "We demonstrate how two QPUs can be combined in parallel to help solve a machine learning classification problem, using PyTorch and PennyLane.", "doi": "", - "canonicalURL": "/qml/demos/ensemble_multi_qpu", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/function_fitting_qsp.metadata.json b/demonstrations/function_fitting_qsp.metadata.json index 9ba28e43c8..192492b725 100644 --- a/demonstrations/function_fitting_qsp.metadata.json +++ b/demonstrations/function_fitting_qsp.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2022-05-24T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Learn how to create polynomial approximations to functions using Quantum Signal Processing (QSP).", "doi": "", - "canonicalURL": "/qml/demos/function_fitting_qsp", "references": [ { "id": "Martyn2021", diff --git a/demonstrations/gbs.metadata.json b/demonstrations/gbs.metadata.json index 7161fd9d77..b26778084c 100644 --- a/demonstrations/gbs.metadata.json +++ b/demonstrations/gbs.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2020-12-04T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Hardware", "Quantum Computing" @@ -23,7 +23,6 @@ ], "seoDescription": "Using light to perform tasks beyond the reach of classical computers.", "doi": "", - "canonicalURL": "/qml/demos/gbs", "references": [ { "id": "Arute2019", @@ -98,4 +97,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/getting_started_with_hybrid_jobs.metadata.json b/demonstrations/getting_started_with_hybrid_jobs.metadata.json index a24c717bd1..5a35d31a97 100644 --- a/demonstrations/getting_started_with_hybrid_jobs.metadata.json +++ b/demonstrations/getting_started_with_hybrid_jobs.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2023-10-16T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Devices and Performance" ], @@ -23,7 +23,6 @@ ], "seoDescription": "Getting started with the Amazon Braket Hybrid Jobs", "doi": "", - "canonicalURL": "/qml/demos/getting_started_with_hybrid_jobs", "references": [], "basedOnPapers": [], "referencedByPapers": [], @@ -35,4 +34,4 @@ "logo": "/_static/hardware_logos/aws.png" } ] -} \ No newline at end of file +} diff --git a/demonstrations/gqe_training.metadata.json b/demonstrations/gqe_training.metadata.json index 5bc6143d61..951117cb0d 100644 --- a/demonstrations/gqe_training.metadata.json +++ b/demonstrations/gqe_training.metadata.json @@ -3,13 +3,13 @@ "authors": [ { "username": "Joseph" - }, + }, { "username": "zy_n" } ], "dateOfPublication": "2024-09-20T00:00:00+00:00", - "dateOfLastModification": "2024-09-20T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": ["Quantum Machine Learning", "Quantum Chemistry", "Algorithms"], "tags": [], "previewImages": [ @@ -24,7 +24,6 @@ ], "seoDescription": "Learn how you can train a small GPT model using the generative quantum eigensolver (GQE) technique and PennyLane data.", "doi": "", - "canonicalURL": "/qml/demos/gqe_training", "references": [ { "id": "nakaji2024", @@ -71,4 +70,4 @@ } ], "hardware": [] -} \ No newline at end of file +} diff --git a/demonstrations/how_to_use_qiskit1_with_pennylane.metadata.json b/demonstrations/how_to_use_qiskit1_with_pennylane.metadata.json index 19b5395679..3c9d27a9ba 100644 --- a/demonstrations/how_to_use_qiskit1_with_pennylane.metadata.json +++ b/demonstrations/how_to_use_qiskit1_with_pennylane.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-07-02T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Computing", "How-to" @@ -24,7 +24,6 @@ ], "seoDescription": "Learn how to get started using Qiskit 1.0 with PennyLane", "doi": "", - "canonicalURL": "/qml/demos/how_to_use_qiskit1_with_pennylane", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/ibm_pennylane.metadata.json b/demonstrations/ibm_pennylane.metadata.json index b0e3468e82..48077adbab 100644 --- a/demonstrations/ibm_pennylane.metadata.json +++ b/demonstrations/ibm_pennylane.metadata.json @@ -12,7 +12,7 @@ } ], "dateOfPublication": "2023-06-20T00:00:00+00:00", - "dateOfLastModification": "2024-08-08T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Devices and Performance" ], @@ -29,7 +29,6 @@ ], "seoDescription": "Learn how to use IBM devices with PennyLane.", "doi": "", - "canonicalURL": "/qml/demos/ibm_pennylane", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/learning2learn.metadata.json b/demonstrations/learning2learn.metadata.json index b84b92c412..7b1f3a810b 100644 --- a/demonstrations/learning2learn.metadata.json +++ b/demonstrations/learning2learn.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2021-03-02T00:00:00+00:00", - "dateOfLastModification": "2024-09-04T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Use a classical recurrent neural network to initilize the parameters of a variational quatum algorithm.", "doi": "", - "canonicalURL": "/qml/demos/learning2learn", "references": [], "basedOnPapers": [ "10.48550/arXiv.1907.05415" @@ -37,4 +36,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/ml_classical_shadows.metadata.json b/demonstrations/ml_classical_shadows.metadata.json index 14c812fb20..3b515b5fc0 100644 --- a/demonstrations/ml_classical_shadows.metadata.json +++ b/demonstrations/ml_classical_shadows.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2022-05-02T00:00:00+00:00", - "dateOfLastModification": "2024-09-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning" ], @@ -23,7 +23,6 @@ ], "seoDescription": "Learn how to apply machine learning to quantum many-body problems by using classical shadow formalism and ML to predict the ground-state properties of the 2D antiferromagnetic Heisenberg model.", "doi": "", - "canonicalURL": "/qml/demos/ml_classical_shadows", "references": [ { "id": "preskill", diff --git a/demonstrations/oqc_pulse.metadata.json b/demonstrations/oqc_pulse.metadata.json index 37353fa36e..1c964a11be 100644 --- a/demonstrations/oqc_pulse.metadata.json +++ b/demonstrations/oqc_pulse.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2023-10-30T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Computing" ], @@ -23,7 +23,6 @@ ], "seoDescription": "Learn how to create polynomial approximations to functions using Quantum Signal Processing (QSP).", "doi": "", - "canonicalURL": "/qml/demos/oqc_pulse", "references": [ { "id": "Rahamim", @@ -71,4 +70,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/plugins_hybrid.metadata.json b/demonstrations/plugins_hybrid.metadata.json index 5959f055c6..355c197960 100644 --- a/demonstrations/plugins_hybrid.metadata.json +++ b/demonstrations/plugins_hybrid.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2019-10-11T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Devices and Performance" ], @@ -19,7 +19,6 @@ ], "seoDescription": "This tutorial introduces the notion of hybrid computation by combining several PennyLane device backends to train an algorithm containing both photonic and qubit devices.", "doi": "", - "canonicalURL": "/qml/demos/plugins_hybrid", "references": [], "basedOnPapers": [], "referencedByPapers": [], @@ -35,4 +34,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/pytorch_noise.metadata.json b/demonstrations/pytorch_noise.metadata.json index f5f868189d..3bb21e9b33 100644 --- a/demonstrations/pytorch_noise.metadata.json +++ b/demonstrations/pytorch_noise.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2019-10-11T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Devices and Performance" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Extend PyTorch with real quantum computing power, by using it to optimize a noisy quantum hardware device.", "doi": "", - "canonicalURL": "/qml/demos/pytorch_noise", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/qnspsa.metadata.json b/demonstrations/qnspsa.metadata.json index 03ad2d3765..d7f8a88daa 100644 --- a/demonstrations/qnspsa.metadata.json +++ b/demonstrations/qnspsa.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2022-07-18T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Introduction to the Quantum natural SPSA optimizer, which reduces the number of quantum measurements in the optimization.", "doi": "", - "canonicalURL": "/qml/demos/qnspsa", "references": [ { "id": "Gacon2021", @@ -90,4 +89,4 @@ "logo": "/_static/hardware_logos/aws.png" } ] -} \ No newline at end of file +} diff --git a/demonstrations/qonn.metadata.json b/demonstrations/qonn.metadata.json index c426d9de26..3fd2f6a305 100644 --- a/demonstrations/qonn.metadata.json +++ b/demonstrations/qonn.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2020-08-05T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Optimizing a quantum optical neural network using PennyLane.", "doi": "", - "canonicalURL": "/qml/demos/qonn", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/qrack.metadata.json b/demonstrations/qrack.metadata.json index c0978d5acb..94eb96cef9 100644 --- a/demonstrations/qrack.metadata.json +++ b/demonstrations/qrack.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-07-10T00:00:00+00:00", - "dateOfLastModification": "2024-08-20T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Devices and Performance" ], @@ -23,7 +23,6 @@ ], "seoDescription": "Quantum JIT compilation (QJIT) using the Qrack device for PennyLane and Catalyst, with GPU-acceleration and novel optimization.", "doi": "", - "canonicalURL": "/qml/demos/qrack", "references": [ { "id": "QECReport", diff --git a/demonstrations/qsim_beyond_classical.metadata.json b/demonstrations/qsim_beyond_classical.metadata.json index 4845991c0d..d95510247c 100644 --- a/demonstrations/qsim_beyond_classical.metadata.json +++ b/demonstrations/qsim_beyond_classical.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2020-11-30T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Hardware", "Quantum Computing" @@ -20,7 +20,6 @@ ], "seoDescription": "Use Google's qsim simulator to explore the barriers between quantum and classical computing, and recreate their benchmarks and circuits.", "doi": "", - "canonicalURL": "/qml/demos/qsim_beyond_classical", "references": [ { "id": "Arute2019", diff --git a/demonstrations/quantum_neural_net.metadata.json b/demonstrations/quantum_neural_net.metadata.json index 6c67918628..15ea1533f9 100644 --- a/demonstrations/quantum_neural_net.metadata.json +++ b/demonstrations/quantum_neural_net.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2019-10-11T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Fit to noisy data with a variational quantum circuit.", "doi": "", - "canonicalURL": "/qml/demos/quantum_neural_net", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/quantum_volume.metadata.json b/demonstrations/quantum_volume.metadata.json index 7158669f03..5a6a18c13e 100644 --- a/demonstrations/quantum_volume.metadata.json +++ b/demonstrations/quantum_volume.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2020-12-15T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Hardware", "Quantum Computing" @@ -20,7 +20,6 @@ ], "seoDescription": "Learn about quantum volume, and how to compute it.", "doi": "", - "canonicalURL": "/qml/demos/quantum_volume", "references": [ { "id": "top500", @@ -109,4 +108,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_How_to_optimize_QML_model_using_JAX_and_JAXopt.metadata.json b/demonstrations/tutorial_How_to_optimize_QML_model_using_JAX_and_JAXopt.metadata.json index 015aee733d..159dc0a2a3 100644 --- a/demonstrations/tutorial_How_to_optimize_QML_model_using_JAX_and_JAXopt.metadata.json +++ b/demonstrations/tutorial_How_to_optimize_QML_model_using_JAX_and_JAXopt.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2024-01-18T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning", "Optimization", @@ -28,7 +28,6 @@ ], "seoDescription": "Learn how to train a quantum machine learning model using PennyLane, JAX, and JAXopt.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_How_to_optimize_QML_model_using_JAX_and_JAXopt", "references": [], "basedOnPapers": [], "referencedByPapers": [], @@ -49,4 +48,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_How_to_optimize_QML_model_using_JAX_and_Optax.metadata.json b/demonstrations/tutorial_How_to_optimize_QML_model_using_JAX_and_Optax.metadata.json index ec31611a56..2148b168eb 100644 --- a/demonstrations/tutorial_How_to_optimize_QML_model_using_JAX_and_Optax.metadata.json +++ b/demonstrations/tutorial_How_to_optimize_QML_model_using_JAX_and_Optax.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2024-01-18T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning", "Optimization", @@ -28,7 +28,6 @@ ], "seoDescription": "Learn how to train a quantum machine learning model using PennyLane, JAX, and Optax.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_How_to_optimize_QML_model_using_JAX_and_Optax", "references": [], "basedOnPapers": [], "referencedByPapers": [], @@ -49,4 +48,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_How_to_optimize_QML_model_using_JAX_catalyst_and_Optax.metadata.json b/demonstrations/tutorial_How_to_optimize_QML_model_using_JAX_catalyst_and_Optax.metadata.json index 3a913bf120..4f82ad28e0 100644 --- a/demonstrations/tutorial_How_to_optimize_QML_model_using_JAX_catalyst_and_Optax.metadata.json +++ b/demonstrations/tutorial_How_to_optimize_QML_model_using_JAX_catalyst_and_Optax.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-04-26T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning", "Optimization", @@ -25,7 +25,6 @@ ], "seoDescription": "Learn how to train a quantum machine learning model using PennyLane, JAX, Catalyst, and Optax.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_How_to_optimize_QML_model_using_JAX_catalyst_and_Optax", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/tutorial_How_to_simulate_quantum_circuits_with_tensor_networks.metadata.json b/demonstrations/tutorial_How_to_simulate_quantum_circuits_with_tensor_networks.metadata.json index 58d598dd88..7065e33abc 100644 --- a/demonstrations/tutorial_How_to_simulate_quantum_circuits_with_tensor_networks.metadata.json +++ b/demonstrations/tutorial_How_to_simulate_quantum_circuits_with_tensor_networks.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-07-09T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Getting Started", "Quantum Computing", @@ -28,7 +28,6 @@ ], "seoDescription": "Learn how to simulate quantum circuits with tensor networks using the default.tensor PennyLane device.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_How_to_simulate_quantum_circuits_with_tensor_networks", "references": [ { "id": "orus", diff --git a/demonstrations/tutorial_QGAN.metadata.json b/demonstrations/tutorial_QGAN.metadata.json index 60e966f15f..2cf2f49c60 100644 --- a/demonstrations/tutorial_QGAN.metadata.json +++ b/demonstrations/tutorial_QGAN.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2019-10-11T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning" ], @@ -19,7 +19,6 @@ ], "seoDescription": "This demo constructs and trains a Quantum Generative Adversarial Network (QGAN) using PennyLane, Cirq, and TensorFlow.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_QGAN", "references": [], "basedOnPapers": [ "10.1103/PhysRevA.98.012324" diff --git a/demonstrations/tutorial_QUBO.metadata.json b/demonstrations/tutorial_QUBO.metadata.json index 3c65c09cb1..2c6477d250 100644 --- a/demonstrations/tutorial_QUBO.metadata.json +++ b/demonstrations/tutorial_QUBO.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-02-29T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -23,10 +23,9 @@ ], "seoDescription": "Learn how to solve a QUBO problem in a quantum computer.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_QUBO", "references": [], "basedOnPapers": [], "referencedByPapers": [], "relatedContent": [ ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_adaptive_circuits.metadata.json b/demonstrations/tutorial_adaptive_circuits.metadata.json index a199402a12..676fc101da 100644 --- a/demonstrations/tutorial_adaptive_circuits.metadata.json +++ b/demonstrations/tutorial_adaptive_circuits.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2021-09-13T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Chemistry" ], @@ -23,7 +23,6 @@ ], "seoDescription": "Learn how to build quantum chemistry circuits adaptively.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_adaptive_circuits", "references": [ { "id": "peruzzo2014", diff --git a/demonstrations/tutorial_adjoint_diff.metadata.json b/demonstrations/tutorial_adjoint_diff.metadata.json index 441f91b3dd..95e9a2c6fc 100644 --- a/demonstrations/tutorial_adjoint_diff.metadata.json +++ b/demonstrations/tutorial_adjoint_diff.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2021-11-23T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Getting Started" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Learn how to use the adjoint method to compute gradients of quantum circuits.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_adjoint_diff", "references": [ { "id": "Jones2020", diff --git a/demonstrations/tutorial_adversarial_attacks_QML.metadata.json b/demonstrations/tutorial_adversarial_attacks_QML.metadata.json index db3e8d6385..5a8a3711b0 100644 --- a/demonstrations/tutorial_adversarial_attacks_QML.metadata.json +++ b/demonstrations/tutorial_adversarial_attacks_QML.metadata.json @@ -10,7 +10,7 @@ } ], "dateOfPublication": "2024-09-16T00:00:00+00:00", - "dateOfLastModification": "2024-09-16T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": ["Quantum Machine Learning", "Quantum Computing"], "tags": ["Quantum machine learning", "QML", "Adversarial attacks", "Quantum security"], "previewImages": [ @@ -25,7 +25,6 @@ ], "seoDescription": "Learn how to construct adversarial attacks on classification networks and how to make quantum machine learning (QML) models more robust.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_adversarial_attacks_QML", "references": [ { "id": "Wendlinger2024", @@ -77,4 +76,4 @@ } ], "hardware": [] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_apply_qsvt.metadata.json b/demonstrations/tutorial_apply_qsvt.metadata.json index 5b7fe315bb..05d050d721 100644 --- a/demonstrations/tutorial_apply_qsvt.metadata.json +++ b/demonstrations/tutorial_apply_qsvt.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2023-08-22T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Computing", "Algorithms", @@ -28,7 +28,6 @@ ], "seoDescription": "Applying QSVT for matrix inversion", "doi": "", - "canonicalURL": "/qml/demos/tutorial_apply_qsvt", "references": [ { "type": "article", diff --git a/demonstrations/tutorial_backprop.metadata.json b/demonstrations/tutorial_backprop.metadata.json index b472049cb5..d29c25bf81 100644 --- a/demonstrations/tutorial_backprop.metadata.json +++ b/demonstrations/tutorial_backprop.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2020-08-11T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Getting Started" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Using backpropagation can speed up training of quantum circuits compared to the parameter-shift rule—if you are using a simulator.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_backprop", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/tutorial_barren_gadgets.metadata.json b/demonstrations/tutorial_barren_gadgets.metadata.json index 938304b74b..0682ae223a 100644 --- a/demonstrations/tutorial_barren_gadgets.metadata.json +++ b/demonstrations/tutorial_barren_gadgets.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2022-12-09T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -23,7 +23,6 @@ ], "seoDescription": "Use perturbative gadgets to avoid cost-function-dependent barren plateaus.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_barren_gadgets", "references": [ { "id": "cichy2022", diff --git a/demonstrations/tutorial_barren_plateaus.metadata.json b/demonstrations/tutorial_barren_plateaus.metadata.json index 3238857ebb..aeba0c1834 100644 --- a/demonstrations/tutorial_barren_plateaus.metadata.json +++ b/demonstrations/tutorial_barren_plateaus.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2019-10-11T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Showing how randomized quantum circuits face the problem of barren plateaus using PennyLane. We will partly reproduce some of the findings in McClean et. al., 2018 with just a few lines of code.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_barren_plateaus", "references": [ { "id": "Dauphin2014", diff --git a/demonstrations/tutorial_block_encoding.metadata.json b/demonstrations/tutorial_block_encoding.metadata.json index 065fc1d25d..09d93d7dde 100644 --- 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": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Computing", "Algorithms" @@ -30,7 +30,6 @@ ], "seoDescription": "Learn about methods to achieve block-encoding for a given matrix.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_block_encoding", "references": [ { "id": "Daan2023", diff --git a/demonstrations/tutorial_bluequbit.metadata.json b/demonstrations/tutorial_bluequbit.metadata.json index 95928b86f9..5103d7af75 100644 --- a/demonstrations/tutorial_bluequbit.metadata.json +++ b/demonstrations/tutorial_bluequbit.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-09-24T00:00:00+00:00", - "dateOfLastModification": "2024-09-24T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Devices and Performance", "Quantum Computing" @@ -24,7 +24,6 @@ ], "seoDescription": "Run large-scale quantum simulations with PennyLane and BlueQubit.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_bluequbit", "references": [ { "id": "Draper2000", @@ -34,7 +33,7 @@ "year": "2000", "journal": "", "url": "https://arxiv.org/abs/quant-ph/0008033" - } + } ], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/tutorial_chemical_reactions.metadata.json b/demonstrations/tutorial_chemical_reactions.metadata.json index 3b48276428..af94ad0df5 100644 --- a/demonstrations/tutorial_chemical_reactions.metadata.json +++ b/demonstrations/tutorial_chemical_reactions.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2021-07-23T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Chemistry" ], @@ -22,7 +22,6 @@ ], "seoDescription": "Construct potential energy surfaces for chemical reactions", "doi": "", - "canonicalURL": "/qml/demos/tutorial_chemical_reactions", "references": [ { "id": "motta2020", diff --git a/demonstrations/tutorial_circuit_compilation.metadata.json b/demonstrations/tutorial_circuit_compilation.metadata.json index e370150a6e..1d8184300a 100644 --- a/demonstrations/tutorial_circuit_compilation.metadata.json +++ b/demonstrations/tutorial_circuit_compilation.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2023-06-14T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Getting Started", "Devices and Performance" @@ -24,7 +24,6 @@ ], "seoDescription": "Learn about circuit transformations and quantum circuit compilation with PennyLane", "doi": "", - "canonicalURL": "/qml/demos/tutorial_circuit_compilation", "references": [], "basedOnPapers": [], "referencedByPapers": [], @@ -35,4 +34,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_classical_expval_estimation.metadata.json b/demonstrations/tutorial_classical_expval_estimation.metadata.json index b3ce4a2140..53e13148c5 100644 --- a/demonstrations/tutorial_classical_expval_estimation.metadata.json +++ b/demonstrations/tutorial_classical_expval_estimation.metadata.json @@ -6,12 +6,12 @@ } ], "dateOfPublication": "2024-09-10T00:00:00+00:00", - "dateOfLastModification": "2024-09-10T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Computing" ], "tags": [], - "previewImages": [ + "previewImages": [ { "type": "thumbnail", "uri": "/_static/demo_thumbnails/regular_demo_thumbnails/thumbnail_classical_expval_estimation.png" @@ -23,7 +23,6 @@ ], "seoDescription": "Estimate expectation values from parametrized quantum circuits efficiently on average with truncated Pauli propagation.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_classical_expval_estimation", "references": [ { "id": "gottesman", diff --git a/demonstrations/tutorial_classical_kernels.metadata.json b/demonstrations/tutorial_classical_kernels.metadata.json index 2b8ca1bb58..3829115493 100644 --- a/demonstrations/tutorial_classical_kernels.metadata.json +++ b/demonstrations/tutorial_classical_kernels.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2022-03-01T00:00:00+00:00", - "dateOfLastModification": "2024-09-04T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Finding a quantum kernel to approximate the Gaussian kernel.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_classical_kernels", "references": [ { "id": "QEK", diff --git a/demonstrations/tutorial_classical_shadows.metadata.json b/demonstrations/tutorial_classical_shadows.metadata.json index 00b0a6f220..c25ea6792d 100644 --- a/demonstrations/tutorial_classical_shadows.metadata.json +++ b/demonstrations/tutorial_classical_shadows.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2021-06-14T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Algorithms" ], @@ -22,7 +22,6 @@ ], "seoDescription": "Learn how to construct classical shadows and use them to estimate observables.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_classical_shadows", "references": [ { "id": "Mauro2003", diff --git a/demonstrations/tutorial_classically_boosted_vqe.metadata.json b/demonstrations/tutorial_classically_boosted_vqe.metadata.json index e5be1d85d1..8d8ed2c7bd 100644 --- a/demonstrations/tutorial_classically_boosted_vqe.metadata.json +++ b/demonstrations/tutorial_classically_boosted_vqe.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2022-10-31T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Chemistry" ], @@ -22,7 +22,6 @@ ], "seoDescription": "Learn how to implement classically-boosted VQE in PennyLane.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_classically_boosted_vqe", "references": [ { "id": "Radin2021", diff --git a/demonstrations/tutorial_clifford_circuit_simulations.metadata.json b/demonstrations/tutorial_clifford_circuit_simulations.metadata.json index 7904fb8337..2dc1876ec4 100644 --- a/demonstrations/tutorial_clifford_circuit_simulations.metadata.json +++ b/demonstrations/tutorial_clifford_circuit_simulations.metadata.json @@ -6,12 +6,12 @@ } ], "dateOfPublication": "2024-04-12T00:00:00+00:00", - "dateOfLastModification": "2024-09-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Devices and Performance" ], "tags": [], - "previewImages": [ + "previewImages": [ { "type": "thumbnail", "uri": "/_static/demonstration_assets/clifford_simulation/thumbnail_clifford_circuit_simulations.png" @@ -23,7 +23,6 @@ ], "seoDescription": "Perform efficient simulations for Clifford circuits.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_clifford_circuit_simulations", "references": [ { "id": "supremecy_exp1", @@ -94,4 +93,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_coherent_vqls.metadata.json b/demonstrations/tutorial_coherent_vqls.metadata.json index 655f8974b9..45f1eb0975 100644 --- a/demonstrations/tutorial_coherent_vqls.metadata.json +++ b/demonstrations/tutorial_coherent_vqls.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2019-11-06T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -19,7 +19,6 @@ ], "seoDescription": "This demonstration extends the variational quantum linear solver to solve linear equations defined by a probabilistic coherent operation.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_coherent_vqls", "references": [ { "id": "BravoPrieto2019", diff --git a/demonstrations/tutorial_contextuality.metadata.json b/demonstrations/tutorial_contextuality.metadata.json index 2432fce583..146da6192d 100644 --- a/demonstrations/tutorial_contextuality.metadata.json +++ b/demonstrations/tutorial_contextuality.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2023-09-06T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning" ], @@ -23,7 +23,6 @@ ], "seoDescription": "Train a problem-inspired ansatz on a contextuality-inspired dataset.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_contextuality", "references": [ { "id": "paper", @@ -80,4 +79,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_data_reuploading_classifier.metadata.json b/demonstrations/tutorial_data_reuploading_classifier.metadata.json index 7b53e58533..bc8f17bc73 100644 --- a/demonstrations/tutorial_data_reuploading_classifier.metadata.json +++ b/demonstrations/tutorial_data_reuploading_classifier.metadata.json @@ -6,20 +6,19 @@ } ], "dateOfPublication": "2019-10-11T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning" ], "tags": [], "previewImages": [ { - "type": "thumbnail", + "type": "thumbnail", "uri": "/_static/demo_thumbnails/regular_demo_thumbnails/thumbnail_data-reuploading_classified.png" } ], "seoDescription": "Implement a single-qubit universal quantum classifier using PennyLane.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_data_reuploading_classifier", "references": [ { "id": "PerezSalinas2019", diff --git a/demonstrations/tutorial_diffable-mitigation.metadata.json b/demonstrations/tutorial_diffable-mitigation.metadata.json index 0476f6ba1c..78a66f6e96 100644 --- a/demonstrations/tutorial_diffable-mitigation.metadata.json +++ b/demonstrations/tutorial_diffable-mitigation.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2022-08-22T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Differentiable error mitigation", "doi": "", - "canonicalURL": "/qml/demos/tutorial_diffable-mitigation", "references": [ { "id": "DiffableTransforms", diff --git a/demonstrations/tutorial_diffable_shadows.metadata.json b/demonstrations/tutorial_diffable_shadows.metadata.json index f26318128c..87124b0296 100644 --- a/demonstrations/tutorial_diffable_shadows.metadata.json +++ b/demonstrations/tutorial_diffable_shadows.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2022-10-07T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Algorithms", "Quantum Computing" @@ -20,7 +20,6 @@ ], "seoDescription": "Classical shadows in the Pauli basis", "doi": "", - "canonicalURL": "/qml/demos/tutorial_diffable_shadows", "references": [ { "id": "Huang2020", diff --git a/demonstrations/tutorial_differentiable_HF.metadata.json b/demonstrations/tutorial_differentiable_HF.metadata.json index b904496e72..2389de40b2 100644 --- a/demonstrations/tutorial_differentiable_HF.metadata.json +++ b/demonstrations/tutorial_differentiable_HF.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2022-05-09T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Chemistry" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Learn how to use the differentiable Hartree-Fock solver", "doi": "", - "canonicalURL": "/qml/demos/tutorial_differentiable_HF", "references": [ { "id": "arrazola2021", diff --git a/demonstrations/tutorial_doubly_stochastic.metadata.json b/demonstrations/tutorial_doubly_stochastic.metadata.json index cecbb7b58f..85af9a0ffb 100644 --- a/demonstrations/tutorial_doubly_stochastic.metadata.json +++ b/demonstrations/tutorial_doubly_stochastic.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2019-10-16T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Minimize a Hamiltonian via an adaptive shot optimization strategy with doubly stochastic gradient descent.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_doubly_stochastic", "references": [ { "id": "Sweke2019", diff --git a/demonstrations/tutorial_eqnn_force_field.metadata.json b/demonstrations/tutorial_eqnn_force_field.metadata.json index 4ef29127f2..f4d7cb8b0a 100644 --- a/demonstrations/tutorial_eqnn_force_field.metadata.json +++ b/demonstrations/tutorial_eqnn_force_field.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2024-03-12T00:00:00+00:00", - "dateOfLastModification": "2024-09-16T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning", "Quantum Chemistry" @@ -27,7 +27,6 @@ ], "seoDescription": "What is equivariant quantum machine learning for chemistry?", "doi": "", - "canonicalURL": "/qml/demos/tutorial_eqnn_force_field", "references": [ { "id": "Le", @@ -106,4 +105,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_equivariant_graph_embedding.metadata.json b/demonstrations/tutorial_equivariant_graph_embedding.metadata.json index 3d2ac4bbfb..22cbcd9936 100644 --- a/demonstrations/tutorial_equivariant_graph_embedding.metadata.json +++ b/demonstrations/tutorial_equivariant_graph_embedding.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2023-07-13T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning" ], @@ -23,7 +23,6 @@ ], "seoDescription": "Find out more about how to embedd graphs into quantum states.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_equivariant_graph_embedding", "references": [ { "id": "Skolik2022", @@ -53,4 +52,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_error_mitigation.metadata.json b/demonstrations/tutorial_error_mitigation.metadata.json index 90b25af2a0..61b744a078 100644 --- a/demonstrations/tutorial_error_mitigation.metadata.json +++ b/demonstrations/tutorial_error_mitigation.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2021-11-29T00:00:00+00:00", - "dateOfLastModification": "2024-08-21T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Algorithms", "Quantum Computing" @@ -23,7 +23,6 @@ ], "seoDescription": "Learn how to mitigate quantum circuits using Mitiq and PennyLane.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_error_mitigation", "references": [ { "id": "proctor2020measuring", @@ -76,4 +75,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_error_prop.metadata.json b/demonstrations/tutorial_error_prop.metadata.json index 8241e2f545..e77f3ee4b3 100644 --- a/demonstrations/tutorial_error_prop.metadata.json +++ b/demonstrations/tutorial_error_prop.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-05-03T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Algorithms", "Quantum Computing", @@ -25,7 +25,6 @@ ], "seoDescription": "Learn how to propagate error through quantum circuits.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_error_prop", "references": [ { "id": "TrotterError", diff --git a/demonstrations/tutorial_expressivity_fourier_series.metadata.json b/demonstrations/tutorial_expressivity_fourier_series.metadata.json index 2e408c2f3f..a15b3e41cb 100644 --- a/demonstrations/tutorial_expressivity_fourier_series.metadata.json +++ b/demonstrations/tutorial_expressivity_fourier_series.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2020-08-24T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning" ], @@ -22,7 +22,6 @@ ], "seoDescription": "The class of functions a quantum model can learn is characterized by the structure of its corresponding Fourier series.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_expressivity_fourier_series", "references": [ { "id": "schuld2020", @@ -46,4 +45,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_falqon.metadata.json b/demonstrations/tutorial_falqon.metadata.json index 1f024c6549..3af0db611b 100644 --- a/demonstrations/tutorial_falqon.metadata.json +++ b/demonstrations/tutorial_falqon.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2021-05-21T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -22,7 +22,6 @@ ], "seoDescription": "Solve combinatorial optimization problems without a classical optimizer", "doi": "", - "canonicalURL": "/qml/demos/tutorial_falqon", "references": [ { "id": "Magann2021", diff --git a/demonstrations/tutorial_fermionic_operators.metadata.json b/demonstrations/tutorial_fermionic_operators.metadata.json index 8e2b777563..d23b2be902 100644 --- a/demonstrations/tutorial_fermionic_operators.metadata.json +++ b/demonstrations/tutorial_fermionic_operators.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2023-06-27T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Chemistry" ], @@ -27,7 +27,6 @@ ], "seoDescription": "Construct Hamiltonians and other observables using fermionic creation and annihilation operators.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_fermionic_operators", "references": [ { "id": "surjan", @@ -53,4 +52,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_gaussian_transformation.metadata.json b/demonstrations/tutorial_gaussian_transformation.metadata.json index b5de2b3f3a..771442bc90 100644 --- a/demonstrations/tutorial_gaussian_transformation.metadata.json +++ b/demonstrations/tutorial_gaussian_transformation.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2019-10-11T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Getting Started" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Use quantum machine learning techniques to tune a beamsplitter.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_gaussian_transformation", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/tutorial_general_parshift.metadata.json b/demonstrations/tutorial_general_parshift.metadata.json index 186c39a714..b3903e5f70 100644 --- a/demonstrations/tutorial_general_parshift.metadata.json +++ b/demonstrations/tutorial_general_parshift.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2021-08-23T00:00:00+00:00", - "dateOfLastModification": "2024-09-04T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Reconstruct quantum functions and compute their derivatives.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_general_parshift", "references": [ { "id": "GenPar", diff --git a/demonstrations/tutorial_geometric_qml.metadata.json b/demonstrations/tutorial_geometric_qml.metadata.json index b4a188230d..5ed683f8a5 100644 --- a/demonstrations/tutorial_geometric_qml.metadata.json +++ b/demonstrations/tutorial_geometric_qml.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2022-10-18T00:00:00+00:00", - "dateOfLastModification": "2024-09-04T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Using the natural symmetries in a quantum learning problem can improve learning", "doi": "", - "canonicalURL": "/qml/demos/tutorial_geometric_qml", "references": [ { "id": "Bronstein2021", @@ -58,4 +57,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_givens_rotations.metadata.json b/demonstrations/tutorial_givens_rotations.metadata.json index 2fff93a4ad..7ce03efc41 100644 --- a/demonstrations/tutorial_givens_rotations.metadata.json +++ b/demonstrations/tutorial_givens_rotations.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2021-06-30T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Chemistry" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Discover the building blocks of quantum circuits for quantum chemistry", "doi": "", - "canonicalURL": "/qml/demos/tutorial_givens_rotations", "references": [ { "id": "anselmetti", diff --git a/demonstrations/tutorial_grovers_algorithm.metadata.json b/demonstrations/tutorial_grovers_algorithm.metadata.json index a6f4799044..c4dab1bb37 100644 --- a/demonstrations/tutorial_grovers_algorithm.metadata.json +++ b/demonstrations/tutorial_grovers_algorithm.metadata.json @@ -6,10 +6,10 @@ } ], "dateOfPublication": "2023-07-03T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ - "Getting Started", - "Algorithms", + "Getting Started", + "Algorithms", "Quantum Computing" ], "tags": [], @@ -25,7 +25,6 @@ ], "seoDescription": "Learn how to find an entry in a list using Grover's Algorithm", "doi": "", - "canonicalURL": "/qml/demos/tutorial_grovers_algorithm", "references": [], "basedOnPapers": [], "referencedByPapers": [], @@ -36,4 +35,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_guide_to_pennylane_knowing_qiskit.metadata.json b/demonstrations/tutorial_guide_to_pennylane_knowing_qiskit.metadata.json index a99afb3178..e2609e360c 100644 --- a/demonstrations/tutorial_guide_to_pennylane_knowing_qiskit.metadata.json +++ b/demonstrations/tutorial_guide_to_pennylane_knowing_qiskit.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-07-22T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Computing" ], @@ -23,7 +23,6 @@ ], "seoDescription": "This is your ultimate guide to PennyLane if you already know Qiskit.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_guide_to_pennylane_knowing_qiskit", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/tutorial_haar_measure.metadata.json b/demonstrations/tutorial_haar_measure.metadata.json index 931a0510a5..97b58dacbf 100644 --- a/demonstrations/tutorial_haar_measure.metadata.json +++ b/demonstrations/tutorial_haar_measure.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2021-03-22T00:00:00+00:00", - "dateOfLastModification": "2024-09-03T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning", "Quantum Computing" @@ -20,7 +20,6 @@ ], "seoDescription": "Learn all about the Haar measure and how to randomly sample quantum states.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_haar_measure", "references": [ { "id": "NandC2000", diff --git a/demonstrations/tutorial_here_comes_the_sun.metadata.json b/demonstrations/tutorial_here_comes_the_sun.metadata.json index 3bda2c258f..36335d5c43 100644 --- a/demonstrations/tutorial_here_comes_the_sun.metadata.json +++ b/demonstrations/tutorial_here_comes_the_sun.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2023-04-03T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -23,7 +23,6 @@ ], "seoDescription": "Learn about multivariate quantum gates for optimization", "doi": "", - "canonicalURL": "/qml/demos/tutorial_here_comes_the_sun", "references": [ { "id": "vatan", @@ -75,4 +74,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_how_to_collect_mcm_stats.metadata.json b/demonstrations/tutorial_how_to_collect_mcm_stats.metadata.json index 830ad87be9..8938ea83b7 100644 --- a/demonstrations/tutorial_how_to_collect_mcm_stats.metadata.json +++ b/demonstrations/tutorial_how_to_collect_mcm_stats.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-04-26T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Getting Started", "Quantum Computing", @@ -25,7 +25,6 @@ ], "seoDescription": "Learn how to collect statistics about measurements performed during a quantum circuit.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_how_to_collect_mcm_stats", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/tutorial_how_to_create_dynamic_mcm_circuits.metadata.json b/demonstrations/tutorial_how_to_create_dynamic_mcm_circuits.metadata.json index 3ab47cb58c..eeb016d7cf 100644 --- a/demonstrations/tutorial_how_to_create_dynamic_mcm_circuits.metadata.json +++ b/demonstrations/tutorial_how_to_create_dynamic_mcm_circuits.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-05-03T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Getting Started", "Quantum Computing", @@ -25,7 +25,6 @@ ], "seoDescription": "Learn how to create dynamic circuits with control flow based on mid-circuit measurements.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_how_to_create_dynamic_mcm_circuits", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/tutorial_how_to_quantum_just_in_time_compile_vqe_catalyst.metadata.json b/demonstrations/tutorial_how_to_quantum_just_in_time_compile_vqe_catalyst.metadata.json index 4de5c6fc82..575ad4eba4 100644 --- a/demonstrations/tutorial_how_to_quantum_just_in_time_compile_vqe_catalyst.metadata.json +++ b/demonstrations/tutorial_how_to_quantum_just_in_time_compile_vqe_catalyst.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2024-04-26T00:00:00+00:00", - "dateOfLastModification": "2024-09-04T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning", "Optimization", @@ -29,7 +29,6 @@ ], "seoDescription": "Learn how to find the ground state of a molecule with VQE using PennyLane, Catalyst, and just-in-time compilation.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_how_to_quantum_just_in_time_compile_vqe_catalyst", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/tutorial_how_to_use_noise_models.metadata.json b/demonstrations/tutorial_how_to_use_noise_models.metadata.json index 2a2d9d94a2..9d235628a7 100644 --- a/demonstrations/tutorial_how_to_use_noise_models.metadata.json +++ b/demonstrations/tutorial_how_to_use_noise_models.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-10-01T00:00:00+00:00", - "dateOfLastModification": "2024-10-01T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Computing", "How-to" @@ -24,7 +24,6 @@ ], "seoDescription": "Learn how noise models can be built and inserted into a quantum circuit in PennyLane.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_how_to_use_noise_models", "references": [ ], "basedOnPapers": [], diff --git a/demonstrations/tutorial_how_to_use_registers.metadata.json b/demonstrations/tutorial_how_to_use_registers.metadata.json index 2d46a3eeeb..fdb53666a8 100644 --- a/demonstrations/tutorial_how_to_use_registers.metadata.json +++ b/demonstrations/tutorial_how_to_use_registers.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-09-05T00:00:00+00:00", - "dateOfLastModification": "2024-09-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Getting Started", "How-to" @@ -24,7 +24,6 @@ ], "seoDescription": "Learn how wire registers can be built and used in PennyLane.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_how_to_use_registers", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/tutorial_implicit_diff_susceptibility.metadata.json b/demonstrations/tutorial_implicit_diff_susceptibility.metadata.json index a4c1aa2775..a336b36d71 100644 --- a/demonstrations/tutorial_implicit_diff_susceptibility.metadata.json +++ b/demonstrations/tutorial_implicit_diff_susceptibility.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2022-11-28T00:00:00+00:00", - "dateOfLastModification": "2024-08-30T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -22,7 +22,6 @@ ], "seoDescription": "Implicitly differentiating the the solution of a VQA in PennyLane.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_implicit_diff_susceptibility", "references": [ { "id": "Paradis2004", @@ -96,4 +95,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_initial_state_preparation.metadata.json b/demonstrations/tutorial_initial_state_preparation.metadata.json index 4e949fd9f7..9ee85aaabf 100644 --- a/demonstrations/tutorial_initial_state_preparation.metadata.json +++ b/demonstrations/tutorial_initial_state_preparation.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2023-10-20T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Chemistry" ], @@ -23,7 +23,6 @@ ], "seoDescription": "Prepare initial states for quantum algorithms from output of traditional quantum chemistry methods.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_initial_state_preparation", "references": [ ], "basedOnPapers": [], @@ -40,4 +39,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_intro_amplitude_amplification.metadata.json b/demonstrations/tutorial_intro_amplitude_amplification.metadata.json index 53feb9c966..a9b38146ff 100644 --- a/demonstrations/tutorial_intro_amplitude_amplification.metadata.json +++ b/demonstrations/tutorial_intro_amplitude_amplification.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2024-05-07T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Computing", "Algorithms" @@ -27,7 +27,6 @@ ], "seoDescription": "Learn Amplitude Amplification from scratch and how to use fixed-point quantum search", "doi": "", - "canonicalURL": "/qml/demos/tutorial_intro_amplitude_amplification", "references": [ { "id": "ampamp", @@ -83,4 +82,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_intro_qrom.metadata.json b/demonstrations/tutorial_intro_qrom.metadata.json index f004331990..9fe232c5f7 100644 --- a/demonstrations/tutorial_intro_qrom.metadata.json +++ b/demonstrations/tutorial_intro_qrom.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2024-09-18T00:00:00+00:00", - "dateOfLastModification": "2024-09-18T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Algorithms", "Quantum Computing" @@ -27,7 +27,6 @@ ], "seoDescription": "Learn how to enter data into a quantum computer with a quantum read-only memory (QROM) approach.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_intro_qrom", "references": [ { "id": "unary", @@ -79,4 +78,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_intro_qsvt.metadata.json b/demonstrations/tutorial_intro_qsvt.metadata.json index 8011c8a7fa..80af77e7bc 100644 --- a/demonstrations/tutorial_intro_qsvt.metadata.json +++ b/demonstrations/tutorial_intro_qsvt.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2023-05-23T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Algorithms", "Quantum Computing" @@ -24,7 +24,6 @@ ], "seoDescription": "Master the basics of the quantum singular value transformation", "doi": "", - "canonicalURL": "/qml/demos/tutorial_intro_qsvt", "references": [ { "id": "qsvt", @@ -66,4 +65,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_isingmodel_PyTorch.metadata.json b/demonstrations/tutorial_isingmodel_PyTorch.metadata.json index e19aa2bc5a..7f84d908fc 100644 --- a/demonstrations/tutorial_isingmodel_PyTorch.metadata.json +++ b/demonstrations/tutorial_isingmodel_PyTorch.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2019-10-16T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -19,7 +19,6 @@ ], "seoDescription": "This demonstration uses the PyTorch interface of PennyLane to optimize a 3-qubit Ising model.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_isingmodel_PyTorch", "references": [ { "id": "Schuld2018", diff --git a/demonstrations/tutorial_jax_transformations.metadata.json b/demonstrations/tutorial_jax_transformations.metadata.json index 143e9e3a5b..d2767d9069 100644 --- a/demonstrations/tutorial_jax_transformations.metadata.json +++ b/demonstrations/tutorial_jax_transformations.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2021-04-12T00:00:00+00:00", - "dateOfLastModification": "2024-08-30T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Devices and Performance" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Learn how to use JAX with PennyLane.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_jax_transformations", "references": [], "basedOnPapers": [], "referencedByPapers": [], @@ -40,4 +39,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_kernel_based_training.metadata.json b/demonstrations/tutorial_kernel_based_training.metadata.json index 38ba9ee667..9b3434187e 100644 --- a/demonstrations/tutorial_kernel_based_training.metadata.json +++ b/demonstrations/tutorial_kernel_based_training.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2021-02-03T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Train a quantum machine learning model based on the idea of quantum kernels.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_kernel_based_training", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/tutorial_kernels_module.metadata.json b/demonstrations/tutorial_kernels_module.metadata.json index 71eb88b6e3..fba0d5748f 100644 --- a/demonstrations/tutorial_kernels_module.metadata.json +++ b/demonstrations/tutorial_kernels_module.metadata.json @@ -21,7 +21,7 @@ } ], "dateOfPublication": "2021-06-24T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning" ], @@ -34,7 +34,6 @@ ], "seoDescription": "Kernels and alignment training with Pennylane.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_kernels_module", "references": [ { "id": "Training_QEKs", diff --git a/demonstrations/tutorial_lcu_blockencoding.metadata.json b/demonstrations/tutorial_lcu_blockencoding.metadata.json index 93154219d6..d9f2d1c57a 100644 --- a/demonstrations/tutorial_lcu_blockencoding.metadata.json +++ b/demonstrations/tutorial_lcu_blockencoding.metadata.json @@ -12,7 +12,7 @@ } ], "dateOfPublication": "2023-10-25T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Algorithms", "Quantum Computing" @@ -30,7 +30,6 @@ ], "seoDescription": "Master the basics of LCUs and their applications", "doi": "", - "canonicalURL": "/qml/demos/tutorial_lcu_blockencoding", "references": [ { "id": "qsvt", diff --git a/demonstrations/tutorial_learning_dynamics_incoherently.metadata.json b/demonstrations/tutorial_learning_dynamics_incoherently.metadata.json index 6d720568e3..7fb9cfde72 100644 --- a/demonstrations/tutorial_learning_dynamics_incoherently.metadata.json +++ b/demonstrations/tutorial_learning_dynamics_incoherently.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-08-15T00:00:00+00:00", - "dateOfLastModification": "2024-08-15T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning", "How-to" @@ -24,7 +24,6 @@ ], "seoDescription": "Learn how to reproduce an unknown quantum process with classical shadow measurements", "doi": "", - "canonicalURL": "/qml/demos/tutorial_learning_dynamics_incoherently", "references": [ { "id": "jerbi2023power", @@ -55,12 +54,12 @@ { "type": "demonstration", "id": "tutorial_classical_shadows", - "weight": 1.0 + "weight": 1.0 }, { "type": "demonstration", "id": "tutorial_variational_classifier", - "weight": 1.0 + "weight": 1.0 } ] } diff --git a/demonstrations/tutorial_learning_few_data.metadata.json b/demonstrations/tutorial_learning_few_data.metadata.json index 7fb254adfd..e3392b024b 100644 --- a/demonstrations/tutorial_learning_few_data.metadata.json +++ b/demonstrations/tutorial_learning_few_data.metadata.json @@ -12,7 +12,7 @@ } ], "dateOfPublication": "2022-08-29T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning" ], @@ -25,7 +25,6 @@ ], "seoDescription": "Generalization of quantum machine learning models.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_learning_few_data", "references": [ { "id": "CaroGeneralization", diff --git a/demonstrations/tutorial_learning_from_experiments.metadata.json b/demonstrations/tutorial_learning_from_experiments.metadata.json index 0c4563082e..098d5255a1 100644 --- a/demonstrations/tutorial_learning_from_experiments.metadata.json +++ b/demonstrations/tutorial_learning_from_experiments.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2022-04-18T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Learn how quantum memory can boost quantum machine learning algorithms", "doi": "", - "canonicalURL": "/qml/demos/tutorial_learning_from_experiments", "references": [ { "id": "Huang2021", diff --git a/demonstrations/tutorial_learningshallow.metadata.json b/demonstrations/tutorial_learningshallow.metadata.json index b7e58d889d..a7718c5ea3 100644 --- a/demonstrations/tutorial_learningshallow.metadata.json +++ b/demonstrations/tutorial_learningshallow.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-01-24T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization", "Quantum Computing", @@ -25,7 +25,6 @@ ], "seoDescription": "Learn how to do circuit sewing with local inversions, which play a crucial role in learning shallow quantum circuits", "doi": "", - "canonicalURL": "/qml/demos/tutorial_learningshallow", "references": [ { "id": "Huang", @@ -84,4 +83,3 @@ } ] } - diff --git a/demonstrations/tutorial_liealgebra.metadata.json b/demonstrations/tutorial_liealgebra.metadata.json index 5b7082dbde..6e9e6edfc2 100644 --- a/demonstrations/tutorial_liealgebra.metadata.json +++ b/demonstrations/tutorial_liealgebra.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-02-27T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Computing", "Getting Started" @@ -24,7 +24,6 @@ ], "seoDescription": "A gentle introduction to Lie theory covering the basics of Lie algebras and Lie groups in the context of quantum computing.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_liealgebra", "references": [ { "id": "Wiersema", @@ -114,4 +113,3 @@ } ] } - diff --git a/demonstrations/tutorial_liesim.metadata.json b/demonstrations/tutorial_liesim.metadata.json index ab538c7aa8..f3d75d959d 100644 --- a/demonstrations/tutorial_liesim.metadata.json +++ b/demonstrations/tutorial_liesim.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-06-07T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Computing", "Getting Started" @@ -24,7 +24,6 @@ ], "seoDescription": "A differentiable implementation of g-sim in PennyLane", "doi": "", - "canonicalURL": "/qml/demos/tutorial_liesim", "references": [ { "id": "Wiersema", diff --git a/demonstrations/tutorial_liesim_extension.metadata.json b/demonstrations/tutorial_liesim_extension.metadata.json index b223f37577..c91f1393be 100644 --- a/demonstrations/tutorial_liesim_extension.metadata.json +++ b/demonstrations/tutorial_liesim_extension.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-06-18T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Computing", "Quantum Machine Learning" @@ -24,7 +24,6 @@ ], "seoDescription": "(g + P)-sim: Extending g-sim by non-DLA observables and gates", "doi": "", - "canonicalURL": "/qml/demos/tutorial_liesim_extension", "references": [ { "id": "Wiersema", diff --git a/demonstrations/tutorial_local_cost_functions.metadata.json b/demonstrations/tutorial_local_cost_functions.metadata.json index 91b2ec37d6..70b8c7b084 100644 --- a/demonstrations/tutorial_local_cost_functions.metadata.json +++ b/demonstrations/tutorial_local_cost_functions.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2020-09-09T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Local cost functions are cost formulations for variational quantum circuits that are more robust to barren plateaus.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_local_cost_functions", "references": [ { "id": "Cerezo2020", diff --git a/demonstrations/tutorial_magic_state_distillation.metadata.json b/demonstrations/tutorial_magic_state_distillation.metadata.json index 731d6d160c..99f65e1d10 100644 --- a/demonstrations/tutorial_magic_state_distillation.metadata.json +++ b/demonstrations/tutorial_magic_state_distillation.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-04-26T00:00:00+00:00", - "dateOfLastModification": "2024-08-30T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Algorithms", "Quantum Computing" @@ -24,7 +24,6 @@ ], "seoDescription": "Use PennyLane, Catalyst, and QJIT to improve the fidelity of magic T-states.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_magic_state_distillation", "references": [ { "id": "bravyi2005", diff --git a/demonstrations/tutorial_mapping.metadata.json b/demonstrations/tutorial_mapping.metadata.json index d4a607a0ba..0b8bc0bebd 100644 --- a/demonstrations/tutorial_mapping.metadata.json +++ b/demonstrations/tutorial_mapping.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-05-06T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Algorithms", "Quantum Computing", @@ -25,7 +25,6 @@ ], "seoDescription": "Learn how to map fermionic operators to qubit operators", "doi": "", - "canonicalURL": "/qml/demos/tutorial_mapping", "references": [ { "id": "Tranter", diff --git a/demonstrations/tutorial_mbqc.metadata.json b/demonstrations/tutorial_mbqc.metadata.json index 3af3885fab..ca063f1f5f 100644 --- a/demonstrations/tutorial_mbqc.metadata.json +++ b/demonstrations/tutorial_mbqc.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2022-12-05T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Hardware", "Quantum Computing" @@ -23,7 +23,6 @@ ], "seoDescription": "Learn about measurement-based quantum computation", "doi": "", - "canonicalURL": "/qml/demos/tutorial_mbqc", "references": [ { "id": "OneWay2001", diff --git a/demonstrations/tutorial_mcm_introduction.metadata.json b/demonstrations/tutorial_mcm_introduction.metadata.json index 586633d57e..7292c7d447 100644 --- a/demonstrations/tutorial_mcm_introduction.metadata.json +++ b/demonstrations/tutorial_mcm_introduction.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-05-10T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Getting Started", "Quantum Computing" @@ -24,7 +24,6 @@ ], "seoDescription": "Learn the basics of mid-circuit measurements and how to use them in PennyLane.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_mcm_introduction", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/tutorial_measurement_optimize.metadata.json b/demonstrations/tutorial_measurement_optimize.metadata.json index 5e6bfea7cc..597ab1dfff 100644 --- a/demonstrations/tutorial_measurement_optimize.metadata.json +++ b/demonstrations/tutorial_measurement_optimize.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2021-01-18T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Chemistry" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Optimize and reduce the number of measurements required to evaluate a variational algorithm cost function.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_measurement_optimize", "references": [ { "id": "peruzzo2014", diff --git a/demonstrations/tutorial_mitigation_advantage.metadata.json b/demonstrations/tutorial_mitigation_advantage.metadata.json index d1d49ba831..612599db9b 100644 --- a/demonstrations/tutorial_mitigation_advantage.metadata.json +++ b/demonstrations/tutorial_mitigation_advantage.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2023-06-16T00:00:00+00:00", - "dateOfLastModification": "2024-09-03T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Hardware", "Quantum Computing" @@ -24,7 +24,6 @@ ], "seoDescription": "Using IBM's 127-qubit quantum computer to simulate deep quantum circuits using Zero Noise Extrapolation", "doi": "", - "canonicalURL": "/qml/demos/tutorial_mitigation_advantage", "references": [ { "id": "ibm", @@ -70,4 +69,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_mol_geo_opt.metadata.json b/demonstrations/tutorial_mol_geo_opt.metadata.json index f873efb255..c876927c3d 100644 --- a/demonstrations/tutorial_mol_geo_opt.metadata.json +++ b/demonstrations/tutorial_mol_geo_opt.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2021-06-30T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Chemistry" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Find the equilibrium geometry of a molecule", "doi": "", - "canonicalURL": "/qml/demos/tutorial_mol_geo_opt", "references": [ { "id": "jensenbook", diff --git a/demonstrations/tutorial_mps.metadata.json b/demonstrations/tutorial_mps.metadata.json index b31eacca34..73c88e90a5 100644 --- a/demonstrations/tutorial_mps.metadata.json +++ b/demonstrations/tutorial_mps.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-09-29T00:00:00+00:00", - "dateOfLastModification": "2024-09-29T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Computing", "Algorithms", @@ -25,7 +25,6 @@ ], "seoDescription": "What is a matrix product state (MPS)? Here is all you need to know about MPS from a quantum computation and quantum simulation perspective.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_mps", "references": [ { "id": "Baiardi", diff --git a/demonstrations/tutorial_multiclass_classification.metadata.json b/demonstrations/tutorial_multiclass_classification.metadata.json index aef243c2a2..a4049ca48d 100644 --- a/demonstrations/tutorial_multiclass_classification.metadata.json +++ b/demonstrations/tutorial_multiclass_classification.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2020-04-09T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": ["Algorithms"], "tags": [], "previewImages": [ @@ -17,7 +17,6 @@ ], "seoDescription": "Using PyTorch to implement a multiclass quantum variational classifier on MNIST data.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_multiclass_classification", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/tutorial_neutral_atoms.metadata.json b/demonstrations/tutorial_neutral_atoms.metadata.json index e53817061a..b443ba3fa8 100644 --- a/demonstrations/tutorial_neutral_atoms.metadata.json +++ b/demonstrations/tutorial_neutral_atoms.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2023-05-30T00:00:00+00:00", - "dateOfLastModification": "2024-08-30T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Hardware", "Quantum Computing" @@ -24,7 +24,6 @@ ], "seoDescription": "Learn how neutral atom quantum devices work using code.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_neutral_atoms", "references": [ { "id": "Aquila2022", @@ -133,4 +132,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_noisy_circuit_optimization.metadata.json b/demonstrations/tutorial_noisy_circuit_optimization.metadata.json index f41fc2a747..158d1e9594 100644 --- a/demonstrations/tutorial_noisy_circuit_optimization.metadata.json +++ b/demonstrations/tutorial_noisy_circuit_optimization.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2020-06-01T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Devices and Performance" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Learn how noise can affect the optimization and training of quantum computations.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_noisy_circuit_optimization", "references": [ { "id": "arute2019", diff --git a/demonstrations/tutorial_noisy_circuits.metadata.json b/demonstrations/tutorial_noisy_circuits.metadata.json index 3cf4ac34c0..92522adae3 100644 --- a/demonstrations/tutorial_noisy_circuits.metadata.json +++ b/demonstrations/tutorial_noisy_circuits.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2021-02-22T00:00:00+00:00", - "dateOfLastModification": "2024-09-03T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Getting Started" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Learn how to simulate noisy quantum circuits", "doi": "", - "canonicalURL": "/qml/demos/tutorial_noisy_circuits", "references": [ { "id": "johannes", diff --git a/demonstrations/tutorial_odegen.metadata.json b/demonstrations/tutorial_odegen.metadata.json index 9ccfef9fa6..ab2eb2a794 100644 --- a/demonstrations/tutorial_odegen.metadata.json +++ b/demonstrations/tutorial_odegen.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2023-12-12T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization", "Quantum Computing", @@ -25,7 +25,6 @@ ], "seoDescription": "Learn how to compute analytic gradients of pulse programs on quantum hardware", "doi": "", - "canonicalURL": "/qml/demos/tutorial_odegen", "references": [ { "id": "Kottmann", @@ -117,4 +116,3 @@ } ] } - diff --git a/demonstrations/tutorial_optimal_control.metadata.json b/demonstrations/tutorial_optimal_control.metadata.json index f26a39b386..62597e4f5d 100644 --- a/demonstrations/tutorial_optimal_control.metadata.json +++ b/demonstrations/tutorial_optimal_control.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2023-08-08T00:00:00+00:00", - "dateOfLastModification": "2024-09-04T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization", "Quantum Computing", @@ -25,7 +25,6 @@ ], "seoDescription": "Learn how to optimize pulse programs to obtain digital gates", "doi": "", - "canonicalURL": "/qml/demos/tutorial_optimal_control", "references": [ { "id": "KingmaBa14", @@ -93,4 +92,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_pasqal.metadata.json b/demonstrations/tutorial_pasqal.metadata.json index 6519606a8e..f5decd0ac3 100644 --- a/demonstrations/tutorial_pasqal.metadata.json +++ b/demonstrations/tutorial_pasqal.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2020-10-13T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Hardware", "Quantum Computing" @@ -20,7 +20,6 @@ ], "seoDescription": "Neutral atom quantum devices allow you to place qubits within interesting three-dimensional configurations.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_pasqal", "references": [ { "id": "barredo2017", diff --git a/demonstrations/tutorial_phase_kickback.metadata.json b/demonstrations/tutorial_phase_kickback.metadata.json index 913a6cf881..063bb9e26a 100644 --- a/demonstrations/tutorial_phase_kickback.metadata.json +++ b/demonstrations/tutorial_phase_kickback.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2023-08-01T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Getting Started", "Algorithms", @@ -25,7 +25,6 @@ ], "seoDescription": "Use phase kickback to create an unbreakable quantum lock", "doi": "", - "canonicalURL": "/qml/demos/tutorial_phase_kickback", "references": [], "basedOnPapers": [], "referencedByPapers": [], @@ -36,4 +35,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_photonics.metadata.json b/demonstrations/tutorial_photonics.metadata.json index f5adf6a523..9c194ba650 100644 --- a/demonstrations/tutorial_photonics.metadata.json +++ b/demonstrations/tutorial_photonics.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2022-05-31T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Hardware", "Quantum Computing" @@ -20,7 +20,6 @@ ], "seoDescription": "Learn how photonic quantum computers work through code", "doi": "", - "canonicalURL": "/qml/demos/tutorial_photonics", "references": [ { "id": "DiVincenzo2000", diff --git a/demonstrations/tutorial_post-variational_quantum_neural_networks.metadata.json b/demonstrations/tutorial_post-variational_quantum_neural_networks.metadata.json index b98fd1aec4..ef4b4e6a61 100644 --- a/demonstrations/tutorial_post-variational_quantum_neural_networks.metadata.json +++ b/demonstrations/tutorial_post-variational_quantum_neural_networks.metadata.json @@ -28,7 +28,6 @@ ], "seoDescription": "Learn about post-variational quantum neural networks", "doi": "", - "canonicalURL": "/qml/demos/tutorial_post-variational_quantum_neural_networks", "references": [ { "id": "cerezo2021variational", @@ -132,4 +131,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_pulse_programming101.metadata.json b/demonstrations/tutorial_pulse_programming101.metadata.json index c6ba767926..7801031d1f 100644 --- a/demonstrations/tutorial_pulse_programming101.metadata.json +++ b/demonstrations/tutorial_pulse_programming101.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2023-03-08T00:00:00+00:00", - "dateOfLastModification": "2024-09-03T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Hardware", "Quantum Computing" @@ -24,7 +24,6 @@ ], "seoDescription": "Simulating differentialble pulse programs in PennyLane with qubits", "doi": "", - "canonicalURL": "/qml/demos/tutorial_pulse_programming101", "references": [ { "id": "Mitei", @@ -75,4 +74,4 @@ "basedOnPapers": [], "referencedByPapers": [], "relatedContent": [] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_qaoa_intro.metadata.json b/demonstrations/tutorial_qaoa_intro.metadata.json index d222bf4b82..f362d99d5f 100644 --- a/demonstrations/tutorial_qaoa_intro.metadata.json +++ b/demonstrations/tutorial_qaoa_intro.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2020-11-18T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Learn how to implement QAOA with PennyLane", "doi": "", - "canonicalURL": "/qml/demos/tutorial_qaoa_intro", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/tutorial_qaoa_maxcut.metadata.json b/demonstrations/tutorial_qaoa_maxcut.metadata.json index d5af72d47b..cbb2bc6bcf 100644 --- a/demonstrations/tutorial_qaoa_maxcut.metadata.json +++ b/demonstrations/tutorial_qaoa_maxcut.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2019-10-11T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Implementing the quantum approximate optimization algorithm using PennyLane to solve the MaxCut problem.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_qaoa_maxcut", "references": [], "basedOnPapers": [ "10.48550/arXiv.1411.4028" diff --git a/demonstrations/tutorial_qcbm.metadata.json b/demonstrations/tutorial_qcbm.metadata.json index 4b94d8ac8d..d88d2ab36b 100644 --- a/demonstrations/tutorial_qcbm.metadata.json +++ b/demonstrations/tutorial_qcbm.metadata.json @@ -7,7 +7,7 @@ } ], "dateOfPublication": "2024-05-22T00:00:00+00:00", - "dateOfLastModification": "2024-08-12T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": ["Quantum Machine Learning"], "tags": [], "previewImages": [ @@ -22,7 +22,6 @@ ], "seoDescription": "Learn how to use the Quantum Circuit Born Machines (QCBMs).", "doi": "", - "canonicalURL": "/qml/demos/tutorial_qcbm", "references": [ { "id": "Liu", @@ -93,4 +92,4 @@ } ], "hardware": [] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_qchem_external.metadata.json b/demonstrations/tutorial_qchem_external.metadata.json index 335a69ae99..eb5d12152d 100644 --- a/demonstrations/tutorial_qchem_external.metadata.json +++ b/demonstrations/tutorial_qchem_external.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2023-01-03T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Chemistry", "Devices and Performance" ], @@ -23,7 +23,6 @@ ], "seoDescription": "Learn how to integrate external quantum chemistry libraries with PennyLane.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_qchem_external", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/tutorial_qft.metadata.json b/demonstrations/tutorial_qft.metadata.json index 7338af71bf..d99c9dd532 100644 --- a/demonstrations/tutorial_qft.metadata.json +++ b/demonstrations/tutorial_qft.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-04-16T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Algorithms", "Quantum Computing" @@ -24,9 +24,8 @@ ], "seoDescription": "Master the basics of the quantum fourier transform", "doi": "", - "canonicalURL": "/qml/demos/tutorial_qft", "references": [], "basedOnPapers": [], "referencedByPapers": [], "relatedContent": [] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_qft_arithmetics.metadata.json b/demonstrations/tutorial_qft_arithmetics.metadata.json index ec1ca35416..b772780baa 100644 --- a/demonstrations/tutorial_qft_arithmetics.metadata.json +++ b/demonstrations/tutorial_qft_arithmetics.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2022-11-07T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Getting Started", "Algorithms", "Quantum Computing" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Learn how to use the quantum Fourier transform (QFT) to do basic arithmetic", "doi": "", - "canonicalURL": "/qml/demos/tutorial_qft_arithmetics", "references": [ { "id": "Draper2000", diff --git a/demonstrations/tutorial_qgrnn.metadata.json b/demonstrations/tutorial_qgrnn.metadata.json index db4d9f5f12..5dd9822d16 100644 --- a/demonstrations/tutorial_qgrnn.metadata.json +++ b/demonstrations/tutorial_qgrnn.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2020-07-27T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Using a quantum graph recurrent neural network to learn quantum dynamics.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_qgrnn", "references": [ { "id": "Verdon2019", diff --git a/demonstrations/tutorial_qnn_module_tf.metadata.json b/demonstrations/tutorial_qnn_module_tf.metadata.json index cbc30864f2..36a7aab856 100644 --- a/demonstrations/tutorial_qnn_module_tf.metadata.json +++ b/demonstrations/tutorial_qnn_module_tf.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2020-11-02T00:00:00+00:00", - "dateOfLastModification": "2024-08-14T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Devices and Performance", "Quantum Machine Learning" @@ -20,7 +20,6 @@ ], "seoDescription": "Learn how to create hybrid ML models in PennyLane using Keras", "doi": "", - "canonicalURL": "/qml/demos/tutorial_qnn_module_tf", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/tutorial_qnn_module_torch.metadata.json b/demonstrations/tutorial_qnn_module_torch.metadata.json index c2e450df0d..bfd569d229 100644 --- a/demonstrations/tutorial_qnn_module_torch.metadata.json +++ b/demonstrations/tutorial_qnn_module_torch.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2020-11-02T00:00:00+00:00", - "dateOfLastModification": "2024-08-14T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Devices and Performance", "Quantum Machine Learning" @@ -20,7 +20,6 @@ ], "seoDescription": "Learn how to create hybrid ML models in PennyLane using Torch", "doi": "", - "canonicalURL": "/qml/demos/tutorial_qnn_module_torch", "references": [], "basedOnPapers": [], "referencedByPapers": [], @@ -31,4 +30,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_qnn_multivariate_regression.metadata.json b/demonstrations/tutorial_qnn_multivariate_regression.metadata.json index b79fd1bf23..2087296497 100644 --- a/demonstrations/tutorial_qnn_multivariate_regression.metadata.json +++ b/demonstrations/tutorial_qnn_multivariate_regression.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2024-10-01T00:00:00+00:00", - "dateOfLastModification": "2024-10-01T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Computing", "Quantum Machine Learning", @@ -28,7 +28,6 @@ ], "seoDescription": "Learn to use a quantum neural network to fit a multivariate function.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_qnn_multivariate_regression", "references": [ { "id": "schuld", diff --git a/demonstrations/tutorial_qpe.metadata.json b/demonstrations/tutorial_qpe.metadata.json index 6a18a1fa3e..512fac8cab 100644 --- a/demonstrations/tutorial_qpe.metadata.json +++ b/demonstrations/tutorial_qpe.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2024-01-30T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Algorithms", "Quantum Computing" @@ -27,7 +27,6 @@ ], "seoDescription": "Master the basics of the quantum phase estimation", "doi": "", - "canonicalURL": "/qml/demos/tutorial_qpe", "references": [ { "id": "qpe", @@ -57,4 +56,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_qsvt_hardware.metadata.json b/demonstrations/tutorial_qsvt_hardware.metadata.json index 8dc8163623..acc4370c21 100644 --- a/demonstrations/tutorial_qsvt_hardware.metadata.json +++ b/demonstrations/tutorial_qsvt_hardware.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-09-18T00:00:00+00:00", - "dateOfLastModification": "2024-09-18T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Algorithms", "Quantum Computing", @@ -25,7 +25,6 @@ ], "seoDescription": "Learn how to implement QSVT on hardware.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_qsvt_hardware", "references": [ ], "basedOnPapers": [], @@ -43,4 +42,4 @@ } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_quantum_analytic_descent.metadata.json b/demonstrations/tutorial_quantum_analytic_descent.metadata.json index 257f9ec7a9..a7ccf5c09b 100644 --- a/demonstrations/tutorial_quantum_analytic_descent.metadata.json +++ b/demonstrations/tutorial_quantum_analytic_descent.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2021-06-30T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -22,7 +22,6 @@ ], "seoDescription": "Implement the Quantum analytic descent algorithm for VQE.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_quantum_analytic_descent", "references": [ { "id": "QAD", diff --git a/demonstrations/tutorial_quantum_chemistry.metadata.json b/demonstrations/tutorial_quantum_chemistry.metadata.json index e580d0a2a2..3d481d3440 100644 --- a/demonstrations/tutorial_quantum_chemistry.metadata.json +++ b/demonstrations/tutorial_quantum_chemistry.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2020-08-02T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Chemistry" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Learn how to build electronic Hamiltonians of molecules.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_quantum_chemistry", "references": [ { "id": "yudong2019", diff --git a/demonstrations/tutorial_quantum_circuit_cutting.metadata.json b/demonstrations/tutorial_quantum_circuit_cutting.metadata.json index 1ebb2134ea..26b07e3392 100644 --- a/demonstrations/tutorial_quantum_circuit_cutting.metadata.json +++ b/demonstrations/tutorial_quantum_circuit_cutting.metadata.json @@ -12,7 +12,7 @@ } ], "dateOfPublication": "2022-09-02T00:00:00+00:00", - "dateOfLastModification": "2024-08-28T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Algorithms", "Quantum Computing" ], @@ -25,7 +25,6 @@ ], "seoDescription": "We dive into two algorithms for splitting a large quantum circuit into smaller ones.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_quantum_circuit_cutting", "references": [ { "id": "Peng2019", diff --git a/demonstrations/tutorial_quantum_dropout.metadata.json b/demonstrations/tutorial_quantum_dropout.metadata.json index 00435ceb41..78fec10d2b 100644 --- a/demonstrations/tutorial_quantum_dropout.metadata.json +++ b/demonstrations/tutorial_quantum_dropout.metadata.json @@ -7,7 +7,7 @@ } ], "dateOfPublication": "2024-03-12T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": ["Quantum Machine Learning"], "tags": ["QNN", "overfitting", "dropout", "regularization"], "previewImages": [ @@ -22,7 +22,6 @@ ], "seoDescription": "Learn to avoid overfitting employing quantum dropout", "doi": "", - "canonicalURL": "/qml/demos/tutorial_quantum_dropout", "references": [ { "id": "dropout", @@ -58,4 +57,4 @@ "referencedByPapers": [], "relatedContent": [], "hardware": [] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_quantum_gans.metadata.json b/demonstrations/tutorial_quantum_gans.metadata.json index 7ae99875e4..ad8e932038 100644 --- a/demonstrations/tutorial_quantum_gans.metadata.json +++ b/demonstrations/tutorial_quantum_gans.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2022-02-01T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Explore quantum GANs to generate hand-written digits of zero", "doi": "", - "canonicalURL": "/qml/demos/tutorial_quantum_gans", "references": [ { "id": "goodfellow2014", diff --git a/demonstrations/tutorial_quantum_metrology.metadata.json b/demonstrations/tutorial_quantum_metrology.metadata.json index 684fa8c6ec..43270bbd94 100644 --- a/demonstrations/tutorial_quantum_metrology.metadata.json +++ b/demonstrations/tutorial_quantum_metrology.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2020-06-18T00:00:00+00:00", - "dateOfLastModification": "2024-08-12T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Using a variational quantum algorithm to optimize a quantum sensing protocol.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_quantum_metrology", "references": [ { "id": "meyer2020", diff --git a/demonstrations/tutorial_quantum_natural_gradient.metadata.json b/demonstrations/tutorial_quantum_natural_gradient.metadata.json index 06dddee6aa..5f0439e02f 100644 --- a/demonstrations/tutorial_quantum_natural_gradient.metadata.json +++ b/demonstrations/tutorial_quantum_natural_gradient.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2019-10-11T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -19,7 +19,6 @@ ], "seoDescription": "The quantum natural gradient method can achieve faster convergence for quantum machine learning problems by taking into account the intrinsic geometry of qubits.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_quantum_natural_gradient", "references": [ { "id": "Amari1998", diff --git a/demonstrations/tutorial_quantum_transfer_learning.metadata.json b/demonstrations/tutorial_quantum_transfer_learning.metadata.json index b38f758c58..0cc03cce27 100644 --- a/demonstrations/tutorial_quantum_transfer_learning.metadata.json +++ b/demonstrations/tutorial_quantum_transfer_learning.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2019-12-19T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Combine PyTorch and PennyLane to train a hybrid quantum-classical image classifier using transfer learning.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_quantum_transfer_learning", "references": [ { "id": "Mari2019", diff --git a/demonstrations/tutorial_quanvolution.metadata.json b/demonstrations/tutorial_quanvolution.metadata.json index f3cfc30781..b24840ac75 100644 --- a/demonstrations/tutorial_quanvolution.metadata.json +++ b/demonstrations/tutorial_quanvolution.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2020-03-24T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Train a quantum convolutional neural network to classify MNIST images.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_quanvolution", "references": [ { "id": "Henderson2019", diff --git a/demonstrations/tutorial_qubit_rotation.metadata.json b/demonstrations/tutorial_qubit_rotation.metadata.json index add65b228a..a8973dad85 100644 --- a/demonstrations/tutorial_qubit_rotation.metadata.json +++ b/demonstrations/tutorial_qubit_rotation.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2019-10-11T00:00:00+00:00", - "dateOfLastModification": "2024-09-04T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Getting Started" ], @@ -19,7 +19,6 @@ ], "seoDescription": "To see how PennyLane allows the easy construction and optimization of quantum functions, let's consider the 'hello world' of QML: qubit rotation.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_qubit_rotation", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/tutorial_qubit_tapering.metadata.json b/demonstrations/tutorial_qubit_tapering.metadata.json index c25c20121f..d65cec6324 100644 --- a/demonstrations/tutorial_qubit_tapering.metadata.json +++ b/demonstrations/tutorial_qubit_tapering.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2022-05-16T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Chemistry" ], @@ -22,7 +22,6 @@ ], "seoDescription": "Learn how to taper off qubits", "doi": "", - "canonicalURL": "/qml/demos/tutorial_qubit_tapering", "references": [ { "id": "bravyi2017", diff --git a/demonstrations/tutorial_qubitization.metadata.json b/demonstrations/tutorial_qubitization.metadata.json index e9aabdd9f5..6ec14b591f 100644 --- a/demonstrations/tutorial_qubitization.metadata.json +++ b/demonstrations/tutorial_qubitization.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2024-09-09T00:00:00+00:00", - "dateOfLastModification": "2024-09-09T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Computing", "Algorithms" @@ -27,7 +27,6 @@ ], "seoDescription": "Learn how to use, visualize and apply qubitization, a block-encoding technique in quantum computing.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_qubitization", "references": [], "basedOnPapers": [], "referencedByPapers": [], @@ -48,4 +47,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_qutrits_bernstein_vazirani.metadata.json b/demonstrations/tutorial_qutrits_bernstein_vazirani.metadata.json index 6cfd5e67e6..2dbf11c48a 100644 --- a/demonstrations/tutorial_qutrits_bernstein_vazirani.metadata.json +++ b/demonstrations/tutorial_qutrits_bernstein_vazirani.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2023-05-09T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Algorithms", "Quantum Computing" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Learn how to interpret the Bernstein–Vazirani algorithm with qutrits", "doi": "", - "canonicalURL": "/qml/demos/tutorial_qutrits_bernstein_vazirani", "references": [ { "id": "bv", @@ -46,4 +45,4 @@ "referencedByPapers": [], "relatedContent": [ ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_resource_estimation.metadata.json b/demonstrations/tutorial_resource_estimation.metadata.json index 3ba43a2135..9bc9fc0efe 100644 --- a/demonstrations/tutorial_resource_estimation.metadata.json +++ b/demonstrations/tutorial_resource_estimation.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2022-11-21T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Chemistry" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Learn how to estimate the number of qubits and gates needed to implement quantum algorithms", "doi": "", - "canonicalURL": "/qml/demos/tutorial_resource_estimation", "references": [ { "id": "vonburg2021", diff --git a/demonstrations/tutorial_rl_pulse.metadata.json b/demonstrations/tutorial_rl_pulse.metadata.json index 0e59a897ba..da285f6a7e 100644 --- a/demonstrations/tutorial_rl_pulse.metadata.json +++ b/demonstrations/tutorial_rl_pulse.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-04-09T00:00:00+00:00", - "dateOfLastModification": "2024-09-04T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Getting Started", "Optimization", @@ -25,7 +25,6 @@ ], "seoDescription": "Learn how to calibrate quantum computers with reinforcement learning", "doi": "", - "canonicalURL": "/qml/demos/tutorial_rl_pulse", "references": [ { "id": "BaumPRXQ21", @@ -124,4 +123,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_rosalin.metadata.json b/demonstrations/tutorial_rosalin.metadata.json index e2a10f8a0d..c2e840380e 100644 --- a/demonstrations/tutorial_rosalin.metadata.json +++ b/demonstrations/tutorial_rosalin.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2020-05-19T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -19,7 +19,6 @@ ], "seoDescription": "The Rosalin optimizer uses a measurement-frugal optimization strategy to minimize the number of times a quantum computer is accessed.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_rosalin", "references": [ { "id": "arrasmith2020", diff --git a/demonstrations/tutorial_rotoselect.metadata.json b/demonstrations/tutorial_rotoselect.metadata.json index e7708e2ebf..11381942df 100644 --- a/demonstrations/tutorial_rotoselect.metadata.json +++ b/demonstrations/tutorial_rotoselect.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2019-10-16T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Applying the Rotoselect optimization algorithm to find the minimum in a variational quantum algorithm.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_rotoselect", "references": [ { "id": "Ostaszewski2019", diff --git a/demonstrations/tutorial_sc_qubits.metadata.json b/demonstrations/tutorial_sc_qubits.metadata.json index 96bd72975d..5dd68bb0ca 100644 --- a/demonstrations/tutorial_sc_qubits.metadata.json +++ b/demonstrations/tutorial_sc_qubits.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2022-03-22T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Hardware", "Quantum Computing" @@ -20,7 +20,6 @@ ], "seoDescription": "Learn about quantum computers based on superconducting qubits, developed by companies such as IBM and Google.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_sc_qubits", "references": [ { "id": "Google2019", diff --git a/demonstrations/tutorial_shadow_hamiltonian_simulation.metadata.json b/demonstrations/tutorial_shadow_hamiltonian_simulation.metadata.json index 9e540bc436..e4ede62383 100644 --- a/demonstrations/tutorial_shadow_hamiltonian_simulation.metadata.json +++ b/demonstrations/tutorial_shadow_hamiltonian_simulation.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2024-08-06T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Computing", "Algorithms" @@ -24,7 +24,6 @@ ], "seoDescription": "A user-friendly intro to the contents of shadow Hamiltonian simulation, a technique introduced by by Somma et al (arXiv:2407.21775), with a code implementation.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_shadow_hamiltonian_simulation", "references": [ { "id": "Wiersema", diff --git a/demonstrations/tutorial_spsa.metadata.json b/demonstrations/tutorial_spsa.metadata.json index e50d7b5079..82e364ef2a 100644 --- a/demonstrations/tutorial_spsa.metadata.json +++ b/demonstrations/tutorial_spsa.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2023-03-19T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -22,7 +22,6 @@ ], "seoDescription": "Use the simultaneous perturbation stochastic approximation algorithm to optimize variational circuits in PennyLane.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_spsa", "references": [ { "id": "spall_overview", @@ -88,4 +87,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/tutorial_state_preparation.metadata.json b/demonstrations/tutorial_state_preparation.metadata.json index dd2f188a56..a519c29a43 100644 --- a/demonstrations/tutorial_state_preparation.metadata.json +++ b/demonstrations/tutorial_state_preparation.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2019-10-11T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Devices and Performance" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Build and optimize a circuit to prepare arbitrary single-qubit states, including mixed states, with PyTorch and PennyLane.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_state_preparation", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/tutorial_stochastic_parameter_shift.metadata.json b/demonstrations/tutorial_stochastic_parameter_shift.metadata.json index 9e36283dce..a952a7939f 100644 --- a/demonstrations/tutorial_stochastic_parameter_shift.metadata.json +++ b/demonstrations/tutorial_stochastic_parameter_shift.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2020-05-25T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Differentiate any qubit gate with the stochastic parameter-shift rule.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_stochastic_parameter_shift", "references": [ { "id": "banchi2020", diff --git a/demonstrations/tutorial_teleportation.metadata.json b/demonstrations/tutorial_teleportation.metadata.json index ae842bd4af..e96483a6f7 100644 --- a/demonstrations/tutorial_teleportation.metadata.json +++ b/demonstrations/tutorial_teleportation.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2023-10-20T00:00:00+00:00", - "dateOfLastModification": "2024-08-12T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Getting Started", "Quantum Computing" @@ -24,7 +24,6 @@ ], "seoDescription": "Transmit arbitrary quantum states using quantum teleportation", "doi": "", - "canonicalURL": "/qml/demos/tutorial_teleportation", "references": [ { "id": "Teleportation1993", diff --git a/demonstrations/tutorial_testing_symmetry.metadata.json b/demonstrations/tutorial_testing_symmetry.metadata.json index ff0b8f24a0..84c42e81b8 100644 --- a/demonstrations/tutorial_testing_symmetry.metadata.json +++ b/demonstrations/tutorial_testing_symmetry.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2023-01-24T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Algorithms", "Quantum Computing" @@ -24,7 +24,6 @@ ], "seoDescription": "Test if a system possesses discrete symmetries", "doi": "", - "canonicalURL": "/qml/demos/tutorial_testing_symmetry", "references": [ { "id": "LaBorde2022", diff --git a/demonstrations/tutorial_tn_circuits.metadata.json b/demonstrations/tutorial_tn_circuits.metadata.json index f0dde1deb3..957950bb1c 100644 --- a/demonstrations/tutorial_tn_circuits.metadata.json +++ b/demonstrations/tutorial_tn_circuits.metadata.json @@ -15,7 +15,7 @@ } ], "dateOfPublication": "2022-03-29T00:00:00+00:00", - "dateOfLastModification": "2024-08-12T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning" ], @@ -28,7 +28,6 @@ ], "seoDescription": "This demonstration explains how to simulate tensor-network quantum circuits.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_tn_circuits", "references": [ { "id": "huggins", diff --git a/demonstrations/tutorial_toric_code.metadata.json b/demonstrations/tutorial_toric_code.metadata.json index 5d3fea9e50..a97638ad5b 100644 --- a/demonstrations/tutorial_toric_code.metadata.json +++ b/demonstrations/tutorial_toric_code.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2022-08-08T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Algorithms", "Quantum Computing" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Investigation of the toric code degenerate ground state and anyon excitations", "doi": "", - "canonicalURL": "/qml/demos/tutorial_toric_code", "references": [ { "id": "Kitaev2003", diff --git a/demonstrations/tutorial_trapped_ions.metadata.json b/demonstrations/tutorial_trapped_ions.metadata.json index 977922539a..735d188455 100644 --- a/demonstrations/tutorial_trapped_ions.metadata.json +++ b/demonstrations/tutorial_trapped_ions.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2021-11-10T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Hardware", "Quantum Computing" @@ -20,7 +20,6 @@ ], "seoDescription": "Learn all about trapped ion quantum computers, developed by companies such as IonQ and Honeywell.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_trapped_ions", "references": [ { "id": "DiVincenzo2000", diff --git a/demonstrations/tutorial_unitary_designs.metadata.json b/demonstrations/tutorial_unitary_designs.metadata.json index 94a0cb4cbe..d97b3337e7 100644 --- a/demonstrations/tutorial_unitary_designs.metadata.json +++ b/demonstrations/tutorial_unitary_designs.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2021-09-07T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning", "Quantum Computing" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Learn about designs and their uses in quantum computing.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_unitary_designs", "references": [ { "id": "Handbook", diff --git a/demonstrations/tutorial_univariate_qvr.metadata.json b/demonstrations/tutorial_univariate_qvr.metadata.json index 5b4d90db7d..b7d6b34de7 100644 --- a/demonstrations/tutorial_univariate_qvr.metadata.json +++ b/demonstrations/tutorial_univariate_qvr.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2023-02-07T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning" ], @@ -26,7 +26,6 @@ ], "seoDescription": "Learn how to quantumly detect anomalous behaviour in time series data with the help of Covalent.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_univariate_qvr", "references": [ { "id": "Baker2022", diff --git a/demonstrations/tutorial_variational_classifier.metadata.json b/demonstrations/tutorial_variational_classifier.metadata.json index 73d6ac4205..cebd93f3a7 100644 --- a/demonstrations/tutorial_variational_classifier.metadata.json +++ b/demonstrations/tutorial_variational_classifier.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2019-10-11T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Machine Learning", "Getting Started" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Use PennyLane to implement quantum circuits that can be trained from labelled data to classify new data samples.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_variational_classifier", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations/tutorial_vqe.metadata.json b/demonstrations/tutorial_vqe.metadata.json index 27c6dfe7bc..b809cec37f 100644 --- a/demonstrations/tutorial_vqe.metadata.json +++ b/demonstrations/tutorial_vqe.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2020-02-08T00:00:00+00:00", - "dateOfLastModification": "2024-08-30T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Chemistry", "Getting Started" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Find the ground state of a Hamiltonian using the variational quantum eigensolver algorithm.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_vqe", "references": [ { "id": "peruzzo2014", diff --git a/demonstrations/tutorial_vqe_qng.metadata.json b/demonstrations/tutorial_vqe_qng.metadata.json index 71f8fb6e6e..cc4be0477d 100644 --- a/demonstrations/tutorial_vqe_qng.metadata.json +++ b/demonstrations/tutorial_vqe_qng.metadata.json @@ -12,7 +12,7 @@ } ], "dateOfPublication": "2020-11-06T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -25,7 +25,6 @@ ], "seoDescription": "Accelerating variational quantum eigensolvers using quantum natural gradients in PennyLane.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_vqe_qng", "references": [ { "id": "stokes2019", diff --git a/demonstrations/tutorial_vqe_spin_sectors.metadata.json b/demonstrations/tutorial_vqe_spin_sectors.metadata.json index d8f686b4b9..e8afdd4075 100644 --- a/demonstrations/tutorial_vqe_spin_sectors.metadata.json +++ b/demonstrations/tutorial_vqe_spin_sectors.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2020-10-13T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Chemistry" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Find the lowest-energy states of a Hamiltonian in different spin sectors", "doi": "", - "canonicalURL": "/qml/demos/tutorial_vqe_spin_sectors", "references": [ { "id": "peruzzo2014", diff --git a/demonstrations/tutorial_vqe_vqd.metadata.json b/demonstrations/tutorial_vqe_vqd.metadata.json index 8627a6dfbb..cfd303ebac 100644 --- a/demonstrations/tutorial_vqe_vqd.metadata.json +++ b/demonstrations/tutorial_vqe_vqd.metadata.json @@ -9,7 +9,7 @@ } ], "dateOfPublication": "2024-08-26T00:00:00+00:00", - "dateOfLastModification": "2024-09-16T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Chemistry", "How-to" @@ -27,7 +27,6 @@ ], "seoDescription": "Learn how to use variational quantum deflation (VQD) to find the first excited state energy of the hydrogen molecule.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_vqe_vqd", "references": [ { diff --git a/demonstrations/tutorial_vqls.metadata.json b/demonstrations/tutorial_vqls.metadata.json index 496e8976b6..9669abd3d3 100644 --- a/demonstrations/tutorial_vqls.metadata.json +++ b/demonstrations/tutorial_vqls.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2019-11-04T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Implementing the variational quantum linear solver to solve a system of linear equation with a quantum device.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_vqls", "references": [ { "id": "BravoPrieto2019", diff --git a/demonstrations/tutorial_vqt.metadata.json b/demonstrations/tutorial_vqt.metadata.json index 7f5b69076d..9b284c0482 100644 --- a/demonstrations/tutorial_vqt.metadata.json +++ b/demonstrations/tutorial_vqt.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2020-07-07T00:00:00+00:00", - "dateOfLastModification": "2024-08-05T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Optimization" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Using the Variational Quantum Thermalizer to prepare the thermal state of a Heisenberg model Hamiltonian.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_vqt", "references": [ { "id": "Verdon2019", diff --git a/demonstrations/tutorial_zx_calculus.metadata.json b/demonstrations/tutorial_zx_calculus.metadata.json index 45583f260d..f646f23511 100644 --- a/demonstrations/tutorial_zx_calculus.metadata.json +++ b/demonstrations/tutorial_zx_calculus.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2023-06-06T00:00:00+00:00", - "dateOfLastModification": "2024-08-06T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Computing" ], @@ -23,7 +23,6 @@ ], "seoDescription": "Introduction to the ZX-calculus and use cases.", "doi": "", - "canonicalURL": "/qml/demos/tutorial_zx_calculus", "references": [ { "id": "Coecke", @@ -140,4 +139,4 @@ "weight": 1.0 } ] -} \ No newline at end of file +} diff --git a/demonstrations/vqe_parallel.metadata.json b/demonstrations/vqe_parallel.metadata.json index 00ce53b7a0..d27d1dd51b 100644 --- a/demonstrations/vqe_parallel.metadata.json +++ b/demonstrations/vqe_parallel.metadata.json @@ -6,7 +6,7 @@ } ], "dateOfPublication": "2020-02-14T00:00:00+00:00", - "dateOfLastModification": "2024-08-14T00:00:00+00:00", + "dateOfLastModification": "2024-10-07T00:00:00+00:00", "categories": [ "Quantum Chemistry" ], @@ -19,7 +19,6 @@ ], "seoDescription": "Using parallel QPUs to speed up the calculation of the potential energy surface of molecular Hamiltonian.", "doi": "", - "canonicalURL": "/qml/demos/vqe_parallel", "references": [], "basedOnPapers": [], "referencedByPapers": [], diff --git a/demonstrations_metadata.md b/demonstrations_metadata.md index 3f9f464f65..0aae3d7c5c 100644 --- a/demonstrations_metadata.md +++ b/demonstrations_metadata.md @@ -15,7 +15,7 @@ Below is given an example of a complete metadata file for a demonstration. "title": "Basic arithmetic with the quantum Fourier transform (QFT)", "authors": [ { - "id": "guillermo_alonso" + "username": "guillermo_alonso" } ], "dateOfPublication": "2022-11-07T00:00:00+00:00", @@ -38,7 +38,6 @@ Below is given an example of a complete metadata file for a demonstration. ], "seoDescription": "Learn how to use the quantum Fourier transform (QFT) to do basic arithmetic", "doi": "", - "canonicalURL": "/qml/demos/tutorial_qft_arithmetics", "references": [ { "id": "Draper2000", @@ -73,7 +72,7 @@ Below is given an example of a complete metadata file for a demonstration. ## Properties -The table below gives details about the fields in the metadata JSON file for version 0.1.0. +The table below gives details about the fields in the metadata JSON file for version 0.1.4. | Name | Is Required | Value Type | Description | |---|---|---|---| @@ -86,7 +85,6 @@ The table below gives details about the fields in the metadata JSON file for ver | `previewImages` | Yes | `array` of `object` | An array of the different images that can be used as previews for this demo - e.g., thumbnails, social media cards (perhaps of different aspect ratios). See below for the object structure. | | `seoDescription` | Yes | `string` | A description of the demo suitable for SEO purposes. Ideally this should be less than 150 characters, but this is not a strict limit. It should be a full, grammatically-correct sentence ending in a full stop. | | `doi` | Yes, but can be an empty string | `string` | The DOI for this demo. | -| `canonicalURL` | Yes | `url` | The canonical URL for this demo. Sometimes there might be more than one URL that points to a given page on a website. The canonical URL defines which of these should be thought of as the _primary_ or _main_ one. | | `references` | Yes | `array` of `object` | An array of the references used for this demo. See below for object structure. | | `basedOnPapers` | Yes, but can be an empty array | `array` of `string` | An array of the DOIs for the papers this demo is based on. | | `referencedByPapers` | Yes, but can be an empty array | `array` of `string` | An array of the DOIs of any papers that reference this demo. | @@ -97,8 +95,8 @@ The table below gives details about the fields in the metadata JSON file for ver | Name | Is Required | Value Type | Description | |---|---|---|---| -| `id` | Yes | `string` | The id of this author. | -| `affiliation` | No | `string` | The affiliation of this author - often the university they work at. | +| `username` | No | `string` | The username of the author's PennyLane profile. Either this field or `name` must be provided. | +| `name` | No | `string` | The full name of the author. Either this field of `username` must be provided. | ### Preview Image Object Properties @@ -118,12 +116,12 @@ The table below gives details about the fields in the metadata JSON file for ver | `year` | Yes | `string` | The year in which the paper or book was published. | | `month` | No | `string` | The month in which the paper or book was published. | | `journal` | No | `string` | The journal that the paper was published in. (Not relevant for books.) | -| `publisher` | No | `string` | The publisher of the book. (Not relevant for papers.) | +| `publisher` | No | `string` | The publisher of the book. (Not relevant for papers.) | | `doi` | No | `string` | The DOI of the paper. (Not the DOI URL - just the DOI.) | | `url` | No | `string` | The URL of the paper or webpage. | | `pages` | No | `string` | The specific pages of a journal or book being referenced, as a mixed list of individual pages and page ranges - i.e., `57, 61-63, 67, 102-104`. | | `volume` | No | `string` | The volume of the journal or the multi-volume book. | -| `number` | No | `string` | The number of the journal. | +| `number` | No | `string` | The number of the journal. | ### Related Content Object Properties @@ -151,12 +149,10 @@ The table below gives details about the fields in the metadata JSON file for ver "title": "", "authors": [ { - "id": "", - "affiliation": "" + "username": "" }, { - "id": "", - "affiliation": "" + "name": "" } ], "dateOfPublication": "", @@ -171,7 +167,6 @@ The table below gives details about the fields in the metadata JSON file for ver ], "seoDescription": "", "doi": "", - "canonicalURL": "", "references": [ { "id": "", diff --git a/metadata_schemas/demo.metadata.schema.0.1.3.json b/metadata_schemas/demo.metadata.schema.0.1.3.json index f28040546b..9e15f5ee8c 100644 --- a/metadata_schemas/demo.metadata.schema.0.1.3.json +++ b/metadata_schemas/demo.metadata.schema.0.1.3.json @@ -1,6 +1,6 @@ { "$schema": "https://json-schema.org/draft/2020-12/schema", - "$id": "demo.metadata.schema.0.1.2.json", + "$id": "demo.metadata.schema.0.1.3.json", "title": "Demo Metadata", "description": "A QML demo's metadata", "type": "object", diff --git a/metadata_schemas/demo.metadata.schema.0.1.4.json b/metadata_schemas/demo.metadata.schema.0.1.4.json new file mode 100644 index 0000000000..529dec8d46 --- /dev/null +++ b/metadata_schemas/demo.metadata.schema.0.1.4.json @@ -0,0 +1,135 @@ +{ + "$schema": "https://json-schema.org/draft/2020-12/schema", + "$id": "demo.metadata.schema.0.1.4.json", + "title": "Demo Metadata", + "description": "A QML demo's metadata", + "type": "object", + "properties": { + "title": { + "description": "The title of the demo.", + "type": "string", + "minLength": 2 + }, + "slug": { + "description": "The slug of the demo. This should match the base name of the metadata file.", + "type": "string", + "minLength": 1 + }, + "authors": { + "description": "The author(s) of the demo. This array must contain at least one item.", + "type": "array", + "items": { + "oneOf": [ + { + "$ref": "file:./objects/author.schema.0.1.0.json" + }, + { + "$ref": "file:./objects/author.schema.0.2.0.json" + } + ] + }, + "minItems": 1 + }, + "dateOfPublication": { + "description": "The date on which the demo was first published, in the form YYYY-MM-DDTHH:MM:SS+00:00.", + "type": "string", + "format": "date-time", + "minLength": 25, + "maxLength": 25 + }, + "dateOfLastModification": { + "description": "The date on which the demo was last modified, in the form YYYY-MM-DDTHH:MM:SS+00:00.", + "type": "string", + "format": "date-time", + "minLength": 25, + "maxLength": 25 + }, + "categories": { + "description": "An array of the categories that this demo is in.", + "type": "array", + "items": { + "enum": [ + "Algorithms", + "Getting Started", + "Optimization", + "Quantum Machine Learning", + "Quantum Chemistry", + "Devices and Performance", + "Quantum Computing", + "Quantum Hardware", + "How-to" + ] + }, + "minItems": 0 + }, + "tags": { + "description": "An array of the tags that the demo has. An empty array is allowed.", + "type": "array", + "items": { + "type": "string" + } + }, + "previewImages": { + "description": "An array of the different images that can be used as previews for this demo - e.g., thumbnails, social media cards (perhaps of different aspect ratios).", + "type": "array", + "items": { + "$ref": "file:./objects/preview.image.schema.0.1.0.json" + }, + "minItems": 1 + }, + "seoDescription": { + "description": "A description of the demo suitable for SEO purposes. Ideally this should be less than 150 characters, but this is not a strict limit. It should be a full, grammatically-correct sentence ending in a full stop.", + "type": "string", + "minLength": 2 + }, + "doi": { + "description": "The DOI for the demo.", + "type": "string", + "pattern": "^$|^10[.]" + }, + "references": { + "description": "An array of the references used for the demo.", + "type": "array", + "items": { + "$ref": "file:./objects/reference.schema.0.1.0.json" + } + }, + "basedOnPapers": { + "description": "An array of the DOIs for the papers the demo is based on. An empty array is allowed.", + "type": "array", + "items": { + "type": "string" + } + }, + "referencedByPapers": { + "description": "An array of the DOIs of any papers that reference the demo. An empty array is allowed.", + "type": "array", + "items": { + "type": "string" + } + }, + "relatedContent": { + "description": "An array of objects describing the content related to the demo. An empty array is allowed.", + "type": "array", + "items": { + "$ref": "file:./objects/related.content.schema.0.1.0.json" + } + }, + "hardware": { + "description": "An array of objects representing third-party vendors who can run the demo on their hardware. An empty array is allowed.", + "type": "array", + "items": { + "$ref": "file:./objects/hardware.schema.0.1.0.json" + } + }, + "discussionForumUrl": { + "description": "Link to dedicated discussion forum thread on https://discuss.pennylane.ai/ for this demo", + "type": "string", + "format": "uri", + "pattern": "(^https?:\/\/(www.)?discuss.pennylane.ai(?:\/.*)?$)" + } + }, + "required": [ + "title", "authors", "dateOfPublication", "dateOfLastModification", "categories", "tags", "previewImages", "seoDescription", "doi", "references", "basedOnPapers", "referencedByPapers", "relatedContent" + ] + } diff --git a/update_metadata.py b/update_metadata.py deleted file mode 100644 index 0d50a41e2e..0000000000 --- a/update_metadata.py +++ /dev/null @@ -1,133 +0,0 @@ -import csv -import json -import glob -from datetime import datetime - - -# The database downloaded from Notion. This has been excluded from the commits, and must be downloaded separately. -DEMONSTRATIONS_DATABASE = "demonstrations_database.csv" - - -def get_names(): - """ Gets a dictionary for which all of the keys are author names and all of the values are the author ids. """ - - filePaths = glob.glob("_static/authors/*.txt") - authors = {} - - # Go through all of the author file paths, open each file, and get the name out of it. - for filePath in filePaths: - with open(filePath, "r") as fileObject: - lines = fileObject.readlines() - - authorId = filePath[16:-4] - authorName = lines[0][8:].strip() - - authors[authorName] = authorId - - return authors - - -def process_datetime(t): - """ Just converts a date from the format 'd/m/y' to 'yyyy-mm-ddTHH:MM:SS'. """ - - if t.strip() == "": - return "" - - d = datetime.strptime(t, "%d/%m/%Y") - - return datetime.strftime(d, "%Y-%m-%dT00:00:00+00:00") - - -def update_metadata(): - """ - Updates all of the metadata files based on the contents of - the database from Notion, the contents of the author files, - and the contents of the demo Python files themselves. - """ - - # Get the dictionary of author names and ids. - names = get_names() - - n = 0 - - with open(DEMONSTRATIONS_DATABASE, encoding="utf-8") as fo1: - csvReader = csv.reader(fo1, delimiter=",") - - # Go through all of the rows in the database. - for row in csvReader: - - # Some of the rows contain irrelevant data. If the first cell of a row starts with 'https://', then it's got demo data in it. - if row[0].startswith("https://"): - # Get the file name from the demo URL. - fileName = row[0][31:-5] - - print(fileName) - - title = "" - - authors = row[5] - # Get all of the author ids from the author dictionary. - authors = [{"id": names.get(author.strip(), "")} for author in authors.split(",")] - - dateOfPublication = process_datetime(row[6]) - dateOfLastModification = process_datetime(row[7]) - categories = [row[9]] - seoDescription = "" - thumbnailURI = "" - - # Some data is easier to get from the demo file itself. - with open("demonstrations/" + fileName + ".py", "r", encoding="utf-8") as fo2: - lines = fo2.readlines() - - lastLine = "" - - # By using some trickery with the contents of the lines, we can extract certain pieces of data. - for line in lines: - if line.strip().startswith("====="): - title = lastLine.strip() - if line.strip().startswith(":property=\"og:description\":"): - seoDescription = line.strip()[27:].strip() - if line.strip().startswith(":property=\"og:image\":"): - thumbnailURI = line.strip()[55:].strip() - - lastLine = line - - # Create a Python dictionary that we can export as JSON. - - demo = {} - demo["title"] = title - demo["authors"] = authors - demo["dateOfPublication"] = dateOfPublication - demo["dateOfLastModification"] = dateOfLastModification - demo["categories"] = categories - demo["tags"] = [] - demo["previewImages"] = [{"type": "thumbnail", "uri": thumbnailURI}] - demo["seoDescription"] = "" - demo["doi"] = "" - demo["canonicalURL"] = row[0].strip() - demo["references"] = [] - demo["basedOnPapers"] = [] - demo["referencedByPapers"] = [] - demo["relatedContent"] = [] - - if n < 100: - metadataFileName = "demonstrations/" + fileName + ".metadata.json" - with open(metadataFileName, "w") as fo3: - json.dump(demo, fo3, indent=4) - - - n += 1 - - print(n) - - -def count_demos(): - """ Counts the number of demos based on the number of metadata files. """ - - filePaths = glob.glob("demonstrations/*.metadata.json") - - print(len(filePaths)) - - -if __name__ == "__main__": - count_demos() From acd1f70d84620ac5cd9406d69a992a1a95aafeef Mon Sep 17 00:00:00 2001 From: David Wierichs Date: Wed, 9 Oct 2024 11:36:29 +0200 Subject: [PATCH 2/2] Demo on " Constant-depth preparation of matrix product states with dynamic circuits" (#1185) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit **Title:** Constant-depth preparation of matrix product states with dynamic circuits **Summary:** Matrix product states (MPS) form an important class of quantum many-body states. Preparing them is an important subroutine for any algorithm that want to use MPS as an initial state, for example. A recent paper, on which this demo is based, and which it is following closely, generalized a method that reduces the depth of such a preparation circuit to constant scaling, by using auxiliary qubits and dynamic quantum circuits (mid-circuit measurements together with classical feedforward). We here focus on the simplest scenario in the main text of the paper, and implement a simple example in code. The implemented MPS has a parameter controlling the correlation length of the prepared state, which we verify explicitly. **Relevant references:** https://arxiv.org/pdf/2404.16083 https://arxiv.org/pdf/quant-ph/0501096 https://journals.aps.org/prxquantum/pdf/10.1103/PRXQuantum.4.020315 **Possible Drawbacks:** **Related GitHub Issues:** ---- If you are writing a demonstration, please answer these questions to facilitate the marketing process. * GOALS — Why are we working on this now? Mid-circuit measurements recently are/were a focus point in PennyLane. MPS states are used in some quantum chemistry algorithms as initial state. * AUDIENCE — Who is this for? Researchers in quantum algorithms * KEYWORDS — What words should be included in the marketing post? TBD * Which of the following types of documentation is most similar to your file? (more details [here](https://www.notion.so/xanaduai/Different-kinds-of-documentation-69200645fe59442991c71f9e7d8a77f8)) - [ ] Tutorial - [x] Demo - [ ] How-to [sc-64275] --------- Co-authored-by: Korbinian Kottmann <43949391+Qottmann@users.noreply.github.com> Co-authored-by: Ivana Kurečić --- ...humbnail_large_constant_depth_mps_prep.png | Bin 0 -> 158792 bytes .../OGthumbnail_constant_depth_mps_prep.png | Bin 0 -> 153556 bytes .../thumbnail_constant_depth_mps_prep.png | Bin 0 -> 34854 bytes .../constant_depth_mps_prep/algorithm.png | Bin 0 -> 284568 bytes .../algorithm_preview.png | Bin 0 -> 149900 bytes .../constant_depth_mps_prep/fusion.png | Bin 0 -> 48908 bytes .../operator_pushing.png | Bin 0 -> 34657 bytes .../operator_pushing_example.png | Bin 0 -> 95604 bytes .../constant_depth_mps_prep/sequential.png | Bin 0 -> 106521 bytes ...rial_constant_depth_mps_prep.metadata.json | 47 + .../tutorial_constant_depth_mps_prep.py | 851 ++++++++++++++++++ 11 files changed, 898 insertions(+) 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