Computation times

102:58.339 total execution time for demos files:

Quantum computation with neutral atoms (tutorial_pasqal.py) 14:33.139 0.0 MB
Alleviating barren plateaus with local cost functions (tutorial_local_cost_functions.py) 10:36.396 0.0 MB
The Variational Quantum Thermalizer (tutorial_vqt.py) 10:04.365 0.0 MB
Multiclass margin classifier (tutorial_multiclass_classification.py) 08:10.424 0.0 MB
Classical Shadows (tutorial_classical_shadows.py) 05:18.137 0.0 MB
Variationally optimizing measurement protocols (tutorial_quantum_metrology.py) 05:10.294 0.0 MB
VQE with parallel QPUs on Rigetti Forest (tutorial_vqe_parallel.py) 04:57.562 0.0 MB
The Quantum Graph Recurrent Neural Network (tutorial_qgrnn.py) 04:31.159 0.0 MB
Quantum gradients with backpropagation (tutorial_backprop.py) 03:57.109 0.0 MB
Feedback-Based Quantum Optimization (FALQON) (tutorial_falqon.py) 03:30.437 0.0 MB
Unitary Designs (tutorial_unitary_designs.py) 03:27.436 0.0 MB
Data-reuploading classifier (tutorial_data_reuploading_classifier.py) 03:25.771 0.0 MB
Turning quantum nodes into Torch Layers (tutorial_qnn_module_torch.py) 03:08.960 0.0 MB
VQE in different spin sectors (tutorial_vqe_uccsd_obs.py) 02:14.439 0.0 MB
Variational classifier (tutorial_variational_classifier.py) 02:03.467 0.0 MB
Kernel-based training of quantum models with scikit-learn (tutorial_kernel_based_training.py) 02:01.657 0.0 MB
Quantum models as Fourier series (tutorial_expressivity_fourier_series.py) 02:00.943 0.0 MB
Turning quantum nodes into Keras Layers (tutorial_qnn_module_tf.py) 01:48.960 0.0 MB
Intro to QAOA (tutorial_qaoa_intro.py) 01:24.741 0.0 MB
Measurement optimization (tutorial_measurement_optimize.py) 01:23.284 0.0 MB
Quanvolutional Neural Networks (tutorial_quanvolution.py) 01:17.005 0.0 MB
Quantum transfer learning (tutorial_quantum_transfer_learning.py) 01:02.799 0.0 MB
Accelerating VQEs with quantum natural gradient (tutorial_vqe_qng.py) 01:01.222 0.0 MB
Ensemble classification with Forest and Qiskit devices (tutorial_ensemble_multi_qpu.py) 00:55.303 0.0 MB
Frugal shot optimization with Rosalin (tutorial_rosalin.py) 00:43.172 0.0 MB
Training a quantum circuit with PyTorch (tutorial_state_preparation.py) 00:34.013 0.0 MB
Quantum Generative Adversarial Networks with Cirq + TensorFlow (tutorial_QGAN.py) 00:33.696 0.0 MB
Plugins and Hybrid computation (tutorial_plugins_hybrid.py) 00:29.822 0.0 MB
A brief overview of VQE (tutorial_vqe.py) 00:29.805 0.0 MB
Doubly stochastic gradient descent (tutorial_doubly_stochastic.py) 00:27.186 0.0 MB
Variational Quantum Linear Solver (tutorial_vqls.py) 00:17.079 0.0 MB
Barren plateaus in quantum neural networks (tutorial_barren_plateaus.py) 00:11.508 0.0 MB
Optimizing noisy circuits with Cirq (tutorial_noisy_circuit_optimization.py) 00:11.428 0.0 MB
QAOA for MaxCut (tutorial_qaoa_maxcut.py) 00:10.985 0.0 MB
Using JAX with PennyLane (tutorial_jax_transformations.py) 00:10.843 0.0 MB
Quantum circuit structure learning (tutorial_rotoselect.py) 00:10.360 0.0 MB
Understanding the Haar Measure (tutorial_haar_measure.py) 00:06.168 0.0 MB
The Stochastic Parameter-Shift Rule (tutorial_stochastic_parameter_shift.py) 00:04.524 0.0 MB
Quantum natural gradient (tutorial_quantum_natural_gradient.py) 00:04.369 0.0 MB
3-qubit Ising model in PyTorch (tutorial_isingmodel_PyTorch.py) 00:03.181 0.0 MB
Quantum advantage with Gaussian Boson Sampling (tutorial_gbs.py) 00:02.247 0.0 MB
Quantum Chemistry with PennyLane (tutorial_quantum_chemistry.py) 00:00.964 0.0 MB
Advanced Usage (tutorial_advanced_usage.py) 00:00.765 0.0 MB
Coherent Variational Quantum Linear Solver (tutorial_coherent_vqls.py) 00:00.754 0.0 MB
Basic tutorial: qubit rotation (tutorial_qubit_rotation.py) 00:00.238 0.0 MB
Noisy circuits (tutorial_noisy_circuits.py) 00:00.144 0.0 MB
Gaussian transformation (tutorial_gaussian_transformation.py) 00:00.081 0.0 MB
Computing gradients in parallel with Amazon Braket (braket-parallel-gradients.py) 00:00.000 0.0 MB
Learning to learn with quantum neural networks (learning2learn.py) 00:00.000 0.0 MB
PyTorch and noisy devices (pytorch_noise.py) 00:00.000 0.0 MB
Optimizing a quantum optical neural network (qonn.py) 00:00.000 0.0 MB
Beyond classical computing with qsim (qsim_beyond_classical.py) 00:00.000 0.0 MB
Function fitting with a photonic quantum neural network (quantum_neural_net.py) 00:00.000 0.0 MB
Quantum volume (quantum_volume.py) 00:00.000 0.0 MB
Optimization using SPSA (spsa.py) 00:00.000 0.0 MB