Take a deeper dive into quantum machine learning by exploring cutting-edge algorithms using PennyLane and near-term quantum hardware.
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:tooltip: Use quantum machine learning to rotate a qubit.
:figure: demonstrations/qubit_rotation/bloch.png
:description: :doc:`demos/tutorial_qubit_rotation`
:tags: autograd beginner
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:tooltip: Use quantum machine learning to tune a beamsplitter.
:figure: demonstrations/gaussian_transformation/gauss-circuit.png
:description: :doc:`demos/tutorial_gaussian_transformation`
:tags: autograd photonics beginner
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:tooltip: Use quantum machine learning in a multi-device quantum algorithm.
:figure: demonstrations/plugins_hybrid/photon_redirection.png
:description: :doc:`demos/tutorial_plugins_hybrid`
:tags: autograd photonics beginner
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:tooltip: Multiple expectation values, Jacobians, and keyword arguments.
:description: :doc:`demos/tutorial_advanced_usage`
:tags: autograd beginner
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:tooltip: Extend PyTorch with real quantum computing power.
:figure: demonstrations/pytorch_noise/bloch.gif
:description: :doc:`demos/pytorch_noise`
:tags: forest pytorch beginner
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:tooltip: Explore quantum chemistry in PennyLane.
:figure: demonstrations/quantum_chemistry/water_structure.png
:description: :doc:`demos/tutorial_quantum_chemistry`
:tags: chemistry beginner
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:tooltip: Do arbitrary state preparation on a real quantum computer.
:figure: demonstrations/state_preparation/NOON.png
:description: :doc:`demos/tutorial_state_preparation`
:tags: pytorch
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:tooltip: Ising model example with PennyLane PyTorch interface.
:figure: demonstrations/Ising_model/isingspins.png
:description: :doc:`demos/tutorial_isingmodel_PyTorch`
:tags: pytorch autograd
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:tooltip: Create a simple QGAN with Cirq and TensorFlow.
:figure: demonstrations/QGAN/qgan3.png
:description: :doc:`demos/tutorial_QGAN`
:tags: cirq tensorflow
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:tooltip: A quantum variational classifier
:figure: demonstrations/variational_classifier/classifier_output_59_0.png
:description: :doc:`demos/tutorial_variational_classifier`
:tags: autograd
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:tooltip: Fit one dimensional noisy data with a quantum neural network.
:figure: demonstrations/quantum_neural_net/qnn_output_28_0.png
:description: :doc:`demos/quantum_neural_net`
:tags: autograd strawberryfields photonics
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:tooltip: Find the ground state of a Hamiltonian.
:figure: demonstrations/variational_quantum_eigensolver/pes_h2.png
:description: :doc:`demos/tutorial_vqe`
:tags: autograd chemistry
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:tooltip: Universal Quantum Classifier with data-reuploading
:figure: demonstrations/data_reuploading/universal_dnn.png
:description: :doc:`demos/tutorial_data_reuploading_classifier`
:tags: autograd
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:tooltip: Faster optimization convergence using quantum natural gradient
:figure: demonstrations/quantum_natural_gradient/qng_optimization.png
:description: :doc:`demos/tutorial_quantum_natural_gradient`
:tags: autograd
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:tooltip: Perform QAOA for MaxCut
:figure: demonstrations/qaoa_maxcut/qaoa_maxcut_partition.png
:description: :doc:`demos/tutorial_qaoa_maxcut`
:tags: autograd
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:tooltip: Barren plateaus in quantum neural networks
:figure: demonstrations/barren_plateaus/surface.png
:description: :doc:`demos/tutorial_barren_plateaus`
:tags: autograd
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:tooltip: Rotoselect algorithm
:figure: demonstrations/rotoselect/rotoselect_structure.png
:description: :doc:`demos/tutorial_rotoselect`
:tags: autograd
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:tooltip: Doubly stochastic gradient descent
:figure: demonstrations/doubly_stochastic/single_shot.png
:description: :doc:`Doubly stochastic gradient descent <demos/tutorial_doubly_stochastic>`
:tags: autograd
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:tooltip: Variational Quantum Linear Solver
:figure: demonstrations/vqls/vqls_zoom.png
:description: :doc:`demos/tutorial_vqls`
:tags: autograd
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:tooltip: Coherent implementation of a variational quantum linear solver
:figure: demonstrations/coherent_vqls/cvqls_zoom.png
:description: :doc:`demos/tutorial_coherent_vqls`
:tags: autograd
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:tooltip: Quantum transfer learning
:figure: demonstrations/quantum_transfer_learning/transfer_images.png
:description: :doc:`demos/tutorial_quantum_transfer_learning`
:tags: autograd pytorch
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:tooltip: Training an embedding to perform metric learning
:figure: demonstrations/embedding_metric_learning/training.png
:description: :doc:`demos/tutorial_embeddings_metric_learning`
:tags: autograd
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:tooltip: Evaluate the potential energy surface of H2 with parallel QPUs
:figure: demonstrations/vqe_parallel/vqe_diagram.png
:description: :doc:`demos/tutorial_vqe_parallel`
:tags: chemistry
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:tooltip: Use multiple QPUs to improve classification
:figure: demonstrations/ensemble_multi_qpu/ensemble_diagram.png
:description: :doc:`demos/tutorial_ensemble_multi_qpu`
:tags: pytorch forest qiskit
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:tooltip: Pre-process images with a quantum convolution
:figure: demonstrations/quanvolution/zoom.png
:description: :doc:`demos/tutorial_quanvolution`
:tags: tensorflow
.. toctree::
:maxdepth: 2
:caption: QML Demos
:hidden:
demos/tutorial_qubit_rotation
demos/tutorial_gaussian_transformation
demos/tutorial_plugins_hybrid
demos/tutorial_advanced_usage
demos/pytorch_noise
demos/tutorial_quantum_chemistry
demos/tutorial_state_preparation
demos/tutorial_isingmodel_PyTorch
demos/tutorial_QGAN
demos/tutorial_variational_classifier
demos/quantum_neural_net
demos/tutorial_vqe
demos/tutorial_data_reuploading_classifier
demos/tutorial_quantum_natural_gradient
demos/tutorial_qaoa_maxcut
demos/tutorial_barren_plateaus
demos/tutorial_rotoselect
demos/tutorial_doubly_stochastic
demos/tutorial_vqls
demos/tutorial_coherent_vqls
demos/tutorial_quantum_transfer_learning
demos/tutorial_embeddings_metric_learning
demos/tutorial_vqe_parallel
demos/tutorial_ensemble_multi_qpu
demos/tutorial_quanvolution