.. role:: html(raw)
:format: html
.. _New_Users:
Tutorials
=========
:html:`
Learn PennyLane
`
The following tutorials introduce the core PennyLane concepts, including QNodes,
plugins, and devices, via simple and easy-to-follow examples.
.. customgalleryitem::
:tooltip: Use quantum machine learning to rotate a qubit.
:figure: ../examples/figures/bloch.png
:description: :ref:`qubit_rotation`
.. customgalleryitem::
:tooltip: Use quantum machine learning to tune a beamsplitter.
:figure: ../examples/figures/gauss-circuit.png
:description: :ref:`gaussian_transformation`
.. customgalleryitem::
:tooltip: Use quantum machine learning in a multi-device quantum algorithm.
:figure: ../examples/figures/photon_redirection.png
:description: :ref:`plugins_hybrid`
.. customgalleryitem::
:tooltip: Multiple expectation values, Jacobians, and keyword arguments.
:description: :ref:`advanced_features`
.. customgalleryitem::
:tooltip: Extend PyTorch with real quantum computing power.
:figure: ../examples/figures/bloch.gif
:description: :ref:`pytorch_noise`
:html:``
:html:`Quantum machine learning with PennyLane
`
Take a deeper dive into quantum machine learning by exploring cutting-edge
algorithms using PennyLane and near-term quantum hardware.
.. customgalleryitem::
:tooltip: Do arbitrary state preparation on a real quantum computer.
:figure: ../examples/figures/NOON.png
:description: :ref:`state_preparation`
.. customgalleryitem::
:tooltip: Use PennyLane to create a simple QGAN
:figure: ../examples/figures/qgan3.png
:description: :ref:`quantum_GAN`
.. customgalleryitem::
:tooltip: A quantum variational classifier
:figure: ../examples/figures/classifier_output_59_0.png
:description: :ref:`variational_classifier`
.. customgalleryitem::
:tooltip: Fit one dimensional noisy data with a quantum neural network.
:figure: ../examples/figures/qnn_output_28_0.png
:description: :ref:`quantum_neural_net`
.. customgalleryitem::
:tooltip: Find the ground state of a Hamiltonian.
:figure: ../examples/figures/vqe_output_22_0.png
:description: :ref:`vqe`
.. customgalleryitem::
:tooltip: Universal Quantum Classifier with data-reuploading
:figure: ../examples/figures/universal_dnn.png
:description: :ref:`data_reuploading_classifier`
.. customgalleryitem::
:tooltip: Faster optimization convergence using quantum natural gradient
:figure: ../examples/figures/quantum_natural_gradient/qng_optimization.png
:description: :ref:`quantum_natural_gradient`
.. customgalleryitem::
:tooltip: Perform QAOA for MaxCut
:figure: ../examples/figures/qaoa_maxcut_partition.png
:description: :ref:`qaoa_maxcut`
.. customgalleryitem::
:tooltip: Barren plateaus in quantum neural networks
:figure: ../examples/figures/barren_plateaus/surface.png
:description: :ref:`barren_plateaus`
:html:``
.. toctree::
:hidden:
:maxdepth: 2
tutorials/pennylane_run_qubit_rotation
tutorials/pennylane_run_gaussian_transformation
tutorials/pennylane_run_plugins_hybrid
tutorials/pennylane_run_advanced_usage
tutorials/pennylane_pytorch_noise
tutorials/pennylane_run_state_preparation
tutorials/pennylane_run_QGAN
tutorials/pennylane_run_variational_classifier
tutorials/pennylane_quantum_neural_net
tutorials/pennylane_run_variational_quantum_eigensolver
tutorials/pennylane_run_data_reuploading_classifier
tutorials/pennylane_run_quantum_natural_gradient
tutorials/pennylane_run_qaoa_maxcut
tutorials/pennylane_run_barren_plateaus