Context for CLI commands.

Represents a demo and its metadata.

Class to generate the gadget Hamiltonian corresponding to a given computational hamiltonian according to the gadget construction derived by

Interface to a Python virtual environment.

A lightweight Belief Propagation + OSD-0 decoder. Args: H (np.ndarray): Parity-check matrix for the codeword (m x n). error_rate

A pickleable mock-up of a Python iterator on a torch.utils.Dataloader. Provide a dataset X and the resulting object O will allow you to use next(O

Pytorch dataloader for the Optical Recognition of Handwritten Digits Data Set

Fully connected classical discriminator

Torch module implementing the *dressed* quantum net.

Load and cache PennyLane and Catalyst objects.inv inventories. On initialization, each inventory is loaded from disk if present in cache

Multi layer perceptron (MLP) with a single hidden layer.

Quantum generator class for the patch method

Class for creating a quantum machine learning (classification) model based on the StronglyEntanglingLayers template. Args: input_dim

Quantum natural SPSA optimizer. Refer to https://quantum-journal.org/papers/q-2021-10-20-567/ for a detailed description of the methodology. When

Embed author bio in posts (ReST format). Based on the pelican_youtube plugin: https://github.com/kura/pelican_youtube Usage: .. bio::

Sphinx-build targets.

Create a community card.

Create a sphinx gallery style thumbnail. tooltip and figure are self explanatory. Description could be a link to a document like in below exa

Class to generate the gadget Hamiltonian corresponding to a given computational hamiltonian according to the gadget construction derived by

Add related demos to the sidebar.

Create a sphinx gallery style thumbnail.