qmatchatea 1.5.10

Quantum matcha TEA python library for tensor network emulation of quantum circuits.

Quantum Matcha Tea

Quantum Matcha Tea is a Tensor Network emulator for quantum circuits and linear optics circuits. You can define your circuits either in qiskit, or using Matcha's internal circuit interface Qcircuit.

If you use another quantum information library (such as cirq) we suggest to save your circuit in qasm format and then load it in qiskit.

The circuits ca be ran using the following backends:

• numpy, using the CPU in python;
• cupy, using the GPU in python.

Documentation

Here is the documentation. The documentation can also be built locally with sphinx with the following python packages:

• sphinx
• sphinx_rtd_theme

and running the command make html in the docs/ folder.

Installation

Independent of the use-case, you have to install the dependencies. Installing the optional dependencies will enable the use of more tensor modules (for instance, supporting GPUs).

Installation via pip

The package is available via PyPi and pip install qmatchatea. After cloning the repository, a local installation via pip is also possible via pip install ..

Optional dependencies

The following optional dependencies are not installed by default.

• cupy: necessary to run on the GPU with the tensor_module="numpy". The installation guide can be found at the cupy website.
• torch: necessary to run simulation with the tensor_module="torch". The installation guide can be found at the pytorch website.
• tensorflow: necessary to run simulation with the tensor_module="tensorflow". The installation guide can be found at the tensorflow website.
• jax: necessary to run simulation with the tensor_module="jax". The installation guide can be found at the jax website.

MPI simulations also require the package mpi4py.

Testing the package

To test the python package qmatchatea simply run from the command: python3 -m unittest

License

The project qmatchatea from the repository py_api_quantum_matcha_tea is licensed under the following license:

Apache License 2.0

The license applies to the files of this project as indicated in the header of each file, but not its dependencies.