Metadata-Version: 2.4
Name: tn4qa
Version: 0.0.11
Summary: A Python package to integrate tensor network methods with quantum algorithms.
Author-email: Angus Mingare <angus.mingare.22@ucl.ac.uk>, Isabelle Heuzé <isabelle.heuze.24@ucl.ac.uk>
License-Expression: MIT
License-File: LICENSE
Requires-Python: <3.12,>=3.11
Requires-Dist: block2==0.5.3rc18
Requires-Dist: cached-property>=1.5.2
Requires-Dist: cotengra>=0.6.2
Requires-Dist: cotengrust>=0.1.4
Requires-Dist: iqm-client>=22.4
Requires-Dist: kahypar>=1.3.6
Requires-Dist: matplotlib>=3.10.1
Requires-Dist: networkx>=3.6.1
Requires-Dist: numpy<3,>=2.1
Requires-Dist: optuna>=4.8.0
Requires-Dist: qiskit-aer>=0.15.1
Requires-Dist: qiskit-algorithms>=0.3.1
Requires-Dist: qiskit-ibm-runtime>=0.34.0
Requires-Dist: qiskit>=2.0.0
Requires-Dist: scikit-learn>=1.3.0
Requires-Dist: scipy<1.16.2,>=1.15.0
Requires-Dist: sparse<0.16,>=0.15.4
Description-Content-Type: text/markdown

# TN4QA

TN4QA (Tensor Networks for Quantum Algorithms) is a package designed to build workflows that use tensor network methods to assist quantum algorithms.

## Installation

Install from PyPI using

```
pip install tn4qa \
  --extra-index-url https://block-hczhai.github.io/block2-preview/pypi/
```

## Getting Started

From the top level of the repository you should be able to build the docs using the following

```
cd ./docs
make html
python3 -m http.server -d build/html 8080
```

so that the docs are accessible through http://localhost:8080. The documentation contains class information as well as tutorials on how to use TN4QA.
