Metadata-Version: 2.4
Name: trainsum
Version: 0.0.2
Summary: A Python package for dealing with quantics tensor trains
Author: Paul Haubenwallner
License-Expression: EUPL-1.2
Project-URL: Repository, https://github.com/fh-igd-iet/trainsum
Project-URL: Documentation, https://trainsum.readthedocs.io
Keywords: quantics,tensor train,tensor network,quantum inspired
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.14
Description-Content-Type: text/x-rst
License-File: LICENSE.txt
Requires-Dist: numpy
Requires-Dist: h5py
Requires-Dist: array_api_compat
Requires-Dist: opt_einsum
Dynamic: license-file

trainsum
========

Welcome to trainsum, a Python package designed for working with quantics tensor trains. The development was done by the ZAQC-team at the Fraunhofer Institute for Graphical Data Analysis (IGD). trainsum is licensed under EUPL 1.2 (similar to GPL).

The main features are:

- easy definition of N-dimensional tensor trains
- quantization of dimensions independent of their size
- einsum-operations equivalent to NumPy’s einsum function
- generic backends for NumPy, Torch and CuPy
- tensorized solver for eigenvalue equations and linear equation systems

Installation
------------
You can install trainsum using pip:

:code:`pip install trainsum`

The dependencies are:

- numpy
- array_api_compat
- opt_einsum
- hdf5

Documentation
-------------
The documentation for trainsum can be found at https://trainsum.readthedocs.io.

Citing
------
If you use trainsum in your research, please cite https://arxiv.org/abs/2602.20226.
