Metadata-Version: 2.4
Name: cudensitymat-cu13
Version: 0.3.0
Summary: cuDensityMat - a component of NVIDIA cuQuantum SDK
Home-page: https://developer.nvidia.com/cuquantum-sdk
Author: NVIDIA Corporation
Author-email: cuda_installer@nvidia.com
License: NVIDIA Proprietary Software
Project-URL: Bug Tracker, https://github.com/NVIDIA/cuQuantum/issues
Project-URL: User Forum, https://github.com/NVIDIA/cuQuantum/discussions
Project-URL: Documentation, https://docs.nvidia.com/cuda/cuquantum/latest/cudensitymat/
Keywords: cuda,nvidia,density matrix,quantum dynamics,high-performance computing,quantum computing
Classifier: Topic :: Scientific/Engineering
Classifier: Environment :: GPU :: NVIDIA CUDA
Classifier: Environment :: GPU :: NVIDIA CUDA :: 13
Description-Content-Type: text/x-rst
Requires-Dist: cutensor-cu13<3,>=2.3.1
Requires-Dist: cutensornet-cu13~=2.9
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****************************************************************************
cuDensityMat: A High-Performance Library for Analog Quantum Dynamics Solvers
****************************************************************************

**NVIDIA cuDensityMat** is a high-performance library for composing analog quantum dynamics equation solvers. cuDensityMat is a component of the `NVIDIA cuQuantum SDK`_.

In addition to C APIs, cuDensityMat can also be accessed in Python via `cuQuantum Python`_.

.. _NVIDIA cuQuantum SDK: https://developer.nvidia.com/cuquantum-sdk
.. _cuQuantum Python: https://pypi.org/project/cuquantum-python/

Documentation
=============

Please refer to https://docs.nvidia.com/cuda/cuquantum/latest/cudensitymat/index.html for the cuDensityMat documentation.

Installation
============

The cuDensityMat wheel can be installed as follows:

.. code-block:: bash

   pip install cudensitymat-cuXX

where XX is the CUDA major version (currently CUDA 12 & 13 are supported).

.. note::

   To use cuQuantum's Python APIs, please directly install `cuQuantum Python`_.

Citing cuQuantum
================

`H. Bayraktar et al., "cuQuantum SDK: A High-Performance Library for Accelerating Quantum Science," 2023 IEEE International Conference on Quantum Computing and Engineering (QCE), Bellevue, WA, USA, 2023, pp. 1050-1061, doi: 10.1109/QCE57702.2023.00119 <https://doi.org/10.1109/QCE57702.2023.00119>`_
