NVIDIA cuStabilizer provides high-performance primitives for GPU-accelerated simulation of noisy Clifford quantum circuits. cuStabilizer is a component of the NVIDIA cuQuantum SDK.
In addition to C APIs, cuStabilizer can also be accessed in Python through cython bindings provided in cuQuantum Python.
Documentation
Please refer to https://docs.nvidia.com/cuda/cuquantum/latest/custabilizer/index.html for the cuStabilizer documentation.
Installation
The cuStabilizer wheel can be installed as follows:
pip install custabilizer-cuXXwhere XX is the CUDA major version (currently CUDA 12 & 13 are supported).
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>
1 maintainer
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distributions
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file custabilizer_cu13-0.5.0-py3-none-manylinux2014_x86_64.whl.
File metadata
- Download URL: custabilizer_cu13-0.5.0-py3-none-manylinux2014_x86_64.whl
- Upload date:
- Size: 7.4 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/7.0.0 CPython/3.14.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
1e7f7016dad0ef123da9a8d1d43e998ff9b8f69b802a4769a51daed089e37764
|
|
| MD5 |
16b200150272deb5434431a0edeceb3f
|
|
| BLAKE2b-256 |
c26dfaee7fd076f0b6eab5c62a9be559dcfb255a9898fc61387b488df268936f
|
File details
Details for the file custabilizer_cu13-0.5.0-py3-none-manylinux2014_aarch64.whl.
File metadata
- Download URL: custabilizer_cu13-0.5.0-py3-none-manylinux2014_aarch64.whl
- Upload date:
- Size: 7.4 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/7.0.0 CPython/3.14.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
c1a29ed723ef0b193af21817654e72572f106f9a48317bd2b164a2ce1d2865b7
|
|
| MD5 |
8c91ab40dce2ac7a875343e686c14b00
|
|
| BLAKE2b-256 |
8912ce4709e4f859d76c2cdd929e5b24da29bf60f479c248360043e767b77fa3
|
