cuStabilizer: A High-Performance Library for Stabilizer Quantum Simulators
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>
Metadata
Release files for custabilizer-cu12 0.5.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| custabilizer_cu12-0.5.0-py3-none-manylinux2014_x86_64.whl | Python 3 | none | Linux glibc 2.17+ x86-64 | Details |
| custabilizer_cu12-0.5.0-py3-none-manylinux2014_aarch64.whl | Python 3 | none | Linux glibc 2.17+ ARM64 | Details |
Total release size: 16.3 MB
Release files / custabilizer_cu12-0.5.0-py3-none-manylinux2014_x86_64.whl
| Download URL | custabilizer_cu12-0.5.0-py3-none-manylinux2014_x86_64.whl |
|---|---|
| Size | 8.2 MB |
| Tags | Linux glibc 2.17+ x86-64 Python 3 |
|
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twine/7.0.0 CPython/3.14.7
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Release files / custabilizer_cu12-0.5.0-py3-none-manylinux2014_aarch64.whl
| Download URL | custabilizer_cu12-0.5.0-py3-none-manylinux2014_aarch64.whl |
|---|---|
| Size | 8.2 MB |
| Tags | Linux glibc 2.17+ ARM64 Python 3 |
|
SHA-256 checksum How to use checksums |
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twine/7.0.0 CPython/3.14.7
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