NVIDIA cuQuantum SDK is a set of high-performance libraries and tools for accelerating quantum computing simulations at both the circuit and device level by orders of magnitude. It consists of five major components:
cuDensityMat: a high-performance library for quantum dynamics equation solvers
cuPauliProp: a high-performance library for Pauli propagation quantum simulators
cuStabilizer: a high-performance library for stabilizer quantum simulators
cuStateVec: a high-performance library for state vector quantum simulators
cuTensorNet: a high-performance library for tensor network computations
In addition to C APIs, cuQuantum also provides Python APIs via cuQuantum Python.
Documentation
Please refer to https://docs.nvidia.com/cuda/cuquantum/index.html for the cuQuantum documentation.
Installation
The cuQuantum wheel can be installed as follows:
pip install cuquantum-cuXXwhere XX is the CUDA major version (currently CUDA 12 and 13 are supported). We encourage users to install package with the -cuXX suffix;
Citing cuQuantum
5 maintainers
Metadata
5 maintainers
Release files for cuquantum-cu12 26.9.0
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 |
|---|---|---|---|---|
| cuquantum_cu12-26.9.0-py3-none-manylinux2014_x86_64.whl | Python 3 | none | Linux glibc 2.17+ x86-64 | Details |
| cuquantum_cu12-26.9.0-py3-none-manylinux2014_aarch64.whl | Python 3 | none | Linux glibc 2.17+ ARM64 | Details |
Total release size: 14.4 kB
Release files / cuquantum_cu12-26.9.0-py3-none-manylinux2014_x86_64.whl
| Download URL | cuquantum_cu12-26.9.0-py3-none-manylinux2014_x86_64.whl |
|---|---|
| Size | 7.2 kB |
| Tags | Linux glibc 2.17+ x86-64 Python 3 |
|
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No |
| Uploaded via |
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Release files / cuquantum_cu12-26.9.0-py3-none-manylinux2014_aarch64.whl
| Download URL | cuquantum_cu12-26.9.0-py3-none-manylinux2014_aarch64.whl |
|---|---|
| Size | 7.2 kB |
| Tags | Linux glibc 2.17+ ARM64 Python 3 |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.7
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