PySTE
A Python package for evolving unitaries and states under the Schrödinger equation using first-order Suzuki-Trotter and computing switching functions.
PySTE stands for Python Suzuki-Trotter-Evolver and is a Python interface to the C++ header-only library Suzuki-Trotter-Evolver: https://github.com/Christopher-K-Long/Suzuki-Trotter-Evolver (doi:10.5281/zenodo.17116329).
While PySTE has limited functionality in comparison to more fleshed out quantum simulation packages such as QuTiP, it is faster at some tasks:
More detailed benchmarks can be found here: https://PySTE.readthedocs.io/en/latest/benchmarks/index.html
Installation
PySTE can be installed as follows:
pip install py-ste
However, the package should be imported as:
import py_ste
Support
Current support:
| macOS Intel (10.13+, 10.15+ on 3.14) |
macOS Apple Silicon (11.0+) |
Windows 64bit | Windows 32bit | Windows Arm64 | manylinux musllinux x86_64 |
Other Linux | |
|---|---|---|---|---|---|---|---|
| CPython 3.8 | ✅ | ✅ | ✅ | ✅ | Build from source | ✅ | Build from source |
| CPython 3.9 | ✅ | ✅ | ✅ | ✅ | Build from source | ✅ | Build from source |
| CPython 3.10 | ✅ | ✅ | ✅ | ✅ | Build from source | ✅ | Build from source |
| CPython 3.11 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | Build from source |
| CPython 3.12 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | Build from source |
| CPython 3.13 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | Build from source |
| CPython 3.14 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | Build from source |
Currently, the pre-built wheels only include the dynamic evolvers. For the faster static evolvers please build from source.
Requirements
Requires:
- NumPy (>= 1.21, < 3)
- Suzuki-Trotter-Evolver (== 1.1.2, packaged with PySTE)
- Eigen3 (>=3.4, <6, packaged with PySTE)
Note that Suzuki-Trotter-Evolver and Eigen3 are packaged with PySTE and so do not need to be installed separately.
If on Linux and using a conda environment you may encounter an error
version `GLIBCXX_...' not found
to fix this you also need to execute:
conda install -c conda-forge libstdcxx-ng
Additional requirements for testing
Additional requirements for benchmarking
Build from source
There are several flags that can be passed which will rebuild PySTE from source using various optimisations. The flags are:
--config-setting="cmake.define.NCTRL_FIXED_SIZES=RANGE"
Defines the strategy used to compile evolvers with a fixed number of controls. The options are:OFF: There will only be evolvers with a dynamic number of controls.SINGLE: There will only be a single evolver with a fixed number of controls specified by--config-setting="cmake.define.NCTRL=...".RANGE(default option): There will be evolvers with a fixed number of controls in the range $[1,$MAX_NCTRL$]$ whereMAX_NCTRLcan be set with--config-setting="cmake.define.MAX_NCTRL=..."POWER: The evolvers with a fixed number of controls will have a number of controls given by powers in the range $[1,$MAX_POWER_NCTRL$]$ of the baseBASE_NCTRLwhereMAX_POWER_NCTRLcan be set with--config-setting="cmake.define.MAX_POWER_NCTRL=..."andBASE_NCTRLwith--config-setting="cmake.define.BASE_NCTRL=..."
--config-setting="cmake.define.NCTRL=1"
The number of controls when using--config-setting="cmake.define.NCTRL_FIXED_SIZES=SINGLE". A positive integer, by default 1.--config-setting="cmake.define.MAX_NCTRL=14"
The maximum number of controls when using--config-setting="cmake.define.NCTRL_FIXED_SIZES=RANGE". A positive integer, by default 14.--config-setting="cmake.define.MAX_POWER_NCTRL=3"
The maximum power when using--config-setting="cmake.define.NCTRL_FIXED_SIZES=POWER". A positive integer, by default 3.--config-setting="cmake.define.BASE_NCTRL=2"
The base of the powers when using--config-setting="cmake.define.NCTRL_FIXED_SIZES=POWER". A positive integer, by default 2.--config-setting="cmake.define.DIM_FIXED_SIZES=RANGE"
Defines the strategy used to compile evolvers with a fixed vector space dimension. The options are:OFF: There will only be evolvers with a dynamic vector space dimension.SINGLE: There will only be a single evolver with a fixed vector space dimension specified by--config-setting="cmake.define.DIM=...".RANGE(default option): There will be evolvers with a fixed vector space dimension in the range $[1,$MAX_DIM$]$ whereMAX_DIMcan be set with--config-setting="cmake.define.MAX_DIM=..."POWER: The evolvers with a fixed vector space dimension will have a vector space dimension given by powers in the range $[1,$MAX_POWER_DIM$]$ of the baseBASE_DIMwhereMAX_POWER_DIMcan be set with--config-setting="cmake.define.MAX_POWER_DIM=..."andBASE_DIMwith--config-setting="cmake.define.BASE_DIM=..."
--config-setting="cmake.define.DIM=2"
The vector space dimension when using--config-setting="cmake.define.DIM_FIXED_SIZES=SINGLE". A positive integer, by default 2.--config-setting="cmake.define.MAX_DIM=16"
The maximum vector space dimension when using--config-setting="cmake.define.DIM_FIXED_SIZES=RANGE". A positive integer, by default 16.--config-setting="cmake.define.MAX_POWER_DIM=4"
The maximum power when using--config-setting="cmake.define.DIM_FIXED_SIZES=POWER". A positive integer, by default 4.--config-setting="cmake.define.BASE_DIM=2"
The base of the powers when using--config-setting="cmake.define.DIM_FIXED_SIZES=POWER". A positive integer, by default 2.
For example,
pip install --no-binary py-ste py-ste \
--no-cache-dir \
--config-setting="cmake.define.NCTRL_FIXED_SIZES=SINGLE" \
--config-setting="cmake.define.NCTRL=2" \
--config-setting="cmake.define.DIM_FIXED_SIZES=POWER" \
--config-setting="cmake.define.MAX_POWER_DIM=3" \
--verbose
will build PySTE from source and optimises evolvers at compile time with 2 control Hamiltonians acting on a vector space of dimensions 2, 4, and 8. Increasing the number of optimised evolvers increases the compile time. The --no-binary py-ste flag instructs pip to build py-ste from source and the following py-ste instructs pip that py-ste is one of the packages to collect (indeed the only package). The --no-cache-dir flag ensures that a cached .whl file is not used instead and the package is actually built from source. Finally, the --verbose flag allows the progress of the build to be seen. This is useful as the builds can often take a long time.
Note building from source requires approximately 16GB of RAM.
Cloning the repository
PySTE uses git submodules and so should be cloned with the flag --recurse-submodules as follows:
git clone --recurse-submodules https://github.com/Christopher-K-Long/PySTE
Alternatively, you can clone the repository normally and then initialise the submodules as follows
git clone https://github.com/Christopher-K-Long/PySTE
git submodule update --init --recursive
Documentation
Documentation, including worked examples, can be found at: https://PySTE.readthedocs.io
Source Code
Source code can be found at: https://github.com/Christopher-K-Long/PySTE
A mirror can be found at: https://gitlab.com/Christopher-K-Long/PySTE
Please submit all pull requests, issues, discussions, and vulnerability reports to the GitHub repository.
Releases from this repository are assigned DOIs and can be found at https://doi.org/10.5281/zenodo.17116431. The DOI for all releases is 10.5281/zenodo.17116431. Additionally, the releases are archived to https://archive.softwareheritage.org/swh:1:dir:508bd76667d9f26712852bbdc31d87d44b72bfc5.
Version and Changes
The current version is 1.1.2. Please see the Change Log for more details. PySTE uses semantic versioning.
Acknowledgements
CKL would like to thank Chris Hall for useful discussions on the structure of the package.
Metadata
Release files for py-ste 1.1.2
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| py_ste-1.1.2.tar.gz | 5.9 MB | Details |
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Total release size: 72.1 MB
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