https://github.com/fjosw/pyerrors
Error propagation and statistical analysis for Monte Carlo simulations in lattice QCD and statistical mechanics using autograd.
https://github.com/fjosw/pyerrors
autocorrelation autograd automatic-differentiation condensed-matter correlation data-analysis error-propagation lattice-field-theory lattice-gauge-theory lattice-qcd markov-chain monte-carlo particle-physics physics python qcd statistical-analysis statistical-mechanics
Last synced: 9 months ago
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Error propagation and statistical analysis for Monte Carlo simulations in lattice QCD and statistical mechanics using autograd.
- Host: GitHub
- URL: https://github.com/fjosw/pyerrors
- Owner: fjosw
- License: mit
- Created: 2020-10-13T14:51:45.000Z (about 5 years ago)
- Default Branch: develop
- Last Pushed: 2025-03-29T14:30:39.000Z (9 months ago)
- Last Synced: 2025-03-29T15:20:34.640Z (9 months ago)
- Topics: autocorrelation, autograd, automatic-differentiation, condensed-matter, correlation, data-analysis, error-propagation, lattice-field-theory, lattice-gauge-theory, lattice-qcd, markov-chain, monte-carlo, particle-physics, physics, python, qcd, statistical-analysis, statistical-mechanics
- Language: Python
- Homepage: https://fjosw.github.io/pyerrors/pyerrors.html
- Size: 22.6 MB
- Stars: 44
- Watchers: 10
- Forks: 15
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Citation: CITATION.cff
- Codeowners: .github/CODEOWNERS
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README
[](https://www.python.org/downloads/) [](https://opensource.org/licenses/MIT) [](https://arxiv.org/abs/2209.14371) [](https://doi.org/10.1016/j.cpc.2023.108750)
# pyerrors
`pyerrors` is a python framework for error computation and propagation of Markov chain Monte Carlo data from lattice field theory and statistical mechanics simulations.
- **Documentation:** https://fjosw.github.io/pyerrors/pyerrors.html
- **Examples:** https://github.com/fjosw/pyerrors/tree/develop/examples
- **Ask a question:** https://github.com/fjosw/pyerrors/discussions/new?category=q-a
- **Changelog:** https://github.com/fjosw/pyerrors/blob/develop/CHANGELOG.md
- **Bug reports:** https://github.com/fjosw/pyerrors/issues
## Installation
Install the most recent release using pip and [pypi](https://pypi.org/project/pyerrors/):
```bash
python -m pip install pyerrors # Fresh install
python -m pip install -U pyerrors # Update
```
## Contributing
We appreciate all contributions to the code, the documentation and the examples. If you want to get involved please have a look at our [contribution guideline](https://github.com/fjosw/pyerrors/blob/develop/CONTRIBUTING.md).
## Citing pyerrors
If you use `pyerrors` for research that leads to a publication we suggest citing the following papers:
- Fabian Joswig, Simon Kuberski, Justus T. Kuhlmann, Jan Neuendorf, *pyerrors: a python framework for error analysis of Monte Carlo data*. Comput.Phys.Commun. 288 (2023) 108750.
- Ulli Wolff, *Monte Carlo errors with less errors*. Comput.Phys.Commun. 156 (2004) 143-153, Comput.Phys.Commun. 176 (2007) 383 (erratum).
- Alberto Ramos, *Automatic differentiation for error analysis of Monte Carlo data*. Comput.Phys.Commun. 238 (2019) 19-35.
- Stefan Schaefer, Rainer Sommer, Francesco Virotta, *Critical slowing down and error analysis in lattice QCD simulations*. Nucl.Phys.B 845 (2011) 93-119.