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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2023
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2308.06652 |
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| _version_ | 1866913216495353856 |
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| author | Altenkort, Luis Clarke, David Anthony Goswami, Jishnu Sandmeyer, Hauke |
| author_facet | Altenkort, Luis Clarke, David Anthony Goswami, Jishnu Sandmeyer, Hauke |
| contents | Python is a particularly appealing language to carry out data analysis, owing in part to its user-friendly character as well as its access to well maintained and powerful libraries like NumPy and SciPy. Still, for the purpose of analyzing data in a lattice QCD context, some desirable functionality is missing from these libraries. Moreover, scripting languages tend to be slower than compiled ones. To help address these points we present the AnalysisToolbox, a collection of Python modules to facilitate lattice QCD data analysis. Some highlighted features include general-purpose jackknife and bootstrap routines; modules for reading in and storing gauge configurations; a module to carry out hadron resonance gas model calculations; and convenience wrappers for SciPy integration, curve fitting, and splines. These features are sped up behind the scenes using parallelization and just-in-time compilation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2308_06652 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Streamlined data analysis in Python Altenkort, Luis Clarke, David Anthony Goswami, Jishnu Sandmeyer, Hauke High Energy Physics - Lattice Python is a particularly appealing language to carry out data analysis, owing in part to its user-friendly character as well as its access to well maintained and powerful libraries like NumPy and SciPy. Still, for the purpose of analyzing data in a lattice QCD context, some desirable functionality is missing from these libraries. Moreover, scripting languages tend to be slower than compiled ones. To help address these points we present the AnalysisToolbox, a collection of Python modules to facilitate lattice QCD data analysis. Some highlighted features include general-purpose jackknife and bootstrap routines; modules for reading in and storing gauge configurations; a module to carry out hadron resonance gas model calculations; and convenience wrappers for SciPy integration, curve fitting, and splines. These features are sped up behind the scenes using parallelization and just-in-time compilation. |
| title | Streamlined data analysis in Python |
| topic | High Energy Physics - Lattice |
| url | https://arxiv.org/abs/2308.06652 |