LinApart: optimizing the univariate partial fraction decomposition
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866914816655884288 |
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| author | Chargeishvili, Bakar Fekésházy, Levente Somogyi, Gábor Van Thurenhout, Sam |
| author_facet | Chargeishvili, Bakar Fekésházy, Levente Somogyi, Gábor Van Thurenhout, Sam |
| contents | We present LinApart, a routine designed for efficiently performing the univariate partial fraction decomposition of large symbolic expressions. Our method is based on an explicit closed formula for the decomposition of rational functions with fully factorized denominators. We provide implementations in both the Wolfram Mathematica and C languages, made available at https://github.com/fekeshazy/LinApart . The routine can provide very significant performance gains over available tools such as the Apart command in Mathematica. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_20130 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | LinApart: optimizing the univariate partial fraction decomposition Chargeishvili, Bakar Fekésházy, Levente Somogyi, Gábor Van Thurenhout, Sam Symbolic Computation High Energy Physics - Phenomenology High Energy Physics - Theory We present LinApart, a routine designed for efficiently performing the univariate partial fraction decomposition of large symbolic expressions. Our method is based on an explicit closed formula for the decomposition of rational functions with fully factorized denominators. We provide implementations in both the Wolfram Mathematica and C languages, made available at https://github.com/fekeshazy/LinApart . The routine can provide very significant performance gains over available tools such as the Apart command in Mathematica. |
| title | LinApart: optimizing the univariate partial fraction decomposition |
| topic | Symbolic Computation High Energy Physics - Phenomenology High Energy Physics - Theory |
| url | https://arxiv.org/abs/2405.20130 |