{"title":"完全旋转高斯消去中生长因子的一个新的上界","authors":"Ankit Bisain, Alan Edelman, John Urschel","doi":"arxiv-2312.00994","DOIUrl":null,"url":null,"abstract":"The growth factor in Gaussian elimination measures how large the entries of\nan LU factorization can be relative to the entries of the original matrix. It\nis a key parameter in error estimates, and one of the most fundamental topics\nin numerical analysis. We produce an upper bound of $n^{0.2079 \\ln n +0.91}$\nfor the growth factor in Gaussian elimination with complete pivoting -- the\nfirst improvement upon Wilkinson's original 1961 bound of $2 \\, n ^{0.25\\ln n\n+0.5}$.","PeriodicalId":501061,"journal":{"name":"arXiv - CS - Numerical Analysis","volume":" 20","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A New Upper Bound For the Growth Factor in Gaussian Elimination with Complete Pivoting\",\"authors\":\"Ankit Bisain, Alan Edelman, John Urschel\",\"doi\":\"arxiv-2312.00994\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The growth factor in Gaussian elimination measures how large the entries of\\nan LU factorization can be relative to the entries of the original matrix. It\\nis a key parameter in error estimates, and one of the most fundamental topics\\nin numerical analysis. We produce an upper bound of $n^{0.2079 \\\\ln n +0.91}$\\nfor the growth factor in Gaussian elimination with complete pivoting -- the\\nfirst improvement upon Wilkinson's original 1961 bound of $2 \\\\, n ^{0.25\\\\ln n\\n+0.5}$.\",\"PeriodicalId\":501061,\"journal\":{\"name\":\"arXiv - CS - Numerical Analysis\",\"volume\":\" 20\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Numerical Analysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2312.00994\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Numerical Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2312.00994","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A New Upper Bound For the Growth Factor in Gaussian Elimination with Complete Pivoting
The growth factor in Gaussian elimination measures how large the entries of
an LU factorization can be relative to the entries of the original matrix. It
is a key parameter in error estimates, and one of the most fundamental topics
in numerical analysis. We produce an upper bound of $n^{0.2079 \ln n +0.91}$
for the growth factor in Gaussian elimination with complete pivoting -- the
first improvement upon Wilkinson's original 1961 bound of $2 \, n ^{0.25\ln n
+0.5}$.