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dc.contributor.authorChan, Cy
dc.contributor.authorDrensky, Vesselin
dc.contributor.authorEdelman, Alan
dc.contributor.authorKan, Raymond
dc.contributor.authorKoev, Plamen
dc.date.accessioned2021-09-20T17:30:53Z
dc.date.available2021-09-20T17:30:53Z
dc.date.issued2018-10-20
dc.identifier.urihttps://hdl.handle.net/1721.1/131906
dc.description.abstractAbstract In this paper, we present two new algorithms for computing all Schur functions $$s_\kappa (x_1,\ldots ,x_n)$$ s κ ( x 1 , … , x n ) for partitions $$\kappa $$ κ such that $$|\kappa |\le N$$ | κ | ≤ N . For nonnegative arguments, $$x_1,\ldots ,x_n$$ x 1 , … , x n , both algorithms are subtraction-free and thus each Schur function is computed to high relative accuracy in floating point arithmetic. The cost of each algorithm per Schur function is $$\mathscr {O}(n^2)$$ O ( n 2 ) .en_US
dc.publisherSpringer USen_US
dc.relation.isversionofhttps://doi.org/10.1007/s10801-018-0846-yen_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceSpringer USen_US
dc.titleOn computing Schur functions and series thereofen_US
dc.typeArticleen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mathematics
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2020-09-24T21:30:12Z
dc.language.rfc3066en
dc.rights.holderSpringer Science+Business Media, LLC, part of Springer Nature
dspace.embargo.termsY
dspace.date.submission2020-09-24T21:30:12Z
mit.licenseOPEN_ACCESS_POLICY
mit.metadata.statusAuthority Work and Publication Information Needed


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