dc.contributor.author | Chan, Cy | |
dc.contributor.author | Drensky, Vesselin | |
dc.contributor.author | Edelman, Alan | |
dc.contributor.author | Kan, Raymond | |
dc.contributor.author | Koev, Plamen | |
dc.date.accessioned | 2021-09-20T17:30:53Z | |
dc.date.available | 2021-09-20T17:30:53Z | |
dc.date.issued | 2018-10-20 | |
dc.identifier.uri | https://hdl.handle.net/1721.1/131906 | |
dc.description.abstract | Abstract
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.publisher | Springer US | en_US |
dc.relation.isversionof | https://doi.org/10.1007/s10801-018-0846-y | en_US |
dc.rights | Creative Commons Attribution-Noncommercial-Share Alike | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | en_US |
dc.source | Springer US | en_US |
dc.title | On computing Schur functions and series thereof | en_US |
dc.type | Article | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Mathematics | |
dc.eprint.version | Author's final manuscript | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dc.date.updated | 2020-09-24T21:30:12Z | |
dc.language.rfc3066 | en | |
dc.rights.holder | Springer Science+Business Media, LLC, part of Springer Nature | |
dspace.embargo.terms | Y | |
dspace.date.submission | 2020-09-24T21:30:12Z | |
mit.license | OPEN_ACCESS_POLICY | |
mit.metadata.status | Authority Work and Publication Information Needed | |