Highprecision arithmetic in mathematical physics
For many scientific calculations, particularly those involving empirical data, IEEE 32bit floatingpoint arithmetic produces results of sufficient accuracy, while for other applications IEEE 64bit floatingpoint is more appropriate. But for some very demanding applications, even higher levels of precision are often required. Furthermore, this article discusses the challenge of highprecision computation, in the context of mathematical physics, and highlights what facilities are required to support future computation, in light of emerging developments in computer architecture.
 Authors:

^{[1]};
^{[2]}
 Lawrence Berkeley National Lab., CA (United States); Univ. of California, Davis, CA (United States)
 Univ. of Newcastle, Callaghan (Australia)
 Publication Date:
 Grant/Contract Number:
 AC0205CH11231
 Type:
 Accepted Manuscript
 Journal Name:
 Mathematics
 Additional Journal Information:
 Journal Volume: 3; Journal Issue: 2; Journal ID: ISSN 22277390
 Publisher:
 MDPI
 Research Org:
 Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
 Sponsoring Org:
 USDOE
 Country of Publication:
 United States
 Language:
 English
 Subject:
 97 MATHEMATICS AND COMPUTING; highprecision arithmetic; numerical integration; PSLQ algorithm; Ising integrals; Poisson equation
 OSTI Identifier:
 1212153
Bailey, David H., and Borwein, Jonathan M.. Highprecision arithmetic in mathematical physics. United States: N. p.,
Web. doi:10.3390/math3020337.
Bailey, David H., & Borwein, Jonathan M.. Highprecision arithmetic in mathematical physics. United States. doi:10.3390/math3020337.
Bailey, David H., and Borwein, Jonathan M.. 2015.
"Highprecision arithmetic in mathematical physics". United States.
doi:10.3390/math3020337. https://www.osti.gov/servlets/purl/1212153.
@article{osti_1212153,
title = {Highprecision arithmetic in mathematical physics},
author = {Bailey, David H. and Borwein, Jonathan M.},
abstractNote = {For many scientific calculations, particularly those involving empirical data, IEEE 32bit floatingpoint arithmetic produces results of sufficient accuracy, while for other applications IEEE 64bit floatingpoint is more appropriate. But for some very demanding applications, even higher levels of precision are often required. Furthermore, this article discusses the challenge of highprecision computation, in the context of mathematical physics, and highlights what facilities are required to support future computation, in light of emerging developments in computer architecture.},
doi = {10.3390/math3020337},
journal = {Mathematics},
number = 2,
volume = 3,
place = {United States},
year = {2015},
month = {5}
}