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Mathematics of Computation

Published by the American Mathematical Society since 1960 (published as Mathematical Tables and other Aids to Computation 1943-1959), Mathematics of Computation is devoted to research articles of the highest quality in computational mathematics.

ISSN 1088-6842 (online) ISSN 0025-5718 (print)

The 2020 MCQ for Mathematics of Computation is 1.78.

What is MCQ? The Mathematical Citation Quotient (MCQ) measures journal impact by looking at citations over a five-year period. Subscribers to MathSciNet may click through for more detailed information.

 

The PSLQ algorithm for empirical data
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by Yong Feng, Jingwei Chen and Wenyuan Wu HTML | PDF
Math. Comp. 88 (2019), 1479-1501 Request permission

Abstract:

The celebrated integer relation finding algorithm PSLQ has been successfully used in many applications. PSLQ was only analyzed theoretically for exact input data, however, when the input data are irrational numbers, they must be approximate ones due to the finite precision of the computer. When the algorithm takes empirical data (inexact data with error bounded) instead of exact real numbers as its input, how do we theoretically ensure the output of the algorithm to be an exact integer relation?

In this paper, we investigate the PSLQ algorithm for empirical data as its input. Firstly, we give a termination condition for this case. Secondly, we analyze a perturbation on the hyperplane matrix constructed from the input data and hence disclose a relationship between the accuracy of the input data and the output quality (an upper bound on the absolute value of the inner product of the exact data and the computed integer relation), which naturally leads to an error control strategy for PSLQ. Further, we analyze the complexity bound of the PSLQ algorithm for empirical data. Examples on transcendental numbers and algebraic numbers show the meaningfulness of our error control strategy.

References
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Additional Information
  • Yong Feng
  • Affiliation: Chongqing Key Lab of Automated Reasoning and Cognition, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, People’s Republic of China
  • MR Author ID: 612618
  • Email: yongfeng@cigit.ac.cn
  • Jingwei Chen
  • Affiliation: Chongqing Key Lab of Automated Reasoning and Cognition, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, People’s Republic of China
  • Email: chenjingwei@cigit.ac.cn
  • Wenyuan Wu
  • Affiliation: Chongqing Key Lab of Automated Reasoning and Cognition, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, People’s Republic of China
  • MR Author ID: 802008
  • Email: wuwenyuan@cigit.ac.cn
  • Received by editor(s): July 17, 2017
  • Received by editor(s) in revised form: November 8, 2017, and January 9, 2018
  • Published electronically: June 20, 2018
  • Additional Notes: The first author was supported by NNSF (China) Grant 11671377 and 61572024.
    The second author was supported by NNSF (China) Grant 11501540, CAS “Light of West China” Program and Youth Innovation Promotion Association of CAS.\endgraf The second author is the corresponding author
    The third author was supported by NNSF (China) Grant 11471307 and 11771421, Chongqing Research Program (cstc2015jcyjys40001, KJ1705121), and CAS Research Program of Frontier Sciences (QYZDB-SSW-SYS026).
  • © Copyright 2018 American Mathematical Society
  • Journal: Math. Comp. 88 (2019), 1479-1501
  • MSC (2010): Primary 11A05, 11Y16; Secondary 68-04
  • DOI: https://doi.org/10.1090/mcom/3356
  • MathSciNet review: 3904153