English

Detecting Potential Instabilities of Numerical Algorithms

Numerical Analysis 2015-09-09 v1

Abstract

It has been the standard teaching of today that backward stability analysis is taught as absolute, just as in Newtonian physics time is taught absolute time. We will prove it is not true in general. It depends on algorithms. We will prove that forward and mixed stability anlaysis are absolutely invalid stability analysis in the sense that they have absolutely wrong reference points for detecting huge element growth of any algoritms(if any), even an "ideal" or "desirable" backward stability analysis is not so "ideal" or "desirable" in general. Any of forward stable, backward stable and mixed stable algorihms as in Demmel, Kahan , Parlett and other's papers and text books, see Demmel(6) and Higham(8)may not be really stable at all because they may fail to detect and expose any potential instabilities of the algorithm in corresponding stability analysis. Therefore, it is impossible to prove an algorithm is stable according to the standard teachin of today, just as it is impossible to prove a mathematical equuation(Maxwell's) is a law of physics according to the standard teaching in Newtonian physics.

Keywords

Cite

@article{arxiv.1509.02157,
  title  = {Detecting Potential Instabilities of Numerical Algorithms},
  author = {Yao Yang},
  journal= {arXiv preprint arXiv:1509.02157},
  year   = {2015}
}

Comments

This paper has a different perspectives about stability analysis axioms (forward stability, backward stability and mixed stability axioms as in Demmel, Kahan and Parlett's papers and teaching at Berkeley for numerical algorithms

R2 v1 2026-06-22T10:51:09.124Z