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PreprintCC BY 4.0arXiv

Instability of Gaussian elimination is exponentially rare (proof of partial result)

Abstract

Gaussian elimination with partial pivoting is the standard algorithm for solving a dense n× n system of linear equations Ax=b. The ``growth factor'' ρ for this process may be as large as 2n−1, and when ρ is large, the algorithm is unstable. Nevertheless, long experience has shown that Gaussian elimination is resoundingly stable in practice. Experiments indicate that among random matrices with independent normally distributed entries, growth factors ρ≫ n1/2 are in a precise sense exponentially rare. Here we take a step toward confirming this observation by proving it not for the full growth factor, which depends on all the entries of the upper-triangular factor U, but for the corner entry unn.

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BibTeX
@misc{trefethen2026instability,
  title = {{Instability of Gaussian elimination is exponentially rare (proof of partial result)}},
  author = {Lloyd N. Trefethen},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.04761},
  eprint = {2610.04761},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.04761},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Instability of Gaussian elimination is exponentially rare (proof of partial result)
AU  - Lloyd N. Trefethen
PY  - 2026
DA  - 2026/10/03
PB  - arXiv
DO  - 10.48550/arxiv.2610.04761
UR  - https://arxiv.org/abs/2610.04761
AB  - Gaussian elimination with partial pivoting is the standard algorithm for solving a dense n× n system of linear equations Ax=b. The ``growth factor'' ρ for this process may be as large as 2^n−1, and when ρ is large, the algorithm is unstable. Nevertheless, long experience has shown that Gaussian elimination is resoundingly stable in practice. Experiments indicate that among random matrices with independent normally distributed entries, growth factors ρ≫ n^1/2 are in a precise sense exponentially rare. Here we take a step toward confirming this observation by proving it not for the full growth factor, which depends on all the entries of the upper-triangular factor U, but for the corner entry u_nn^.
ER  -