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arxiv: 2604.24087 · v1 · submitted 2026-04-27 · 🧮 math.NA · cs.NA

Submatrices with the best-bounded inverses: an asymptotically tight upper bound for mathbb{C}^(n times 2)

Pith reviewed 2026-05-08 02:14 UTC · model grok-4.3

classification 🧮 math.NA cs.NA
keywords submatrix selectionbounded inverseorthonormal columnsspectral normcomplex matricesasymptotically tight boundnumerical linear algebra
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The pith

Any complex n by 2 matrix with orthonormal columns has a 2 by 2 submatrix whose inverse has spectral norm bounded by a constant independent of n.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper proves that for any complex matrix with n rows and exactly two orthonormal columns, there always exists a choice of two rows such that the resulting 2 by 2 submatrix has an inverse whose spectral norm is bounded above by a fixed constant that does not depend on n. This bound is shown to be asymptotically tight, meaning it cannot be replaced by a substantially smaller number for large n. A sympathetic reader cares because the result guarantees the existence of a small, stably invertible submatrix inside arbitrarily tall thin data matrices, which supports reliable numerical computations such as row selection or preconditioning without the conditioning deteriorating as height grows. The work completes the complex case of a 1997 hypothesis after the real case was settled recently.

Core claim

The authors establish that for an arbitrary complex n by 2 matrix A whose columns are orthonormal, the quantity min over all pairs of rows of the spectral norm of the inverse of the corresponding 2 by 2 submatrix is bounded above by a constant depending only on the number of columns and not on n, and that this upper bound is asymptotically tight.

What carries the argument

The best-bounded inverse 2 by 2 submatrix, defined as the submatrix formed by selecting the two rows that minimize the spectral norm of its inverse.

Load-bearing premise

The two columns must be exactly orthonormal and the bound concerns only the spectral norm of the inverse.

What would settle it

A counterexample would be an explicit family of complex n by 2 matrices with orthonormal columns, for arbitrarily large n, in which every possible 2 by 2 submatrix has an inverse whose spectral norm exceeds the stated upper bound.

read the original abstract

The long-standing hypothesis formulated by Goreinov, Tyrtyshnikov and Zamarashkin \cite{GTZ1997} has recently been solved affirmatively in the case of real two-column matrices by Sengupta and Pautov \cite{SP2026}. In this paper, we consider the complex variant of this problem and prove the asymptotically tight upper bound for spectral norms of the best-bounded inverse $2 \times 2$ submatrices of an arbitrary complex $n \times 2$ matrix with orthonormal columns.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

0 major / 2 minor

Summary. The paper claims to prove an asymptotically tight upper bound for the spectral norms of the best-bounded inverse 2×2 submatrices of arbitrary complex n×2 matrices with orthonormal columns, extending the real case solved by Sengupta and Pautov. The argument reduces the problem to a trigonometric optimization over the Grassmannian, derives the bound using Jensen-type inequalities on complex phases, and provides a matching asymptotic lower bound via a phased Vandermonde-type construction.

Significance. If correct, this resolves the complex variant of the Goreinov-Tyrtyshnikov-Zamarashkin hypothesis for the two-column case. The elementary, self-contained proof and the explicit matching lower bound construction are strengths that make the result a solid contribution to numerical linear algebra and matrix theory.

minor comments (2)
  1. [Abstract] Abstract: The abstract refers to 'the asymptotically tight upper bound' without stating its explicit form or the leading constant; adding this would help readers immediately assess the result.
  2. [Main argument] The reduction step to trigonometric optimization over the Grassmannian (mentioned in the proof sketch) would benefit from an explicit parametrization of the complex phases in the first paragraph of the main argument section.

Simulated Author's Rebuttal

0 responses · 0 unresolved

We thank the referee for the positive assessment of our manuscript, the recognition that it resolves the complex variant of the Goreinov-Tyrtyshnikov-Zamarashkin hypothesis for the two-column case, and the recommendation for minor revision. We appreciate the note that the elementary proof and explicit lower-bound construction are strengths.

Circularity Check

0 steps flagged

No significant circularity; self-contained proof

full rationale

The manuscript derives the asymptotically tight bound for the complex case via an explicit reduction to trigonometric optimization on the Grassmannian, application of Jensen-type inequalities to phase terms, and a deterministic Vandermonde-style construction for the matching lower bound. All steps are elementary, parameter-free, and independent of any fitted quantities or prior self-citations; the cited real-case result of Sengupta-Pautov serves only as historical context and is not load-bearing for the complex extension. No equation reduces to a redefinition or renaming of its own inputs.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The proof relies on standard definitions of the spectral norm, orthonormality over C, and the existence of 2-row submatrices; no new entities or fitted constants are introduced.

axioms (2)
  • standard math Spectral norm is the largest singular value of a matrix.
    Invoked when defining the bounded-inverse property.
  • domain assumption Columns of the n x 2 matrix are orthonormal, i.e., A^* A = I_2.
    Stated in the problem setup.

pith-pipeline@v0.9.0 · 5387 in / 1203 out tokens · 41619 ms · 2026-05-08T02:14:05.001181+00:00 · methodology

discussion (0)

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Reference graph

Works this paper leans on

6 extracted references · 2 canonical work pages · 1 internal anchor

  1. [1]

    Berman and R

    A. Berman and R. J. Plemmons.Nonnegative Matrices in the Mathematical Sciences. Classics in Applied Mathematics 9. SIAM, 1994

  2. [2]

    Goreinov, E.E

    S.A. Goreinov, E.E. Tyrtyshnikov, and N.L. Zamarashkin. A theory of pseudo-skeleton approximations.Linear Algebra Appl., 261:1–21, 1997

  3. [3]

    Hausmann and A

    J.-C. Hausmann and A. Knutson. Polygon spaces and grassmannians.L’Enseignement math´ ematique, 43:173–198, 1997

  4. [4]

    R. A. Horn and C. R. Johnson.Matrix Analysis. Cambridge University Press, 2nd edition, 2012

  5. [5]

    Nesterenko

    Yu. Nesterenko. Submatrices with the best-bounded inverses: StudyingR n×2 andC n×2. ArXiv, 2408.16631, 2024

  6. [6]

    On the submatrices with the best-bounded inverses

    R. Sengupta and M. Pautov. On the submatrices with the best-bounded inverses.ArXiv, 2604.05944, 2026. Email address:yuri.r.nesterenko@gmail.com