Skip to content
DraconiticResearch
Search Sources API
201,683 studies31 sourcesUpdated 55 min ago
PreprintCC BY 4.0arXiv

A candidate proof of the sharp Latala and Strzelecka Gaussian matrix bound

Abstract

We give a candidate proof of Conjecture 5 in the third arXiv version of Latala and Strzelecka Operator lp lq norms of Gaussian matrices.

Related

  1. A Gaussian Chain Rule Proof of the Banach Space Hanson Wright Bound
    Witold Bednorz, Rafal Martynek, Rafal Meller
    arXivPreprintCC BY 4.0Full textProbabilityarXiv
  2. A simpler proof of the Matrix Spencer Theorem
    Nikhil Bansal, Yunbum Kook
    arXivPreprintCC BY 4.0Full textCombinatorics & discrete mathematicsProbabilityarXiv
  3. Instability of Gaussian elimination is exponentially rare (proof of partial result)
    Lloyd N. Trefethen
    arXivPreprintCC BY 4.0Full textNumerical analysis & scientific computingarXiv
  4. Royen's proof of the Gaussian correlation inequality as a supersymmetric dimensional reduction
    Yichao Huang
    arXivPreprintCC BY-NC-ND 4.0Full textMathematical physicsProbabilityarXiv
  5. A Hardy-Space Proof of the Filter-Only Gaussian Feedback-Capacity Formula
    Jun Su, Yang Xu, Guangyue Han
    arXivPreprintCC BY 4.0Full textGeneral mathematicsarXiv
BibTeX
@misc{bednorz2026candidate,
  title = {{A candidate proof of the sharp Latala and Strzelecka Gaussian matrix bound}},
  author = {Witold Bednorz and Rafal Martynek and Rafal Meller},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.22927},
  eprint = {2609.22927},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.22927},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - A candidate proof of the sharp Latala and Strzelecka Gaussian matrix bound
AU  - Witold Bednorz
AU  - Rafal Martynek
AU  - Rafal Meller
PY  - 2026
DA  - 2026/09/19
PB  - arXiv
DO  - 10.48550/arxiv.2609.22927
UR  - https://arxiv.org/abs/2609.22927
AB  - We give a candidate proof of Conjecture 5 in the third arXiv version of Latala and Strzelecka Operator lp lq norms of Gaussian matrices.
ER  -