VibeMathedMath problems solved by AI

Bombari's Question on Sign-Quantized Linear Maps

A dimension-independent subgaussian concentration bound for Gaussian vectors under coordinate-wise nonlinear maps, valid for any bounded function under a well-conditioned covariance, which answers a question of Simone Bombari on sign quantization.

Result
Proved
Status
Resolved
AI contribution
AI-discovered
Method
Argument
Field
Probability
Posed by
Simone Bombari
Year posed
Years open
Solved
2026-05-26
Model
Gemini 3.5 Flash
Vendor
Google
Collaborators
Guangyi Zou, Roman Vershynin
Verification
Unreviewed
Publication
Preprint
Significance
10 / 100
Disclosed cost
Wikipedia
No dedicated article

What the AI did

The abstract states the result was discovered by Gemini 3.5 Flash, and the title calls the paper an AI-assisted note. Worth recording that a small fast model, not a frontier reasoning tier, produced it.

Verification

Short arXiv note; not yet peer-reviewed.

Source

arXiv:2605.27563 - On the Subgaussianity of Quantized Linear Maps: An AI-Assisted Note

Discussion