Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 71 tok/s
Gemini 2.5 Pro 46 tok/s Pro
GPT-5 Medium 27 tok/s Pro
GPT-5 High 30 tok/s Pro
GPT-4o 93 tok/s Pro
Kimi K2 207 tok/s Pro
GPT OSS 120B 460 tok/s Pro
Claude Sonnet 4.5 36 tok/s Pro
2000 character limit reached

On sparse random combinatorial matrices (2010.07648v1)

Published 15 Oct 2020 in math.CO and math.PR

Abstract: Let $Q_{n,d}$ denote the random combinatorial matrix whose rows are independent of one another and such that each row is sampled uniformly at random from the subset of vectors in ${0,1}n$ having precisely $d$ entries equal to $1$. We present a short proof of the fact that $\Pr[\det(Q_{n,d})=0] = O\left(\frac{n{1/2}\log{3/2} n}{d}\right)=o(1)$, whenever $d=\omega(n{1/2}\log{3/2} n)$. In particular, our proof accommodates sparse random combinatorial matrices in the sense that $d = o(n)$ is allowed. We also consider the singularity of deterministic integer matrices $A$ randomly perturbed by a sparse combinatorial matrix. In particular, we prove that $\Pr[\det(A+Q_{n,d})=0]=O\left(\frac{n{1/2}\log{3/2} n}{d}\right)$, again, whenever $d=\omega(n{1/2}\log{3/2} n)$ and $A$ has the property that $(1,-d)$ is not an eigenpair of $A$.

Citations (4)

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.