Papers
Topics
Authors
Recent
Detailed Answer
Quick Answer
Concise responses based on abstracts only
Detailed Answer
Well-researched responses based on abstracts and relevant 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 62 tok/s
Gemini 2.5 Pro 53 tok/s Pro
GPT-5 Medium 17 tok/s Pro
GPT-5 High 13 tok/s Pro
GPT-4o 101 tok/s Pro
Kimi K2 217 tok/s Pro
GPT OSS 120B 474 tok/s Pro
Claude Sonnet 4 36 tok/s Pro
2000 character limit reached

Schwartz-Zippel for multilinear polynomials mod N (2204.05037v2)

Published 11 Apr 2022 in cs.DM, cs.CR, and cs.DS

Abstract: We derive a tight upper bound on the probability over $\mathbf{x}=(x_1,\dots,x_\mu) \in \mathbb{Z}\mu$ uniformly distributed in $ [0,m)\mu$ that $f(\mathbf{x}) = 0 \bmod N$ for any $\mu$-linear polynomial $f \in \mathbb{Z}[X_1,\dots,X_\mu]$ co-prime to $N$. We show that for $N=p_1{r_1},...,p_\ell{r_\ell}$ this probability is bounded by $\frac{\mu}{m} + \prod_{i=1}\ell I_{\frac{1}{p_i}}(r_i,\mu)$ where $I$ is the regularized beta function. Furthermore, we provide an inverse result that for any target parameter $\lambda$ bounds the minimum size of $N$ for which the probability that $f(\mathbf{x}) \equiv 0 \bmod N$ is at most $2{-\lambda} + \frac{\mu}{m}$. For $\mu =1$ this is simply $N \geq 2\lambda$. For $\mu \geq 2$, $\log_2(N) \geq 8 \mu{2}+ \log_2(2 \mu)\cdot \lambda$ the probability that $f(\mathbf{x}) \equiv 0 \bmod N$ is bounded by $2{-\lambda} +\frac{\mu}{m}$. We also present a computational method that derives tighter bounds for specific values of $\mu$ and $\lambda$. For example, our analysis shows that for $\mu=20$, $\lambda = 120$ (values typical in cryptography applications), and $\log_2(N)\geq 416$ the probability is bounded by $ 2{-120}+\frac{20}{m}$. We provide a table of computational bounds for a large set of $\mu$ and $\lambda$ values.

Citations (7)

Summary

We haven't generated a summary 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.

Lightbulb On Streamline Icon: https://streamlinehq.com

Continue Learning

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

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube