Target-Dependent Local Verification: Information--Proof-Length Tradeoffs

2026-08-22

AI Summary

本文研究了依赖目标的局部验证方法，探讨信息与证明长度之间的权衡，通过VC维和编码理论提供了一种新的分析框架。

Abstract

We study fixed-layout local verification with target-dependent local tests. Let $M$ be a random variable on $\{0,1\}^K$, and let $S$ record the test selected at each coordinate. For each $s\in\operatorname{supp}(S)$, let $F_s$ be the corresponding target fiber and set $D_{\mathrm{fib}}=\max_s\operatorname{VCdim}(F_s)$. We prove $H(M\mid S)\le \log_2\!\left(\sum_{j=0}^{D_{\mathrm{fib}}}\binom Kj\right)$. A fiber that shatters $d$ coordinates yields a weak relaxed locally decodable code with message length $d$ and block length $d+P$ over the original proof alphabet. For a uniform $K$-bit target and fixed proof alphabet, $Q$, and $σ$, the Goldberg--Gur--Saraogi lower bound implies that $I(M;S)\leγK$, for fixed $γ<1$, forces $P=Ω\!\left(K^{1+1/a}/(\log K)^{2+2/a}\right)$, where $a=\lceil Q/σ\rceil$. If $P\le K(\log K)^c$, then $I(M;S)\ge K-O\!\left(K^{a/(a+1)}(\log K)^{3+ac/(a+1)}\right)=K-o(K)$. Any discrete verifier state $T$ determining $S$ satisfies the same information lower bound. Bounded-randomness adaptive branches can be simulated nonadaptively by exposing their decision trees. A branch using at most $r$ random bits and $q$ adaptive proof queries yields a decoder with perfect completeness and at most $1+2^{r+1}\sum_{j<q}A^j$ queries. Under $I(M;S)\leγK$, near-linear proof length requires this quantity to be $Ω(\log K/\log\log K)$; the binary one-query case gives $P=2^{Ω(K)}$. Applied to a global list-sound dPCP interface of Gur--Minzer--Weissenberg--Zheng, our bound shows that a fixed target-independent menu of $L$ test profiles must satisfy $\log_2L\ge K-o(K)$. Proof-dependent lists and additional target-dependent selection data must be included in the measured state.

Problem

• local verification
• information-proof length tradeoffs
• VC dimension
• locally decodable codes
• proof length

Innovation

• target-dependent local verification
• information-proof length tradeoffs
• VC dimension
• relaxed locally decodable codes
• adaptive branches