New Limits to Classical and Quantum Instance Compression

  • Authors:
  • Andrew Drucker

  • Affiliations:
  • -

  • Venue:
  • FOCS '12 Proceedings of the 2012 IEEE 53rd Annual Symposium on Foundations of Computer Science
  • Year:
  • 2012

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Abstract

Given an instance of a hard decision problem, a limited goal is to \emph{compress} that instance into a smaller, equivalent instance of a second problem. As one example, consider the problem where, given Boolean formulas $\psi^1, \ldots, \psi^t$, we must determine if at least one $\psi^j$ is satisfiable. An \emph{$\mathrm{OR}$-compression scheme} for SAT is a polynomial-time reduction that maps $(\psi^1, \ldots, \psi^t)$ to a string $z$, such that $z$ lies in some ``target'' language $L'$ if and only if $\bigvee_j [\psi^j \in \mathrm{SAT}]$ holds. (Here, $L'$ can be arbitrarily complex.) AND-compression schemes are defined similarly. A compression scheme is \emph{strong} if $|z|$ is polynomially bounded in $n = \max_j |\psi^j|$, independent of $t$. Strong compression for SAT seems unlikely. Work of Harnik and Naor (FOCS '06/SICOMP '10) and Bodlaender, Downey, Fellows, and Hermelin (ICALP '08/JCSS '09) showed that the infeasibility of strong OR-compression for SAT would show limits to instance compression for a large number of natural problems. Bodlaender et al. also showed that the infeasibility of strong AND-compression for SAT would have consequences for a different list of problems. Motivated by this, Fort now and Santhanam (STOC '08/JCSS '11) showed that if SAT is strongly OR-compressible, then $\mathsf{NP} \subseteq \mathsf{coNP/poly}$. Finding similar evidence against AND-compression was left as an open question. We provide such evidence: we show that strong AND- \emph{or} OR-compression for SAT would imply \emph{non-uniform, statistical zero-knowledge proofs} for SAT -- an even stronger and more unlikely consequence than $\mathsf{NP} \subseteq \mathsf{coNP/poly}$. Our method applies against \emph{probabilistic} compression schemes of sufficient ``quality'' with respect to the reliability and compression amount (allowing for tradeoff). This greatly strengthens the evidence given by Fort now and Santhanam against probabilistic OR-compression for SAT. We also give variants of these results for the analogous task of \emph{quantum instance compression}, in which a polynomial-time quantum reduction must output a quantum state that, in an appropriate sense, ``preserves the answer'' to the input instance. The central idea in our proofs is to exploit the information bottleneck in an AND-compression scheme for a language $L$ in order to fool a cheating prover in a proof system for $\over line{L}$. Our key technical tool is a new method to ``disguise'' information being fed into a compressive mapping, we believe this method may find other applications.