Abstract
This paper continues the investigation of the connection between probabilistically checkable proofs (PCPs) and the approximability of NP-optimization problems. The emphasis is on proving tight nonapproximability results via consideration of measures such as the "free-bit complexity" and the "amortized free-bit complexity" of proof systems. The first part of the paper presents a collection of new proof systems based on a new error-correcting code called the long code. We provide a proof system that has amortized free-bit complexity of $2 + \epsilon$, implying that approximating MaxClique within $N^{\frac13-\e}$, and approximating the Chromatic Number within $N^{\frac15-\e}$, are hard, assuming $\NP\neq\coRP$, for any e > 0. We also derive the first explicit and reasonable constant hardness factors for Min Vertex Cover, $\MSAT{2}$, and Max Cut, and we improve the hardness factor for $\MSAT{3}$. We note that our nonapproximability factors for $\maxsnp$ problems are appreciably close to the values known to be achievable by polynomial-time algorithms. Finally, we note a general approach to the derivation of strong nonapproximability results under which the problem reduces to the construction of certain "gadgets." The increasing strength of nonapproximability results obtained via the PCP connection motivates us to ask how far this can go and whether PCPs are inherent in any way. The second part of the paper addresses this. The main result is a "reversal" of the connection due to Feige et al. (FGLSS connection) [J. ACM, 43 (1996), pp. 268--292]: where the latter had shown how to translate proof systems for NP into NP-hardness of approximation results for MaxClique, we show how any NP-hardness of approximation result for MaxClique yields a proof system for NP. Roughly, our result says that for any constant f, if MaxClique is NP-hard to approximate within N1(1+f), then $\NP\subseteq \overline{\fpcp}[\log,f]$, the latter being the class of languages possessing proofs of logarithmic randomness and amortized free-bit complexity f. This suggests that PCPs are inherent to obtaining nonapproximability results. Furthermore, the tight relation suggests that reducing the amortized free-bit complexity is necessary for improving the nonapproximability results for MaxClique. The third part of our paper initiates a systematic investigation of the properties of PCP and FPCP (free PCP) as a function of the following various parameters: randomness, query complexity, free-bit complexity, amortized free-bit complexity, proof size, etc. We are particularly interested in triviality results, which indicate which classes are not powerful enough to capture NP. We also distill the role of randomized reductions in this area and provide a variety of useful transformations between proof checking complexity classes.
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