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Proof Verification and the Hardness of Approximation Problems

Summary: Proof Verification and the Hardness of
Approximation Problems
Sanjeev Arora # Carsten Lund + Rajeev Motwani #
Madhu Sudan § Mario Szegedy ¶
We show that every language in NP has a probablistic verifier that checks mem­
bership proofs for it using logarithmic number of random bits and by examining a
constant number of bits in the proof. If a string is in the language, then there exists
a proof such that the verifier accepts with probability 1 (i.e., for every choice of its
random string). For strings not in the language, the verifier rejects every provided
``proof" with probability at least 1/2. Our result builds upon and improves a recent
result of Arora and Safra [6] whose verifiers examine a nonconstant number of bits
in the proof (though this number is a very slowly growing function of the input
As a consequence we prove that no MAX SNP­hard problem has a polynomial
time approximation scheme, unless NP=P. The class MAX SNP was defined by Pa­
padimitriou and Yannakakis [82] and hard problems for this class include vertex
cover, maximum satisfiability, maximum cut, metric TSP, Steiner trees and shortest
superstring. We also improve upon the clique hardness results of Feige, Goldwasser,
Lovász, Safra and Szegedy [42], and Arora and Safra [6] and shows that there exists


Source: Arora, Sanjeev - Department of Computer Science, Princeton University


Collections: Computer Technologies and Information Sciences