Exponentially-Hard Gap-CSP and Local PRG via Local Hardcore Functions

Abstract

The gap-ETH assumption (Dinur 2016; Manurangsi and Raghavendra 2016) asserts that it is exponentially-hard to distinguish between a satisfiable 3-CNF formula and a 3-CNF formula which is at most 0.99-satisfiable. We show that this assumption follows from the exponential hardness of finding a satisfying assignment for smooth 3-CNFs. Here smoothness means that the number of satisfying assignments is not much smaller than the number of almost-satisfying assignments. We further show that the latter (smooth-ETH) assumption follows from the exponential hardness of solving constraint satisfaction problems over well-studied distributions, and, more generally, from the existence of any exponentially-hard locally-computable one-way function. This confirms a conjecture of Dinur (ECCC 2016).We also prove an analogous result in the cryptographic setting. Namely, we show that the existence of exponentially-hard locally-computable pseudorandom generator with linear stretch (el-PRG) follows from the existence of an exponentially-hard locally-computable almost regular one-way functions.None of the above assumptions (gap-ETH and el-PRG) was previously known to follow from the hardness of a search problem. Our results are based on a new construction of general (GL-type) hardcore functions that, for any exponentially-hard one-way function, output linearly many hardcore bits, can be locally computed, and consume only a linear amount of random bits. We also show that such hardcore functions have several other useful applications in cryptography and complexity theory.