Algorithms and certificates for Boolean CSP refutation: smoothed is no harder than random

We present an algorithm for strongly refuting smoothed instances of all Boolean CSPs. The smoothed model is a hybrid between worst and average-case input models, where the input is an arbitrary instance of the CSP with only the negation patterns of the literals re-randomized with some small probability. For an n-variable smoothed instance of a k-arity CSP, our algorithm runs in n^O(ℓ) time, and succeeds with high probability in bounding the optimum fraction of satisfiable constraints away from 1, provided that the number of constraints is at least Õ(n) (n/ell)^(k/2 - 1). This matches, up to polylogarithmic factors in n, the trade-off between running time and the number of constraints of the state-of-the-art algorithms for refuting fully random instances of CSPs.