Lower Bounds for Bit Pigeonhole Principles in Bounded-Depth Resolution over Parities
Abstract
We prove lower bounds for proofs of the bit pigeonhole principle (BPHP) and its generalizations in bounded-depth resolution over parities (Res()). For weak BPHPnm with m = cn pigeons (for any constant c>1) and n holes, for all ε>0, we prove that any depth N1.5 - ε proof in Res() must have exponential size, where N = cn n is the number of variables. Inspired by recent work in TFNP on multicollision-finding, we consider a generalization of the bit pigeonhole principle, denoted t-BPHPnm, asserting that there is a map from [m] to [n] (m > (t-1)n) such that each i ∈ [n] has fewer than t preimages. We prove that any depth N2-1/t-ε proof in Res() of t-BPHPnctn (for any constant c ≥ 1) must have exponential size. For the usual bit pigeonhole principle, we show that any depth N2-ε Res() proof of BPHPnn+1 must have exponential size. As a byproduct of our proof, we obtain that any randomized parity decision tree for the collision-finding problem with n+1 pigeons and n holes must have depth (n), which matches the upper bound coming from a deterministic decision tree. We also prove a lifting theorem for bounded-depth Res() with a constant size gadget which lifts from (p, q)-DT-hardness, recently defined by Bhattacharya and Chattopadhyay. By combining our lifting theorem with the ((n), (n))-DT-hardness of the n-variate Tseitin contradiction over a suitable expander, proved by Bhattacharya and Chattopadhyay, we obtain an N-variate constant-width unsatisfiable CNF formula with O(N) clauses for which any depth N2-ε Res() proof requires size ((Nε)). Previously no superpolynomial lower bounds were known for Res() proofs when the depth is superlinear in the size of the formula.
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