Revised: December 28, 2021

Published: December 5, 2023

**Keywords:**circuit complexity, lower bounds, shrinkage, formulas, formula complexity, KRW conjecture

**Categories:**complexity, circuit complexity, lower bounds, shrinkage, formulas, formula complexity, KRW conjecture

**ACM Classification:**F.1.1

**AMS Classification:**68Q06

**Abstract:**
[Plain Text Version]

Håstad showed that any De Morgan formula (composed of AND, OR and NOT gates) shrinks by a factor of $\widetilde{O}(p^{2})$ under a random restriction that leaves each variable alive independently with probability $p$ [SICOMP, 1998]. Using this result, he gave an $\widetilde{\Omega}(n^{3})$ formula size lower bound for the Andreev function, which, up to lower order improvements, remains the state-of-the-art lower bound for any explicit function.

In this paper, we extend the shrinkage result of Håstad to hold under a far wider family of random restrictions and their generalization — random projections. Based on our shrinkage results, we obtain an $\widetilde{\Omega}(n^{3})$ formula size lower bound for an explicit function computable in $\ACz$. This improves upon the best known formula size lower bounds for $\ACz$, that were only quadratic prior to our work. In addition, we prove that the KRW conjecture [Karchmer et al., Computational Complexity 5(3/4), 1995] holds for inner functions for which the unweighted quantum adversary bound is tight. In particular, this holds for inner functions with a tight Khrapchenko bound.

Our random projections are tailor-made to the function's structure so that the function maintains structure even under projection — using such projections is necessary, as standard random restrictions simplify $\ACz$ circuits. In contrast, we show that any De Morgan formula shrinks by a quadratic factor under our random projections, allowing us to prove the cubic lower bound.

Our proof techniques build on Håstad's proof for the simpler case of balanced formulas. This allows for a significantly simpler proof at the cost of slightly worse parameters. As such, when specialized to the case of $p$-random restrictions, our proof can be used as an exposition of Håstad's result.

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An extended abstract of this article appeared in the Proceeding of the 12th Innovations in Theoretical Computer Science Conference (ITCS'21).