In this work, we establish the strongest known lower bounds against QAC0, while allowing its full power of polynomially many ancillae and gates. Our two main results show that: (1) Depth 3 QAC0 circuits cannot compute PARITY regardless of size, and require at least Ω(exp(√n)) many gates to compute MAJORITY. (2) Depth 2 circuits cannot approximate high-influence Boolean functions (e.g., PARITY) with non-negligible advantage, regardless of size.

Abstract In a Merlin–Arthur proof system, the proof verifier (Arthur) accepts valid proofs (from Merlin) with probability 1, and rejects invalid proofs with probability arbitrarily close to 1. The running time of such a system is defined to be the length of Merlin’s proof plus the running time of Arthur. We provide new Merlin–Arthur proof systems for some key problems in fine-grained complexity. In several cases our proof systems have optimal running time. Our main results include: Certifying that a list ofnintegers has no 3-SUM solution can be done in Merlin–Arthur time $$\tilde{O}(n)$$ O~(n) . Previously, Carmosino et al. [ITCS 2016] showed that the problem has a nondeterministic algorithm running in $$\tilde{O}(n^{1.5})$$ O~(n1.5) time (that is, there is a proof system with proofs of length $$\tilde{O}(n^{1.5})$$ O~(n1.5) and a deterministic verifier running in $$\tilde{O}(n^{1.5})$$ O~(n1.5) time). Counting the number ofk-cliques with total edge weight equal to zero in ann-node graph can be done in Merlin–Arthur time $${\tilde{O}}(n^{\lceil k/2\rceil })$$ O~(n⌈k/2⌉) (where $$k\ge 3$$ k≥3 ). For oddk, this bound can be further improved for sparse graphs: for example, counting the number of zero-weight triangles in anm-edge graph can be done in Merlin–Arthur time $${\tilde{O}}(m)$$ O~(m) . Previous Merlin–Arthur protocols by Williams [CCC’16] and Björklund and Kaski [PODC’16] could only countk-cliques in unweighted graphs, and had worse running times for smallk. Computing the All-Pairs Shortest Distances matrix for ann-node graph can be done in Merlin–Arthur time $$\tilde{O}(n^2)$$ O~(n2) . Note this is optimal, as the matrix can have $$\Omega (n^2)$$ Ω(n2) nonzero entries in general. Previously, Carmosino et al. [ITCS 2016] showed that this problem has an $$\tilde{O}(n^{2.94})$$ O~(n2.94) nondeterministic time algorithm. Certifying that ann-variablek-CNF is unsatisfiable can be done in Merlin–Arthur time $$2^{n/2 - n/O(k)}$$ 2n/2-n/O(k) . We also observe an algebrization barrier for the previous $$2^{n/2}\cdot \textrm{poly}(n)$$ 2n/2·poly(n) -time Merlin–Arthur protocol of R. Williams [CCC’16] for $$\#$$ # SAT: in particular, his protocol algebrizes, and we observe there is no algebrizing protocol fork-UNSAT running in $$2^{n/2}/n^{\omega (1)}$$ 2n/2/nω(1) time. Therefore we have to exploit non-algebrizing properties to obtain our new protocol. Certifying a Quantified Boolean Formula is true can be done in Merlin–Arthur time $$2^{4n/5}\cdot \textrm{poly}(n)$$ 24n/5·poly(n) . Previously, the only nontrivial result known along these lines was an Arthur–Merlin–Arthur protocol (where Merlin’s proof depends on some of Arthur’s coins) running in $$2^{2n/3}\cdot \textrm{poly}(n)$$ 22n/3·poly(n) time. Due to the centrality of these problems in fine-grained complexity, our results have consequences for many other problems of interest. For example, our work implies that certifying there is no Subset Sum solution tonintegers can be done in Merlin–Arthur time $$2^{n/3}\cdot \textrm{poly}(n)$$ 2n/3·poly(n)