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Let $ACC \circ THR$ be the class of constant-depth circuits comprised of AND, OR, and MOD$m$ gates (for some constant $m > 1$), with a bottom layer of gates computing arbitrary linear threshold functions. This class of circuits can be seen…

Computational Complexity · Computer Science 2014-01-13 Ryan Williams

We prove the first unconditional consistency result for superpolynomial circuit lower bounds with a relatively strong theory of bounded arithmetic. Namely, we show that the theory V$^0_2$ is consistent with the conjecture that NEXP…

Computational Complexity · Computer Science 2023-08-29 Albert Atserias , Sam Buss , Moritz Müller

One of the prominent current challenges in complexity theory is the attempt to prove lower bounds for $TC^0$, the class of constant-depth, polynomial-size circuits with majority gates. Relying on the results of Williams (2013), an appealing…

Computational Complexity · Computer Science 2017-11-07 Roei Tell

Proving super-polynomial lower bounds against depth-2 threshold circuits of the form THR of THR is a well-known open problem that represents a frontier of our understanding in boolean circuit complexity. By contrast, exponential lower…

Computational Complexity · Computer Science 2017-05-09 Arkadev Chattopadhyay , Nikhil S. Mande

In a recent breakthrough, Chen, Hirahara and Ren prove that $\mathsf{S_2E}/_1 \not\subset \mathsf{SIZE}[2^n/n]$ by giving a single-valued $\mathsf{FS_2P}$ algorithm for the Range Avoidance Problem ($\mathsf{Avoid}$) that works for…

Computational Complexity · Computer Science 2024-04-05 Zeyong Li

The Minimum Circuit Size Problem for Partial Functions ($MCSP^*$) is hard assuming the Exponential Time Hypothesis (ETH) (Ilango, 2020). This breakthrough hardness result leveraged a characterization of the optimal $\{\land, \lor, \neg\}$…

Computational Complexity · Computer Science 2025-11-24 Marco Carmosino , Ngu Dang , Tim Jackman

We introduce a new algebraic proof system, which has tight connections to (algebraic) circuit complexity. In particular, we show that any super-polynomial lower bound on any Boolean tautology in our proof system implies that the permanent…

Computational Complexity · Computer Science 2014-04-16 Joshua A. Grochow , Toniann Pitassi

In order to formally understand the power of neural computing, we first need to crack the frontier of threshold circuits with two and three layers, a regime that has been surprisingly intractable to analyze. We prove the first super-linear…

Computational Complexity · Computer Science 2018-02-01 Daniel M. Kane , Ryan Williams

We introduce the polynomial coefficient matrix and identify maximum rank of this matrix under variable substitution as a complexity measure for multivariate polynomials. We use our techniques to prove super-polynomial lower bounds against…

Computational Complexity · Computer Science 2013-02-15 Mrinal Kumar , Gaurav Maheshwari , Jayalal Sarma M. N

We design new polynomials for representing threshold functions in three different regimes: probabilistic polynomials of low degree, which need far less randomness than previous constructions, polynomial threshold functions (PTFs) with…

Data Structures and Algorithms · Computer Science 2016-08-16 Josh Alman , Timothy M. Chan , Ryan Williams

Agrawal and Vinay [AV08] showed how any polynomial size arithmetic circuit can be thought of as a depth four arithmetic circuit of subexponential size. The resulting circuit size in this simulation was more carefully analyzed by Korian…

Computational Complexity · Computer Science 2017-08-02 Suryajith Chillara , Mrinal Kumar , Ramprasad Saptharishi , V Vinay

We give new bounds on the circuit complexity of the quantum Fourier transform (QFT). We give an upper bound of O(log n + log log (1/epsilon)) on the circuit depth for computing an approximation of the QFT with respect to the modulus 2^n…

Quantum Physics · Physics 2007-05-23 Richard Cleve , John Watrous

Proving that there are problems in $\mathsf{P}^\mathsf{NP}$ that require boolean circuits of super-linear size is a major frontier in complexity theory. While such lower bounds are known for larger complexity classes, existing results only…

Computational Complexity · Computer Science 2023-06-22 Jan Bydzovsky , Jan Krajicek , Igor C. Oliveira

The best known size lower bounds against unrestricted circuits have remained around $3n$ for several decades. Moreover, the only known technique for proving lower bounds in this model, gate elimination, is inherently limited to proving…

Computational Complexity · Computer Science 2020-12-09 Alexander Golovnev , Alexander S. Kulikov , R. Ryan Williams

We show that there is a defining equation of degree at most $\mathsf{poly}(n)$ for the (Zariski closure of the) set of the non-rigid matrices: that is, we show that for every large enough field $\mathbb{F}$, there is a non-zero…

Computational Complexity · Computer Science 2020-11-06 Mrinal Kumar , Ben Lee Volk

We give the first super-polynomial separation in the power of bounded-depth boolean formulas vs. circuits. Specifically, we consider the problem Distance $k(n)$ Connectivity, which asks whether two specified nodes in a graph of size $n$ are…

Computational Complexity · Computer Science 2013-12-03 Benjamin Rossman

We establish new correlation bounds and pseudorandom generators for a collection of computation models. These models are all natural generalizations of structured low-degree $F_2$-polynomials that we did not have correlation bounds for…

Computational Complexity · Computer Science 2025-01-07 Vinayak M. Kumar

We show that the permanent cannot be computed by DLOGTIME-uniform threshold or arithmetic circuits of depth o(log log n) and polynomial size.

Computational Complexity · Computer Science 2009-02-12 Pascal Koiran , Sylvain Perifel

We give several new lower bounds on size of homogeneous non-commutative circuits. We present an explicit homogeneous bivariate polynomial of degree $d$ which requires homogeneous non-commutative circuit of size $\Omega(d/\log d)$. For an…

Computational Complexity · Computer Science 2023-01-05 Prerona Chatterjee , Pavel Hrubeš

In this paper, we investigate computational power of threshold circuits and other theoretical models of neural networks in terms of the following four complexity measures: size (the number of gates), depth, weight and energy. Here the…

Computational Complexity · Computer Science 2023-06-29 Kei Uchizawa , Haruki Abe
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