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We study the algorithmic problem of multiplying large matrices that are rectangular. We prove that the method that has been used to construct the fastest algorithms for rectangular matrix multiplication cannot give algorithms with…

Computational Complexity · Computer Science 2025-11-10 Matthias Christandl , François Le Gall , Vladimir Lysikov , Jeroen Zuiddam

The border rank of the matrix multiplication operator for n by n matrices is a standard measure of its complexity. Using techniques from algebraic geometry and representation theory, we show the border rank is at least 2n^2-n. Our bounds…

Computational Complexity · Computer Science 2013-06-04 J. M. Landsberg , Giorgio Ottaviani

We prove new lower bounds on the growth of robust quantum circuit complexity -- the minimal number of gates $C_{\delta}(U)$ to approximate a unitary $U$ up to an error of $\delta$ in operator norm distance. More precisely we show two bounds…

Quantum Physics · Physics 2023-06-05 Jonas Haferkamp

We show a tight lower bound of $\Omega(N \log\log N)$ on the number of transmissions required to compute the parity of $N$ input bits with constant error in a noisy communication network of $N$ randomly placed sensors, each having one input…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-02-10 Chinmoy Dutta , Yashodhan Kanoria , D. Manjunath , Jaikumar Radhakrishnan

The problem of constructing hazard-free Boolean circuits dates back to the 1940s and is an important problem in circuit design. Our main lower-bound result unconditionally shows the existence of functions whose circuit complexity is…

Computational Complexity · Computer Science 2021-01-01 Christian Ikenmeyer , Balagopal Komarath , Christoph Lenzen , Vladimir Lysikov , Andrey Mokhov , Karteek Sreenivasaiah

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

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

This paper focuses on a particular transmission scheme called local network coding, which has been reported to provide significant performance gains in practical wireless networks. The performance of this scheme strongly depends on the…

Networking and Internet Architecture · Computer Science 2015-03-17 Petteri Mannersalo , Georgios S. Paschos , Lazaros Gkatzikis

We establish a generic form of hardness amplification for the approximability of constant-depth Boolean circuits by polynomials. Specifically, we show that if a Boolean circuit cannot be pointwise approximated by low-degree polynomials to…

Computational Complexity · Computer Science 2014-04-29 Mark Bun , Justin Thaler

A monotone Boolean circuit is composed of OR gates, AND gates and input gates corresponding to the input variables and the Boolean constants. It is $q$-multilinear if for each its output gate $o$ and for each prime implicant $s$ of the…

Computational Complexity · Computer Science 2023-05-15 Andrzej Lingas , Mia Persson

Despite the apparent similarity between shared randomness and shared entanglement in the context of Communication Complexity, our understanding of the latter is not as good as of the former. In particular, there is no known "entanglement…

Quantum Physics · Physics 2022-03-29 Dmytro Gavinsky

A subset $\mathcal{C}\subseteq\{0,1,2\}^n$ is said to be a $\textit{trifferent}$ code (of block length $n$) if for every three distinct codewords $x,y, z \in \mathcal{C}$, there is a coordinate $i\in \{1,2,\ldots,n\}$ where they all differ,…

Information Theory · Computer Science 2024-02-06 Siddharth Bhandari , Abhishek Khetan

We prove a lower bound of $\Omega(n^2/\log^2 n)$ on the size of any syntactically multilinear arithmetic circuit computing some explicit multilinear polynomial $f(x_1, \ldots, x_n)$. Our approach expands and improves upon a result of Raz,…

Computational Complexity · Computer Science 2017-11-03 Noga Alon , Mrinal Kumar , Ben Lee Volk

Suppose we have n algorithms, quantum or classical, each computing some bit-value with bounded error probability. We describe a quantum algorithm that uses O(sqrt{n}) repetitions of the base algorithms and with high probability finds the…

Quantum Physics · Physics 2017-01-03 Peter Hoyer , Michele Mosca , Ronald de Wolf

The paper discusses the gate complexity and the depth of reversible circuits consisting of NOT, CNOT and 2-CNOT gates in the case, when the number of additional inputs is limited. We study Shannon's gate complexity function $L(n, q)$ and…

Computational Complexity · Computer Science 2017-03-28 Dmitry V. Zakablukov

We study the power of negation in the Boolean and algebraic settings and show the following results. * We construct a family of polynomials $P_n$ in $n$ variables, all of whose monomials have positive coefficients, such that $P_n$ can be…

Computational Complexity · Computer Science 2025-12-23 Bruno Cavalar , Théo Borém Fabris , Partha Mukhopadhyay , Srikanth Srinivasan , Amir Yehudayoff

Motivated by the resurgence of neural networks in being able to solve complex learning tasks we undertake a study of high depth networks using ReLU gates which implement the function $x \mapsto \max\{0,x\}$. We try to understand the role of…

Computational Complexity · Computer Science 2017-11-10 Anirbit Mukherjee , Amitabh Basu

Additive Fourier Transform is sdudied. A fast multiplication algorithm for polynomials over the binary field is given. The bit complexity of the algorithm is $O(n(log n)(\log\log n)^2)$.

Number Theory · Mathematics 2025-05-15 Chunlei Liu

Koiran showed that if a $n$-variate polynomial of degree $d$ (with $d=n^{O(1)}$) is computed by a circuit of size $s$, then it is also computed by a homogeneous circuit of depth four and of size $2^{O(\sqrt{d}\log(d)\log(s))}$. Using this…

Computational Complexity · Computer Science 2014-05-19 Sébastien Tavenas

We show that any $n$-variate polynomial computable by a syntactically multilinear circuit of size $\operatorname{poly}(n)$ can be computed by a depth-$4$ syntactically multilinear ($\Sigma\Pi\Sigma\Pi$) circuit of size at most…

Computational Complexity · Computer Science 2019-02-20 Mrinal Kumar , Rafael Oliveira , Ramprasad Saptharishi