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Let $R=K[x_{1},x_{2},\cdots, x_{m}]$ where $K$ is a field. In this paper, we give some properties of $n$-matrix factorizations of polynomials in $R$. We also derive some results giving some lower bounds on the number of $n$-matrix factors…

Rings and Algebras · Mathematics 2025-02-11 Yves Fomatati

The approximate degree of a Boolean function is the minimum degree of real polynomial that approximates it pointwise. For any Boolean function, its approximate degree serves as a lower bound on its quantum query complexity, and generically…

Computational Complexity · Computer Science 2023-05-23 Mark Bun , Nadezhda Voronova

We present a randomized quantum algorithm for polynomial factorization over finite fields. For polynomials of degree $n$ over a finite field $\F_q$, the average-case complexity of our algorithm is an expected $O(n^{1 + o(1)} \log^{2 +…

Symbolic Computation · Computer Science 2018-12-14 Javad Doliskani

The $N$th power of a polynomial matrix of fixed size and degree can be computed by binary powering as fast as multiplying two polynomials of linear degree in~$N$. When Fast Fourier Transform (FFT) is available, the resulting complexity is…

Symbolic Computation · Computer Science 2023-05-29 Alin Bostan , Vincent Neiger , Sergey Yurkevich

It is known that there is no EPTAS for the $m$-dimensional knapsack problem unless $W[1] = FPT$. It is true already for the case, when $m = 2$. But, an FPTAS still can exist for some other particular cases of the problem. In this note, we…

Computational Complexity · Computer Science 2022-11-30 D. V. Gribanov

In a sequence of seminal results in the 80's, Kaltofen showed that the complexity class VP is closed under taking factors. A natural question in this context is to understand if other natural classes of multivariate polynomials, for…

Computational Complexity · Computer Science 2018-03-19 Chi-Ning Chou , Mrinal Kumar , Noam Solomon

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

The polynomial method and the Ambainis's lower bound (or \emph{Alb}, for short) method are two main quantum lower bound techniques. While recently Ambainis showed that the polynomial method is not tight, the present paper aims at studying…

Quantum Physics · Physics 2007-05-23 Shengyu Zhang

We extend the Ax-Katz theorem for a single polynomial from finite fields to the rings Z_m with m composite. This extension not only yields the analogous result, but gives significantly higher divisibility bounds. We conjecture what computer…

Computational Complexity · Computer Science 2014-08-19 Robert L. Surowka , Kenneth W. Regan

The Planar Graph Metric Compression Problem is to compactly encode the distances among $k$ nodes in a planar graph of size $n$. Two na\"ive solutions are to store the graph using $O(n)$ bits, or to explicitly store the distance matrix with…

Data Structures and Algorithms · Computer Science 2017-03-16 Amir Abboud , Pawel Gawrychowski , Shay Mozes , Oren Weimann

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

This paper studies the fundamental limits of reinforcement learning (RL) in the challenging \emph{partially observable} setting. While it is well-established that learning in Partially Observable Markov Decision Processes (POMDPs) requires…

Machine Learning · Computer Science 2023-02-03 Fan Chen , Huan Wang , Caiming Xiong , Song Mei , Yu Bai

Given a polynomial $f$ and a semi-algebraic set $S$, we provide a symbolic algorithm to find the equations and inequalities defining a semi-algebraic set $Q$ which is identical to the closure of the image of $S$ under $f$, i.e.,…

Algebraic Geometry · Mathematics 2022-10-26 Ngoc Hoang Anh Mai

We define and study the complexity of robust polynomials for Boolean functions and the related fault-tolerant quantum decision trees, where input bits are perturbed by noise. We compare several different possible definitions. Our main…

Quantum Physics · Physics 2007-05-23 Harry Buhrman , Ilan Newman , Hein Roehrig , Ronald de Wolf

We give the first non-trivial upper bounds on the average sensitivity and noise sensitivity of polynomial threshold functions. More specifically, for a Boolean function f on n variables equal to the sign of a real, multivariate polynomial…

Computational Complexity · Computer Science 2014-03-28 Prahladh Harsha , Adam Klivans , Raghu Meka

The approximate degree of a Boolean function $f\colon\{0,1\}^n\to\{0,1\}$ is the minimum degree of a real polynomial $p$ that approximates $f$ pointwise: $|f(x)-p(x)|\leq1/3$ for all $x\in\{0,1\}^n.$ For every $\delta>0,$ we construct CNF…

Computational Complexity · Computer Science 2022-09-07 Alexander A. Sherstov

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

We prove an asymptotically tight bound (asymptotic with respect to the number of polynomials for fixed degrees and number of variables) on the number of semi-algebraically connected components of the realizations of all realizable sign…

Combinatorics · Mathematics 2009-07-14 Saugata Basu , Richard Pollack , Marie-Francoise Roy

The existence of string functions, which are not polynomial time computable, but whose graph is checkable in polynomial time, is a basic assumption in cryptography. We prove that in the framework of algebraic complexity, there are no such…

Computational Complexity · Computer Science 2018-12-18 Peter Bürgisser

Let $\{w_{i,j}\}_{1\leq i\leq n, 1\leq j\leq s} \subset L_m=F(X_1,...,X_m)[{\partial \over \partial X_1},..., {\partial \over \partial X_m}]$ be linear partial differential operators of orders with respect to ${\partial \over \partial…

Symbolic Computation · Computer Science 2007-05-23 Dima Grigoriev