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Building on the blueprint from Goemans and Williamson (1995) for the Max-Cut problem, we construct a polynomial-time approximation algorithm for orthogonally constrained quadratic optimization problems. First, we derive a semidefinite…

Optimization and Control · Mathematics 2026-03-17 Ryan Cory-Wright , Jean Pauphilet

We show that quantum algorithms can be used to re-prove a classical theorem in approximation theory, Jackson's Theorem, which gives a nearly-optimal quantitative version of Weierstrass's Theorem on uniform approximation of continuous…

Quantum Physics · Physics 2011-03-15 Andrew Drucker , Ronald de Wolf

Exploiting symmetry in Groebner basis computations is difficult when the symmetry takes the form of a group acting by automorphisms on monomials in finitely many variables. This is largely due to the fact that the group elements, being…

Commutative Algebra · Mathematics 2017-10-10 Andries E. Brouwer , Jan Draisma

Semidefinite relaxations are a powerful tool for approximately solving combinatorial optimization problems such as MAX-CUT and the Grothendieck problem. By exploiting a bounded rank property of extreme points in the semidefinite cone, we…

Data Structures and Algorithms · Computer Science 2014-08-12 Roy Frostig , Sida I. Wang

We adopt a continuous model to estimate the Grothendieck constants. An analytical formula to compute the lower bounds of Grothendieck constants has been explicitly derived for arbitrary orders, which improves previous bounds. Moreover, our…

Quantum Physics · Physics 2015-06-23 Bobo Hua , Ming Li , Tinggui Zhang , Chunqin Zhou , Xianqing Li-Jost , Shao-Ming Fei

A theorem is proved concerning approximation of analytic functions by multivariate polynomials in the $s$-dimensional hypercube. The geometric convergence rate is determined not by the usual notion of degree of a multivariate polynomial,…

Numerical Analysis · Mathematics 2016-08-09 Lloyd N. Trefethen

We consider the $(\ell_p,\ell_r)$-Grothendieck problem, which seeks to maximize the bilinear form $y^T A x$ for an input matrix $A$ over vectors $x,y$ with $\|x\|_p=\|y\|_r=1$. The problem is equivalent to computing the $p \to r^*$ operator…

Data Structures and Algorithms · Computer Science 2019-11-07 Vijay Bhattiprolu , Mrinalkanti Ghosh , Venkatesan Guruswami , Euiwoong Lee , Madhur Tulsiani

Decomposition theorems in classical Fourier analysis enable us to express a bounded function in terms of few linear phases with large Fourier coefficients plus a part that is pseudorandom with respect to linear phases. The Goldreich-Levin…

Data Structures and Algorithms · Computer Science 2019-06-14 Madhur Tulsiani , Julia Wolf

The problem of expressing a specific polynomial as the determinant of a square matrix of affine-linear forms arises from algebraic geometry, optimisation, complexity theory, and scientific computing. Motivated by recent developments in this…

Commutative Algebra · Mathematics 2023-09-18 Ada Boralevi , Jasper van Doornmalen , Jan Draisma , Michiel E. Hochstenbach , Bor Plestenjak

Quaternionic polynomials occur naturally in applications of quaternions in science and engineering, and normalization of quaternionic polynomials is a basic manipulation. Once a Groebner basis is certified for the defining ideal I of the…

Symbolic Computation · Computer Science 2025-04-22 Hongbo Li , Zhengyang Wang , Yue Liu , Lei Huang , Changpeng Shao

This paper extends the framework of randomised matrix multiplication to a coarser partition and proposes an algorithm as a complement to the classical algorithm, especially when the optimal probability distribution of the latter one is…

Numerical Analysis · Mathematics 2019-05-20 Yue Wu

Grothendieck's theorem asserts that every continuous linear operator from $\ell_{1}$ to $\ell_{2}$ is absolutely $\left( 1;1\right) $-summing. In this note we prove that the optimal constant $g_{m}$ so that every continuous $m$-linear…

Functional Analysis · Mathematics 2015-10-02 Daniel Pellegrino , Juan B. Seoane-Sepulveda

We show that two important quantities from two disparate areas of complexity theory --- Strassen's exponent of matrix multiplication $\omega$ and Grothendieck's constant $K_G$ --- are intimately related. They are different measures of size…

Computational Complexity · Computer Science 2018-06-07 Jinjie Zhang , Shmuel Friedland , Lek-Heng Lim

The structure of filtered algebras of Grothendieck's differential operators of truncated polynomials in one variable and graded Poisson algebras of their principal symbols is explicitly determined. A related infinitesimal-birational duality…

Algebraic Geometry · Mathematics 2007-05-23 Tomasz Maszczyk

Grothendieck inequalities are fundamental inequalities which are frequently used in many areas of mathematics and computer science. They can be interpreted as upper bounds for the integrality gap between two optimization problems: a…

Optimization and Control · Mathematics 2014-06-03 Jop Briet , Fernando Mario de Oliveira Filho , Frank Vallentin

Arthur Cohn's irreducibility criterion for polynomials with integer coefficients and its generalization connect primes to irreducibles, and integral bases to the variable $x$. As we follow this link, we find that these polynomials are ready…

Number Theory · Mathematics 2018-09-05 Fusun Akman

We survey connections of the Grothendieck inequality and its variants to combinatorial optimization and computational complexity.

Data Structures and Algorithms · Computer Science 2011-08-12 Subhash Khot , Assaf Naor

As part of the search for the value of the smallest upper bound of the best constant for the famous Grothendieck inequality, the so-called Grothendieck constant (a hard open problem - unsolved since 1953), we provide a further approach,…

Functional Analysis · Mathematics 2020-10-13 Frank Oertel

We establish results with an arithmetic flavor that generalize the polynomial multidimensional Szemeredi theorem and related multiple recurrence and convergence results in ergodic theory. For instance, we show that in all these statements…

Dynamical Systems · Mathematics 2015-11-19 Nikos Frantzikinakis , Bernard Host

The Aaronson-Ambainis conjecture (Theory of Computing '14) says that every low-degree bounded polynomial on the Boolean hypercube has an influential variable. This conjecture, if true, would imply that the acceptance probability of every…

Quantum Physics · Physics 2022-03-02 Nikhil Bansal , Makrand Sinha , Ronald de Wolf