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Extending the wavenumber-explicit analysis of [Chen & Qiu, J. Comput. Appl. Math. 309 (2017)], we analyze the $L^2$-convergence of a least squares method for the Helmholtz equation with wavenumber $k$. For domains with an analytic boundary,…

Numerical Analysis · Mathematics 2024-07-25 Maximilian Bernkopf , Jens Markus Melenk

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

For any real numbers $B \ge 1$ and $\delta \in (0, 1)$ and function $f: [0, B] \rightarrow \mathbb{R}$, let $d_{B; \delta} (f) \in \mathbb{Z}_{> 0}$ denote the minimum degree of a polynomial $p(x)$ satisfying $\sup_{x \in [0, B]} \big| p(x)…

Computational Complexity · Computer Science 2022-05-13 Amol Aggarwal , Josh Alman

We consider the number of quantum queries required to determine the coefficients of a degree-d polynomial over GF(q). A lower bound shown independently by Kane and Kutin and by Meyer and Pommersheim shows that d/2+1/2 quantum queries are…

Quantum Physics · Physics 2016-09-08 Andrew M. Childs , Wim van Dam , Shih-Han Hung , Igor E. Shparlinski

In this paper, we study polynomial norms, i.e. norms that are the $d^{\text{th}}$ root of a degree-$d$ homogeneous polynomial $f$. We first show that a necessary and sufficient condition for $f^{1/d}$ to be a norm is for $f$ to be strictly…

Optimization and Control · Mathematics 2018-07-18 Amir Ali Ahmadi , Etienne de Klerk , Georgina Hall

Representations of Boolean functions by real polynomials play an important role in complexity theory. Typically, one is interested in the least degree of a polynomial p(x_1,...,x_n) that approximates or sign-represents a given Boolean…

Computational Complexity · Computer Science 2008-05-15 Alexander A. Sherstov

In the complexity estimation for an attack that reduces a cryptosystem to solving a system of polynomial equations, the degree of regularity and an upper bound of the first fall degree are often used in cryptanalysis. While the degree of…

Symbolic Computation · Computer Science 2026-01-22 Shuhei Nakamura

The problem of finding a nontrivial factor of a polynomial f(x) over a finite field F_q has many known efficient, but randomized, algorithms. The deterministic complexity of this problem is a famous open question even assuming the…

Computational Complexity · Computer Science 2019-02-20 Manuel Arora , Gábor Ivanyos , Marek Karpinski , Nitin Saxena

In this paper we associate to each multivariate polynomial $f$ that is homogeneous relative to a subset of its variables a series of polynomial families $P_\lambda (f)$ of $m$-tuples of homogeneous polynomials of equal degree such that the…

Computational Complexity · Computer Science 2017-08-03 Hông Vân Lê

A graph $G$ contains a graph $H$ as a pivot-minor if $H$ can be obtained from $G$ by applying a sequence of vertex deletions and edge pivots. Pivot-minors play an important role in the study of rank-width. Pivot-minors have mainly been…

Cylindrical algebraic decomposition (CAD) is an important tool for working with polynomial systems, particularly quantifier elimination. However, it has complexity doubly exponential in the number of variables. The base algorithm can be…

Symbolic Computation · Computer Science 2016-10-03 Matthew England , James H. Davenport

Many satisfiability modulo theories solvers implement a variant of the DPLL(T ) framework which separates theory-specific reasoning from reasoning on the propositional abstraction of the formula. Such solvers conclude that a formula is…

Logic in Computer Science · Computer Science 2015-06-05 Liana Hadarean , Alex Horn , Tim King

The so-called algebraic approach to the constraint satisfaction problem (CSP) has been a prevalent method of the study of complexity of these problems since early 2000's. The core of this approach is the notion of polymorphisms which…

Logic in Computer Science · Computer Science 2026-05-15 Maximilian Hadek , Tomáš Jakl , Jakub Opršal

We show that every language in NP has a PCP verifier that tosses $O(\log n)$ random coins, has perfect completeness, and a soundness error of at most $1/\text{poly}(n)$, while making at most $O(\text{poly}\log\log n)$ queries into a proof…

Computational Complexity · Computer Science 2018-10-09 Irit Dinur , Prahladh Harsha , Guy Kindler

In this note, we propose a framework for proving computational lower bounds in norm approximation by leveraging a reverse detection--estimation gap. The starting point is a testing problem together with an estimator whose error is…

Statistics Theory · Mathematics 2026-04-07 Runshi Tang , Yuefeng Han , Anru R. Zhang

The approximate degree of a Boolean function $f \colon \{-1, 1\}^n \rightarrow \{-1, 1\}$ is the least degree of a real polynomial that approximates $f$ pointwise to error at most $1/3$. We introduce a generic method for increasing the…

Computational Complexity · Computer Science 2017-03-20 Mark Bun , Justin Thaler

The probabilistic learning on manifolds (PLoM) introduced in 2016 has solved difficult supervised problems for the ``small data'' limit where the number N of points in the training set is small. Many extensions have since been proposed,…

Methodology · Statistics 2021-02-23 Christian Soize , Roger Ghanem

This paper analyzes to what extent it is possible to efficiently reduce the number of clauses in NP-hard satisfiability problems, without changing the answer. Upper and lower bounds are established using the concept of kernelization.…

Computational Complexity · Computer Science 2019-07-01 Bart M. P. Jansen , Astrid Pieterse

We make use of a result of Hurwitz and Reznick, and a consequence of this result due to Fidalgo and Kovacec, to determine a new sufficient condition for a polynomial $f\in\mathbb{R}[X_1,...,X_n]$ of even degree to be a sum of squares. This…

Optimization and Control · Mathematics 2012-11-15 Mehdi Ghasemi , Murray Marshall

Low-degree polynomials have emerged as a powerful paradigm for providing evidence of statistical-computational gaps across a variety of high-dimensional statistical models [Wein25]. For detection problems -- where the goal is to test a…

Machine Learning · Statistics 2026-01-06 Alexandra Carpentier , Simone Maria Giancola , Christophe Giraud , Nicolas Verzelen
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