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It has long been known that any Boolean function that depends on n input variables has both degree and exact quantum query complexity of Omega(log n), and that this bound is achieved for some functions. In this paper we study the case of…

Quantum Physics · Physics 2013-03-26 Andris Ambainis , Ronald de Wolf

Polynomial approximations to boolean functions have led to many positive results in computer science. In particular, polynomial approximations to the sign function underly algorithms for agnostically learning halfspaces, as well as…

Computational Complexity · Computer Science 2014-12-09 Mark Bun , Thomas Steinke

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 prove various theorems on approximation using polynomials with integer coefficients in the Bernstein basis of any given order. In the extreme, we draw the coefficients from $\{ \pm 1\}$ only. A basic case of our results states that for…

Information Theory · Computer Science 2022-12-08 C. Sinan Güntürk , Weilin Li

We study approximation of Boolean functions by low-degree polynomials over the ring $\mathbb{Z}/2^k\mathbb{Z}$. More precisely, given a Boolean function $F:\{0,1\}^n \rightarrow \{0,1\}$, define its $k$-lift to be $F_k:\{0,1\}^n \rightarrow…

Computational Complexity · Computer Science 2020-05-08 Abhishek Bhrushundi , Prahladh Harsha , Srikanth Srinivasan

We study the computation complexity of Boolean functions in the quantum black box model. In this model our task is to compute a function $f:\{0,1\}\to\{0,1\}$ on an input $x\in\{0,1\}^n$ that can be accessed by querying the black box.…

Quantum Physics · Physics 2017-01-25 Andris Ambainis , Janis Iraids

The $\epsilon$-approximate degree $deg_\epsilon(f)$ of a Boolean function $f$ is the least degree of a real-valued polynomial that approximates $f$ pointwise to error $\epsilon$. The approximate degree of $f$ is at least $k$ iff there…

Computational Complexity · Computer Science 2019-06-04 Andrej Bogdanov , Nikhil S. Mande , Justin Thaler , Christopher Williamson

We give two approximation algorithms solving the Stochastic Boolean Function Evaluation (SBFE) problem for symmetric Boolean functions. The first is an $O(\log n)$-approximation algorithm, based on the submodular goal-value approach of…

Data Structures and Algorithms · Computer Science 2022-01-05 Dimitrios Gkenosis , Nathaniel Grammel , Lisa Hellerstein , Devorah Kletenik

In this work, we consider a new type of Fourier-like representation of Boolean function $f\colon\{+1,-1\}^n\to\{+1,-1\}$ \[ f(x) = \cos\left(\pi\sum_{S\subseteq[n]}\phi_S \prod_{i\in S} x_i\right). \] This representation, which we call the…

Quantum Physics · Physics 2019-03-27 Ryuhei Mori

We give a new presentation of the main result of Arunachalam, Bri\"et and Palazuelos (SICOMP'19) and show that quantum query algorithms are characterized by a new class of polynomials which we call Fourier completely bounded polynomials. We…

Quantum Physics · Physics 2023-06-29 Francisco Escudero Gutiérrez

Let X = (x_0,...,x_{n-1})$ be a sequence of n numbers. For \epsilon > 0, we say that x_i is an \epsilon-approximate median if the number of elements strictly less than x_i, and the number of elements strictly greater than x_i are each less…

Quantum Physics · Physics 2007-05-23 Ashwin Nayak , Felix Wu

We make the case for neural network objects and extend an already existing neural network calculus explained in detail in Chapter 2 on \cite{bigbook}. Our aim will be to show that, yes, indeed, it makes sense to talk about neural network…

Machine Learning · Computer Science 2024-02-05 Shakil Rafi , Joshua Lee Padgett , Ukash Nakarmi

In this note, we develop a bounded-error quantum algorithm that makes $\tilde O(n^{1/4}\varepsilon^{-1/2})$ queries to a Boolean function $f$, accepts a monotone function, and rejects a function that is $\varepsilon$-far from being…

Quantum Physics · Physics 2015-03-11 Aleksandrs Belovs , Eric Blais

The vectorial Boolean functions are employed in cryptography to build block coding algorithms. An important criterion on these functions is their resistance to the differential cryptanalysis. Nyberg defined the notion of almost perfect…

Algebraic Geometry · Mathematics 2008-05-02 François Rodier

Let $g: \{-1,1\}^k \to \{-1,1\}$ be any Boolean function and $q_1,\dots,q_k$ be any degree-2 polynomials over $\{-1,1\}^n.$ We give a \emph{deterministic} algorithm which, given as input explicit descriptions of $g,q_1,\dots,q_k$ and an…

Computational Complexity · Computer Science 2013-11-28 Anindya De , Ilias Diakonikolas , Rocco A. Servedio

Polynomial representations of Boolean functions over various rings such as $\mathbb{Z}$ and $\mathbb{Z}_m$ have been studied since Minsky and Papert (1969). From then on, they have been employed in a large variety of fields including…

Computational Complexity · Computer Science 2020-05-04 Xiaoming Sun , Yuan Sun , Jiaheng Wang , Kewen Wu , Zhiyu Xia , Yufan Zheng

The sensitivity of a Boolean function f is the maximum over all inputs x, of the number of sensitive coordinates of x. The well-known sensitivity conjecture of Nisan (see also Nisan and Szegedy) states that every sensitivity-s Boolean…

Computational Complexity · Computer Science 2016-04-27 Parikshit Gopalan , Rocco Servedio , Avishay Tal , Avi Wigderson

We give a new framework for proving the existence of low-degree, polynomial approximators for Boolean functions with respect to broad classes of non-product distributions. Our proofs use techniques related to the classical moment problem…

Computational Complexity · Computer Science 2013-01-07 Adam Klivans , Raghu Meka

The relationship between quantum physics and discrete mathematics is reviewed in this article. The Boolean functions unitary representation is considered. The relationship between Zhegalkin polynomial, which defines the algebraic normal…

Quantum Physics · Physics 2019-06-18 Yu. I. Bogdanov , N. A. Bogdanova , D. V. Fastovets , V. F. Lukichev

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