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Related papers: Testing Boolean Functions Properties

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We study the query complexity of testing for properties defined by read once formulas, as instances of {\em massively parametrized properties}, and prove several testability and non-testability results. First we prove the testability of any…

Data Structures and Algorithms · Computer Science 2014-03-28 Eldar Fischer , Yonatan Goldhirsh , Oded Lachish

We prove that any non-adaptive algorithm that tests whether an unknown Boolean function $f: \{0, 1\}^n\to \{0, 1\}$ is a $k$-junta or $\epsilon$-far from every $k$-junta must make $\widetilde{\Omega}(k^{3/2} / \epsilon)$ many queries for a…

Computational Complexity · Computer Science 2017-04-24 Xi Chen , Rocco A. Servedio , Li-Yang Tan , Erik Waingarten , Jinyu Xie

We show that arbitrary functions of continuous variables, e.g. position and momentum, can be used to generate tests that distinguish quantum theory from local hidden variable theories. By optimising these functions, we obtain more robust…

Quantum Physics · Physics 2009-11-16 Q. Y. He , E. G. Cavalcanti , M. D. Reid , P. D. Drummond

In this paper, we consider a quantum algorithm for solving the following problem: ``Suppose $f$ is a function given as a black box (that is also called an oracle) and $f$ is invariant under some AND-mask. Examine a property of $f$ by…

Quantum Physics · Physics 2007-05-23 Hiroo Azuma

We present an $\tilde{O}(n^{2/3}/\epsilon^2)$-query algorithm that tests whether an unknown Boolean function $f\colon\{0,1\}^n\rightarrow \{0,1\}$ is unate (i.e., every variable is either non-decreasing or non-increasing) or $\epsilon$-far…

Data Structures and Algorithms · Computer Science 2019-04-11 Xi Chen , Erik Waingarten

The Forrelation problem is a central problem that demonstrates an exponential separation between quantum and classical capabilities. In this problem, given query access to $n$-bit Boolean functions $f$ and $g$, the goal is to estimate the…

Quantum Physics · Physics 2025-08-05 Uma Girish , Rocco Servedio

We present new algorithms to compute fundamental properties of a Boolean function given in truth-table form. Specifically, we give an O(N^2.322 log N) algorithm for block sensitivity, an O(N^1.585 log N) algorithm for `tree decomposition,'…

Computational Complexity · Computer Science 2007-05-23 Scott Aaronson

We compare quantum and classical machines designed for learning an N-bit Boolean function in order to address how a quantum system improves the machine learning behavior. The machines of the two types consist of the same number of…

Quantum Physics · Physics 2014-10-15 Seokwon Yoo , Jeongho Bang , Changhyoup Lee , Jinhyoung Lee

We consider a family of unstructured problems, for which we propose a method for constructing analog, continuous-time quantum algorithms that are more efficient than their classical counterparts. In this family of problems, which we refer…

Quantum Physics · Physics 2014-01-22 Itay Hen

We study the problem of testing discrete distributions with a focus on the high probability regime. Specifically, given samples from one or more discrete distributions, a property $\mathcal{P}$, and parameters $0< \epsilon, \delta <1$, we…

Data Structures and Algorithms · Computer Science 2020-09-15 Ilias Diakonikolas , Themis Gouleakis , Daniel M. Kane , John Peebles , Eric Price

We study the probability of making an error if, by querying an oracle a fixed number of times, we declare constant a randomly chosen n-bit Boolean function. We compare the classical and the quantum case, and we determine for how many…

Quantum Physics · Physics 2016-09-08 Fabio Benatti , Luca Marinatto

Recently there has been much interest in Gowers uniformity norms from the perspective of theoretical computer science. This is mainly due to the fact that these norms provide a method for testing whether the maximum correlation of a…

Computational Complexity · Computer Science 2013-08-14 Hamed Hatami , Shachar Lovett

By using a new way to encode Boolean functions in a reversible gate, an algorithm is developed in quantum computing over Z_2, symbolized QC/2, (as opposed to QC over C) that needs only one function evaluation to solve the Grover Database…

Quantum Physics · Physics 2024-09-09 David Ellerman

We present a quantum algorithm for approximating the linear structures of a Boolean function $f$. Different from previous algorithms (such as Simon's and Shor's algorithms) which rely on restrictions on the Boolean function, our algorithm…

Quantum Physics · Physics 2016-02-17 Hong-Wei Li , Li Yang

We study classical query algorithms with post-selection, and find that they are closely connected to rational functions with nonnegative coefficients. We show that the post-selected classical query complexity of a Boolean function is equal…

Computational Complexity · Computer Science 2018-05-15 Chris Cade

We examine a hierarchy of equivalence classes of quasi-random properties of Boolean Functions. In particular, we prove an equivalence between a number of properties including balanced influences, spectral discrepancy, local strong…

Combinatorics · Mathematics 2022-09-09 Fan Chung , Nicholas Sieger

We study quantum algorithms for verifying properties of the output probability distribution of a classical or quantum circuit, given access to the source code that generates the distribution. We consider the basic task of uniformity…

Quantum Physics · Physics 2024-11-08 Clément L. Canonne , Robin Kothari , Ryan O'Donnell

Quantum algorithms can be analyzed in a query model to compute Boolean functions. Function input is provided in a black box, and the aim is to compute the function value using as few queries to the black box as possible. A repetition code…

Quantum Physics · Physics 2009-04-24 Alina Vasilieva

We reveal a close relationship between quantum metrology and the Deutsch-Jozsa algorithm on continuous variable quantum systems. We develop a general procedure, characterized by two parameters, that unifies parameter estimation and the…

Quantum Physics · Physics 2016-08-14 Marcin Zwierz , Carlos A. Pérez-Delgado , Pieter Kok

This paper provides lower bounds on the convergence rate of Derivative Free Optimization (DFO) with noisy function evaluations, exposing a fundamental and unavoidable gap between the performance of algorithms with access to gradients and…

Machine Learning · Statistics 2012-09-13 Kevin G. Jamieson , Robert D. Nowak , Benjamin Recht
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