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Quantum state filtering is a variant of the unambiguous state discrimination problem: the states are grouped in sets and we want to determine to which particular set a given input state belongs.The simplest case, when the N given states are…

Quantum Physics · Physics 2009-11-11 Janos A. Bergou , Mark Hillery

This paper proposes algorithms for learning two-level Boolean rules in Conjunctive Normal Form (CNF, i.e. AND-of-ORs) or Disjunctive Normal Form (DNF, i.e. OR-of-ANDs) as a type of human-interpretable classification model, aiming for a…

Machine Learning · Computer Science 2015-11-24 Guolong Su , Dennis Wei , Kush R. Varshney , Dmitry M. Malioutov

We give a new upper bound on the quantum query complexity of deciding $st$-connectivity on certain classes of planar graphs, and show the bound is sometimes exponentially better than previous results. We then show Boolean formula evaluation…

Quantum Physics · Physics 2019-12-19 Stacey Jeffery , Shelby Kimmel

This article investigates the probabilistic relationship between quantum classification of Boolean functions and their Hamming distance. By integrating concepts from quantum computing, information theory, and combinatorics, we explore how…

A quantum algorithm is a set of instructions for a quantum computer, however, unlike algorithms in classical computer science their results cannot be guaranteed. A quantum system can undergo two types of operation, measurement and quantum…

Data Structures and Algorithms · Computer Science 2007-05-30 Eva Borbely

In this paper, we propose efficient probabilistic algorithms for several problems regarding the autocorrelation spectrum. First, we present a quantum algorithm that samples from the Walsh spectrum of any derivative of $f()$. Informally, the…

Quantum Physics · Physics 2019-10-09 Debajyoti Bera , Subhamoy Maitra , SAPV Tharrmashastha

In order to estimate the specific intrinsic volumes of a planar Boolean model from a binary image, we consider local digital algorithms based on weighted sums of $2\times 2$ configuration counts. For Boolean models with balls as grains,…

Statistics Theory · Mathematics 2016-02-24 Anne Marie Svane

This paper explores a fine-grained version of the Watrous conjecture, including the randomized and quantum algorithms with success probabilities arbitrarily close to $1/2$. Our contributions include the following: i) An analysis of the…

Computational Complexity · Computer Science 2023-10-24 Supartha Podder , Penghui Yao , Zekun Ye

The algebraic degree of Boolean functions (or vectorial Boolean functions) is an important cryptographic parameter that should be computed by fast algorithms. They work in two main ways: (1) by computing the algebraic normal form and then…

Cryptography and Security · Computer Science 2020-07-03 Valentin Bakoev

A Boolean function of n bits is balanced if it takes the value 1 with probability 1/2. We exhibit a balanced Boolean function with a randomized evaluation procedure (with probability 0 of making a mistake) so that on uniformly random…

Probability · Mathematics 2012-06-21 Itai Benjamini , Oded Schramm , David B. Wilson

Consider the problem of estimating the median of N items to a precision epsilon, i.e., the estimate should be such that, with a high probability, the number of items, with values both smaller than and larger than this estimate, is less than…

Quantum Physics · Physics 2007-05-23 Lov K. Grover

We present quantum algorithms for solving two problems regarding stochastic processes. The first algorithm prepares the thermal Gibbs state of a quantum system and runs in time almost linear in $\sqrt{N \beta/{\cal Z}}$ and polynomial in…

Quantum Physics · Physics 2017-01-11 Anirban Narayan Chowdhury , Rolando D. Somma

Attempts to separate the power of classical and quantum models of computation have a long history. The ultimate goal is to find exponential separations for computational problems. However, such separations do not come a dime a dozen: while…

Quantum Physics · Physics 2013-12-05 Martin Roetteler

We study quantum learning algorithms for quantum measurements. The optimal learning algorithm is derived for arbitrary von Neumann measurements in the case of training with one or two examples. The analysis of the case of three examples…

Quantum Physics · Physics 2011-08-31 Alessandro Bisio , Giacomo Mauro D'Ariano , Paolo Perinotti , Michal Sedlak

We propose a quantum algorithm (in the form of a quantum oracle) that estimates the closeness of a given Boolean function to one that satisfies the ``strict avalanche criterion'' (SAC). This algorithm requires $n$ queries of the Boolean…

Data Structures and Algorithms · Computer Science 2022-11-29 C. A. Jothishwaran , Abhishek Chakraborty , Vishvendra Singh Poonia , Pantelimon Stanica , Sugata Gangopadhyay

A central tool in the study of systems of linear equations with integer coefficients is the Generalised von Neumann Theorem of Green and Tao. This theorem reduces the task of counting the weighted solutions of these equations to that of…

Number Theory · Mathematics 2020-08-05 Aled Walker

We study the problem of detecting outlier pairs of strongly correlated variables among a collection of $n$ variables with otherwise weak pairwise correlations. After normalization, this task amounts to the geometric task where we are given…

Data Structures and Algorithms · Computer Science 2018-01-08 Matti Karppa , Petteri Kaski , Jukka Kohonen

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

We present an efficient quantum algorithm to simulate nonlinear differential equations with polynomial vector fields of arbitrary degree on quantum platforms. Models of physical systems that are governed by ordinary differential equations…

Dynamical Systems · Mathematics 2023-02-08 Amit Surana , Abeynaya Gnanasekaran , Tuhin Sahai

A natural measure of smoothness of a Boolean function is its sensitivity (the largest number of Hamming neighbors of a point which differ from it in function value). The structure of smooth or equivalently low-sensitivity functions is still…

Computational Complexity · Computer Science 2015-08-12 Parikshit Gopalan , Noam Nisan , Rocco A. Servedio , Kunal Talwar , Avi Wigderson
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