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This paper studies quantum supervised learning for classical inference from quantum states. In this model, a learner has access to a set of labeled quantum samples as the training set. The objective is to find a quantum measurement that…

Quantum Physics · Physics 2024-08-26 Mohsen Heidari , Wojciech Szpankowski

We define a class of stochastic processes based on evolutions and measurements of quantum systems, and consider the complexity of predicting their long-term behavior. It is shown that a very general class of decision problems regarding…

Computational Complexity · Computer Science 2007-05-23 John Watrous

Simon in his FOCS'94 paper was the first to show an exponential gap between classical and quantum computation. The problem he dealt with is now part of a well-studied class of problems, the hidden subgroup problems. We study Simon's problem…

Quantum Physics · Physics 2007-05-23 Pascal Koiran , Vincent Nesme , Natacha Portier

Most problems in uncertainty quantification, despite its ubiquitousness in scientific computing, applied mathematics and data science, remain formidable on a classical computer. For uncertainties that arise in partial differential equations…

Quantum Physics · Physics 2022-09-29 Francois Golse , Shi Jin , Nana Liu

There is a natural relationship between Jones polynomials and quantum computation. We use this relationship to show that the complexity of evaluating relative-error approximations of Jones polynomials can be used to bound the classical…

Quantum Physics · Physics 2017-11-03 Ryan L. Mann , Michael J. Bremner

We prove that, to compute a Boolean function $f$ on $N$ variables with error probability $\epsilon$, any quantum black-box algorithm has to query at least $\frac{1 - 2\sqrt{\epsilon}}{2} \rho_f N = \frac{1 - 2\sqrt{\epsilon}}{2} \bar{S}_f$…

Quantum Physics · Physics 2007-05-23 Yaoyun Shi

A previously developed quantum search algorithm for solving 1-SAT problems in a single step is generalized to apply to a range of highly constrained k-SAT problems. We identify a bound on the number of clauses in satisfiability problems for…

Artificial Intelligence · Computer Science 2011-05-30 T. Hogg

This study examines clusterability testing for a signed graph in the bounded-degree model. Our contributions are two-fold. First, we provide a quantum algorithm with query complexity $\tilde{O}(N^{1/3})$ for testing clusterability, which…

Quantum Physics · Physics 2023-11-20 Kuo-Chin Chen , Simon Apers , Min-Hsiu Hsieh

A quantum algorithm is exact if, on any input data, it outputs the correct answer with certainty (probability 1). A key question is: how big is the advantage of exact quantum algorithms over their classical counterparts: deterministic…

Quantum Physics · Physics 2014-07-11 Andris Ambainis

Algorithms with unitary oracles can be nested, which makes them extremely versatile. An example is the phase estimation algorithm used in many candidate algorithms for quantum speed-up. The search for new quantum algorithms benefits from…

Quantum Physics · Physics 2024-04-01 Zuzana Gavorová , Matan Seidel , Yonathan Touati

We present a number of results related to quantum algorithms with small error probability and quantum algorithms that are zero-error. First, we give a tight analysis of the trade-offs between the number of queries of quantum search…

Computational Complexity · Computer Science 2007-05-23 H. Buhrman , R. Cleve , R. de Wolf , Ch. Zalka

In this paper, we study the communication complexity for the problem of computing a conjunctive query on a large database in a parallel setting with $p$ servers. In contrast to previous work, where upper and lower bounds on the…

Databases · Computer Science 2016-04-08 Paul Beame , Paraschos Koutris , Dan Suciu

The CONGEST and CONGEST-CLIQUE models have been carefully studied to represent situations where the communication bandwidth between processors in a network is severely limited. Messages of only $O(log(n))$ bits of information each may be…

Quantum annealers are specialized quantum computers for solving combinatorial optimization problems using special characteristics of quantum computing (QC), such as superposition, entanglement, and quantum tunneling. Theoretically, quantum…

Software Engineering · Computer Science 2024-07-29 Xinyi Wang , Asmar Muqeet , Tao Yue , Shaukat Ali , Paolo Arcaini

Although classical computing has excelled in a wide range of applications, there remain problems that push the limits of its capabilities, especially in fields like cryptography, optimization, and materials science. Quantum computing…

Software Engineering · Computer Science 2025-01-14 Neilson Carlos Leite Ramalho , Erico Augusto da Silva , Higor Amario de Souza , Marcos Lordello Chaim

We study the complexity of quantum query algorithms that make p queries in parallel in each timestep. This model is in part motivated by the fact that decoherence times of qubits are typically small, so it makes sense to parallelize quantum…

Quantum Physics · Physics 2015-02-24 Stacey Jeffery , Frederic Magniez , Ronald de Wolf

The classical Yao principle states that the complexity R_epsilon(f) of an optimal randomized algorithm for a function f with success probability 1-epsilon equals the complexity max_mu D_epsilon^mu(f) of an optimal deterministic algorithm…

Quantum Physics · Physics 2007-05-23 Mart de Graaf , Ronald de Wolf

In the exact quantum query model a successful algorithm must always output the correct function value. We investigate the function that is true if exactly $k$ or $l$ of the $n$ input bits given by an oracle are 1. We find an optimal…

Quantum Physics · Physics 2018-01-11 Andris Ambainis , Jānis Iraids , Daniel Nagaj

Within the simultaneous message passing model of communication complexity, under a public-coin assumption, we derive the minimum achievable worst-case error probability of a classical fingerprinting protocol with one-sided error. We then…

Quantum Physics · Physics 2007-05-23 Rolf T. Horn , A. J. Scott , Jonathan Walgate , Richard Cleve , A. I. Lvovsky , Barry C. Sanders

The use of quantum computing for machine learning is among the most exciting prospective applications of quantum technologies. However, machine learning tasks where data is provided can be considerably different than commonly studied…

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