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Quantum versions of random walks have diverse applications that are motivating experimental implementations as well as theoretical studies. However, the main impetus behind this interest is their use in quantum algorithms, which have always…

Quantum Physics · Physics 2011-07-20 Viv Kendon

A semidefinite program (SDP) is a particular kind of convex optimization problem with applications in operations research, combinatorial optimization, quantum information science, and beyond. In this work, we propose variational quantum…

Quantum Physics · Physics 2024-06-19 Dhrumil Patel , Patrick J. Coles , Mark M. Wilde

Quantum annealing is a generic algorithm using quantum-mechanical fluctuations to search for the solution of an optimization problem. The present paper first reviews the fundamentals of quantum annealing and then reports on preliminary…

Disordered Systems and Neural Networks · Physics 2010-06-10 Masayuki Ohzeki , Hidetoshi Nishimori

In recent years, quantum, quantum-inspired, and hybrid algorithms are increasingly showing promise for solving software engineering optimization problems. However, best-intended practices for conducting empirical studies have not yet well…

Software Engineering · Computer Science 2025-11-03 Man Zhang , Yuechen Li , Tao Yue , Kai-Yuan Cai

Quantum computing has brought a paradigm change in computer science, where non-classical technologies have promised to outperform their classical counterpart. Such an advantage was only demonstrated for tasks without practical applications,…

This Perspective focuses on the several overlaps between quantum algorithms and Monte Carlo methods in the domains of physics and chemistry. We will analyze the challenges and possibilities of integrating established quantum Monte Carlo…

Quantum Physics · Physics 2024-09-26 Guglielmo Mazzola

Quantum-classical hybrid algorithms are emerging as promising candidates for near-term practical applications of quantum information processors in a wide variety of fields ranging from chemistry to physics and materials science. We report…

Variational hybrid quantum-classical optimization represents one of the most promising avenue to show the advantage of nowadays noisy intermediate-scale quantum computers in solving hard problems, such as finding the minimum-energy state of…

Quantum Physics · Physics 2020-11-18 Laura Gentini , Alessandro Cuccoli , Stefano Pirandola , Paola Verrucchi , Leonardo Banchi

For solving the Poisson equation it is usually possible to discretize it into solving the corresponding linear system $Ax=b$.Variational quantum algorithms (VQAs) for the discreted Poisson equation have been studied before. We give a VQA…

Quantum Physics · Physics 2025-04-22 Xiaoqi Liu , Yuedi Qu , Ming Li , Shu-qian Shen

Noisy intermediate-scale quantum computers (NISQ computers) are now readily available, motivating many researchers to experiment with Variational Quantum Algorithms (VQAs). Among them, the Quantum Approximate Optimization Algorithm (QAOA)…

Optimization and Control · Mathematics 2024-08-13 Camille Grange , Michael Poss , Eric Bourreau

Quantum computing, leveraging quantum phenomena like superposition and entanglement, is emerging as a transformative force in computing technology, promising unparalleled computational speed and efficiency crucial for engineering…

Quantum Physics · Physics 2024-08-30 Osama Muhammad Raisuddin , Suvranu De

We develop and apply several strategies for setting physical parameters on quantum annealers for application problems that do not fit natively on the hardware graph. The strategies are tested with a culled random set of mixed satisfiability…

Quantum Physics · Physics 2016-11-24 Kristen L. Pudenz

Variational quantum algorithms (VQAs) are hybrid quantum-classical approaches used for tackling a wide range of problems on noisy intermediate-scale quantum (NISQ) devices. Testing these algorithms on relevant hardware is crucial to…

Quantum computers have the potential to transform the ways in which we tackle some important problems. The efforts by companies like Google, IBM and Microsoft to construct quantum computers have been making headlines for years. Equally…

Quantum Physics · Physics 2018-12-05 Raffaele Miceli , Michael McGuigan

This paper presents an iterative method suitable for inverting semilinear problems which are important kernels in many numerical applications. The primary idea is to employ a parametrization that is able to reduce semilinear problems into…

Numerical Analysis · Mathematics 2019-08-02 Prosper Torsu

In this paper we briefly review two recent use-cases of quantum optimization algorithms applied to hard problems in finance and economy. Specifically, we discuss the prediction of financial crashes as well as dynamic portfolio optimization.…

General Finance · Quantitative Finance 2020-10-06 Samuel Mugel , Enrique Lizaso , Roman Orus

We present a method to split quantum circuits of variational quantum algorithms (VQAs) to allow for parallel training and execution, that maximally exploits the limited number of qubits in hardware to solve large problem instances. We apply…

Quantum Physics · Physics 2023-04-07 Michele Cattelan , Sheir Yarkoni

We study the problem of the practical realization of an abstract quantum circuit when executed on quantum hardware. By practical, we mean adapting the circuit to particulars of the physical environment which restricts/complicates the…

Quantum Physics · Physics 2008-03-27 D. Maslov , S. M. Falconer , M. Mosca

The accurate estimation of quantum observables is a critical task in science. With progress on the hardware, measuring a quantum system will become increasingly demanding, particularly for variational protocols that require extensive…

Fault-tolerant quantum computations require alternating quantum and classical computations, where the classical computations prove vital in detecting and correcting errors in the quantum computation. Recently, interest in using these…

Quantum Physics · Physics 2025-09-09 Niels M. P. Neumann
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