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Stochastic models are highly relevant tools in science, engineering, and society. Recent work suggests emerging quantum computing technologies can substantially decrease the memory requirements for simulating stochastic models. Here we show…

Quantum Physics · Physics 2019-06-04 John Realpe-Gómez , Nathan Killoran

This study presents a novel quantum algorithm for lattice gas automata simulation with a single time step, demonstrating logarithmic complexity in terms of $CX$ gates. The algorithm is composed of three main steps: collision, mapping, and…

In recent years, deep learning has had a profound impact on machine learning and artificial intelligence. At the same time, algorithms for quantum computers have been shown to efficiently solve some problems that are intractable on…

Quantum Physics · Physics 2015-05-25 Nathan Wiebe , Ashish Kapoor , Krysta M. Svore

Quantum computing is a new model of computation, based on quantum physics. Quantum computers can be exponentially faster than conventional computers for problems such as factoring. Besides full-scale quantum computers, more restricted…

Formal Languages and Automata Theory · Computer Science 2018-07-05 Andris Ambainis , Abuzer Yakaryılmaz

Quantum algorithms are demonstrated to outperform classical algorithms for certain problems and thus are promising candidates for efficient information processing. Herein we aim to provide a brief and popular introduction to quantum…

Quantum Physics · Physics 2022-12-22 Shihao Zhang , Lvzhou Li

Quantum computers are predicted to outperform classical ones for solving partial differential equations, perhaps exponentially. Here we consider a prototypical PDE - the heat equation in a rectangular region - and compare in detail the…

Quantum Physics · Physics 2020-06-19 Noah Linden , Ashley Montanaro , Changpeng Shao

Quantum computers leverage the principles of quantum mechanics to do computation with a potential advantage over classical computers. While a single classical computer transforms one particular binary input into an output after applying one…

Emerging Technologies · Computer Science 2025-03-17 Francisco Chicano , Gabiel Luque , Zakaria Abdelmoiz Dahi , Rodrigo Gil-Merino

Quantum computing promises to provide the next step up in computational power for diverse application areas. In this review, we examine the science behind the quantum hype, and the breakthroughs required to achieve true quantum advantage in…

Quantum Physics · Physics 2025-09-26 R. Au-Yeung , B. Camino , O. Rathore , V. Kendon

Quantum computing promises the ability to compute properties of quantum systems exponentially faster than classical computers. Quantum advantage is achieved when a practical problem is solved more efficiently on a quantum computer than on a…

Quantum Physics · Physics 2025-12-03 William A. Simon , Peter J. Love

Numerical simulation of quantum systems is crucial to further our understanding of natural phenomena. Many systems of key interest and importance, in areas such as superconducting materials and quantum chemistry, are thought to be described…

Quantum Physics · Physics 2010-11-17 Katherine L Brown , William J Munro , Vivien M Kendon

Quantum computing is concerned with computer technology based on the principles of quantum mechanics, with operations performed at the quantum level. Quantum computational models make it possible to analyze the resources required for…

Formal Languages and Automata Theory · Computer Science 2019-01-24 Amandeep Singh Bhatia , Ajay Kumar

Quantum algorithms have the potential to provide exponential speedups over some of the best known classical algorithms. These speedups may enable quantum devices to solve currently intractable problems such as those in the fields of…

Quantum Physics · Physics 2018-12-13 Ciarán Ryan-Anderson

Machine Learning algorithms are extensively used in an increasing number of systems, applications, technologies, and products, both in industry and in society as a whole. They enable computing devices to learn from previous experience and…

Quantum Physics · Physics 2025-02-17 Lucas Lamata

We develop and implement automated methods for optimizing quantum circuits of the size and type expected in quantum computations that outperform classical computers. We show how to handle continuous gate parameters and report a collection…

Quantum Physics · Physics 2018-06-04 Yunseong Nam , Neil J. Ross , Yuan Su , Andrew M. Childs , Dmitri Maslov

Quantum computation appears to offer significant advantages over classical computation and this has generated a tremendous interest in the field. In this thesis we consider the application of quantum computers to scientific computing and…

Quantum Physics · Physics 2018-05-10 Stuart Hadfield

Recently, increased computational power and data availability, as well as algorithmic advances, have led machine learning techniques to impressive results in regression, classification, data-generation and reinforcement learning tasks.…

We consider whether trainable quantum unitaries can be used to discover quantum speed-ups for classical problems. Using methods recently developed for training quantum neural nets, we consider Simon's problem, for which there is a known…

Quantum Physics · Physics 2018-06-28 Kwok Ho Wan , Feiyang Liu , Oscar Dahlsten , M. S. Kim

This study examines the simulation of quantum algorithms on a classical computer. The program code implemented on a classical computer will be a straight connection between the mathematical formulation of quantum mechanics and computational…

Quantum Physics · Physics 2007-06-13 Peter Nyman

The advent of hybrid computing platforms consisting of quantum processing units integrated with conventional high-performance computing brings new opportunities for algorithm design. By strategically offloading select portions of the…

Classical machine learning theory and theory of quantum computations are among of the most rapidly developing scientific areas in our days. In recent years, researchers investigated if quantum computing can help to improve classical machine…

Quantum Physics · Physics 2019-06-26 D. V. Fastovets , Yu. I. Bogdanov , B. I. Bantysh , V. F. Lukichev