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The observation of an unequivocal quantum speedup remains an elusive objective for quantum computing. The D-Wave quantum annealing processors have been at the forefront of experimental attempts to address this goal, given their relatively…

Quantum Physics · Physics 2018-08-08 Tameem Albash , Daniel A. Lidar

Quantum computation offers a promising alternative to classical computing methods in many areas of numerical science, with algorithms that make use of the unique way in which quantum computers store and manipulate data often achieving…

Quantum Physics · Physics 2022-07-19 Christopher D. Phillips , Vladimir I. Okhmatovski

Despite rapid recent progress towards the development of quantum computers capable of providing computational advantages over classical computers, it seems likely that such computers will, initially at least, be required to run in a hybrid…

Data Structures and Algorithms · Computer Science 2020-01-27 Alastair A. Abbott , Cristian S. Calude , Michael J. Dinneen , Richard Hua

Quantum information science explores the frontier of highly complex quantum states, the "entanglement frontier." This study is motivated by the observation (widely believed but unproven) that classical systems cannot simulate highly…

Quantum Physics · Physics 2012-11-13 John Preskill

(Abridged.) Quantum computers promise to solve some problems exponentially faster than traditional computers, but we still do not fully understand why this is the case. While the most studied model of quantum computation uses qubits, which…

Quantum Physics · Physics 2025-05-29 Cameron Calcluth

Quantum computing provides a powerful framework for tackling computational problems that are classically intractable. The goal of this paper is to explore the use of quantum computers for solving relevant problems in systems and control…

Systems and Control · Electrical Eng. & Systems 2025-12-23 Jan Schneider , Julian Berberich

A central goal in quantum computing is the development of quantum hardware and quantum algorithms in order to analyse challenging scientific and engineering problems. Research in quantum computation involves contributions from both physics…

We present a classical algorithm to find approximate solutions to instances of quadratic unconstrained binary optimisation. The algorithm can be seen as an analogue of quantum annealing under the restriction of a product state space, where…

Quantum Physics · Physics 2023-02-14 Joseph Bowles , Alexandre Dauphin , Patrick Huembeli , José Martinez , Antonio Acín

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…

Quantum random sampling is the leading proposal for demonstrating a computational advantage of quantum computers over classical computers. Recently, first large-scale implementations of quantum random sampling have arguably surpassed the…

Quantum Physics · Physics 2023-07-21 Dominik Hangleiter , Jens Eisert

Quantum computers can execute algorithms that sometimes dramatically outperform classical computation. Undoubtedly the best-known example of this is Shor's discovery of an efficient quantum algorithm for factoring integers, whereas the same…

Quantum Physics · Physics 2017-08-23 Wim van Dam , Yoshitaka Sasaki

Quantum Annealing (QA) is one of the most promising frameworks for quantum optimization. Here, we focus on the problem of minimizing complex classical cost functions associated with prototypical discrete neural networks, specifically the…

Quantum Physics · Physics 2023-05-17 Guglielmo Lami , Pietro Torta , Giuseppe E. Santoro , Mario Collura

The question of whether or not quantum computers can efficiently solve NP-complete problems is open, although indications are that BQP does not contain NP. Still, many of these problems are natural candidates for solution on quantum…

Quantum Physics · Physics 2007-05-23 Steve Huntsman

Quantum computing has the potential to revolutionize multiple fields by solving complex problems that can not be solved in reasonable time with current classical computers. Nevertheless, the development of quantum computers is still in its…

Quantum computers have the potential of solving problems more efficiently than classical computers. While first commercial prototypes have become available, the performance of such machines in practical application is still subject to…

Emerging Technologies · Computer Science 2020-05-13 Tom Krüger , Wolfgang Mauerer

Quantum annealing (QA) has the potential to significantly improve solution quality and reduce time complexity in solving combinatorial optimization problems compared to classical optimization methods. However, due to the limited number of…

Quantum Physics · Physics 2025-04-09 Seongmin Kim , Sang-Woo Ahn , In-Saeng Suh , Alexander W. Dowling , Eungkyu Lee , Tengfei Luo

Entanglement lies at the core of quantum algorithms designed to solve problems that are intractable by classical approaches. One such algorithm, quantum annealing (QA), provides a promising path to a practical quantum processor. We have…

This paper argues that the requirement of applicableness of quantum linearity to any physical level from molecules and atoms to the level of macroscopic extensional world, which leads to a main foundational problem in quantum theory…

Quantum Physics · Physics 2014-06-25 Arkady Bolotin

Many quantum algorithms can be represented in a form of a classical circuit positioned between quantum Fourier transformations. Motivated by the search for new quantum algorithms, we turn to circuits where the latter transformation is…

Quantum Physics · Physics 2019-07-03 Vojtěch Havlíček , Sergii Strelchuk , Kristan Temme

Quantum annealing has shown significant potential as an approach to near-term quantum computing. Despite promising progress towards obtaining a quantum speedup, quantum annealers are limited by the need to embed problem instances within the…

Data Structures and Algorithms · Computer Science 2018-07-31 Alastair A. Abbott , Cristian S. Calude , Michael J. Dinneen , Richard Hua