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Faster algorithms, novel cryptographic mechanisms, and alternative methods of communication become possible when the model underlying information and computation changes from a classical mechanical model to a quantum mechanical one. Quantum…

Quantum Physics · Physics 2009-12-29 Eleanor G. Rieffel

Quantum computing, leveraging the principles of quantum mechanics, has been found to significantly enhance computational capabilities in principle, in some cases beyond classical computing limits. This paper explores quantum computing's…

Quantum Physics · Physics 2025-03-28 Chence Niu , Elnaz Irannezhad , Casey Myers , Vinayak Dixit

Quantum annealing offers a novel approach to finding the optimal solutions for a variety of computational problems, where the quantum annealing controls influence the observed performance and error mechanisms by tuning the underlying…

Quantum Physics · Physics 2021-01-13 Erica Grant , Travis Humble , Benjamin Stump

Simulated annealing provides a heuristic solution to combinatorial optimization problems. The cost function of a problem is mapped onto the energy function of a physical many-body system, and, by using thermal or quantum fluctuations, the…

Statistical Mechanics · Physics 2025-12-05 Yoshiaki Horiike , Yuki Kawaguchi

Quantum annealing is a heuristic optimization algorithm that exploits quantum evolution to approximately find lowest energy states. Quantum annealers have scaled up in recent years to tackle increasingly larger and more highly connected…

Quantum Physics · Physics 2025-07-04 Humberto Munoz Bauza , Daniel A. Lidar

Finding the global minimum in a rugged potential landscape is a computationally hard task, often equivalent to relevant optimization problems. Simulated annealing is a computational technique which explores the configuration space by…

Quantum Physics · Physics 2017-05-10 Tobias Graß , Maciej Lewenstein

This paper summarizes a quantum algorithm of [R.D. Somma, et.al., Phys. Rev. Lett. 101, 130504 (2008)] that simulates a classical annealing process for solving discrete optimization problems. The complexity of the quantum algorithm scales…

Quantum Physics · Physics 2015-12-16 Sergio Boixo , Rolando D. Somma

Quantum annealing is an optimization technique which potentially leverages quantum tunneling to enhance computational performance. Existing quantum annealers use superconducting flux qubits with short coherence times, limited primarily by…

We discuss the usefulness of quantum cloning and present examples of quantum computation tasks for which cloning offers an advantage which cannot be matched by any approach that does not resort to it. In these quantum computations, we need…

Quantum Physics · Physics 2007-05-23 Gao Ting , Yan Feng-Li , Wang Zhi-Xi

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 Tunneling is ubiquitous across different fields, from quantum chemical reactions, and magnetic materials to quantum simulators and quantum computers. While simulating the real-time quantum dynamics of tunneling is infeasible for…

Quantum Physics · Physics 2017-10-17 Guglielmo Mazzola , Vadim N. Smelyanskiy , Matthias Troyer

Features of the residual energy after the quantum annealing are investigated. The quantum annealing method exploits quantum fluctuations to search the ground state of classical disordered Hamiltonian. If the quantum fluctuation is reduced…

Disordered Systems and Neural Networks · Physics 2009-11-11 Sei Suzuki , Masato Okada

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…

The presence of a bias field, encoding some information about the target state, can enhance the performance of quantum optimization methods. Here we investigate the effect of such a bias field on the outcome of quantum annealing sampling,…

Quantum Physics · Physics 2022-10-19 Tobias Graß

Quantum computers are designed to outperform standard computers by running quantum algorithms. Areas in which quantum algorithms can be applied include cryptography, search and optimisation, simulation of quantum systems, and solving large…

Quantum Physics · Physics 2016-02-24 Ashley Montanaro

We briefly review various computational methods for the solution of optimization problems. First, several classical methods such as Metropolis algorithm and simulated annealing are discussed. We continue with a description of quantum…

Statistical Mechanics · Physics 2015-12-01 Eliahu Cohen , Boaz Tamir

The recent emergence of novel computational devices, such as quantum computers, coherent Ising machines, and digital annealers presents new opportunities for hardware-accelerated hybrid optimization algorithms. Unfortunately, demonstrations…

Optimization and Control · Mathematics 2020-10-21 Yuchen Pang , Carleton Coffrin , Andrey Y. Lokhov , Marc Vuffray

This research highlights the potential of quantum annealing in tackling large-scale optimization problems within the airline industry,demonstrating its efficiency for certain problem sizes while also acknowledging its current limitations.…

Quantum Physics · Physics 2026-02-16 Kuntal Adak , Sakshi Kaushik , Rahul Rana

Quantum computing exposes the brilliance of quantum mechanics through computer science and, as such, gives oneself a marvelous and exhilarating journey to go through. This article leads along that journey with a historical and current…

Popular Physics · Physics 2024-03-18 Robert Kudelić

Quantum annealing is a method developed to solve combinatorial optimization problems by utilizing quantum bits. Solving such problems corresponds to minimizing a cost function defined over binary variables. However, in many practical cases,…

Quantum Physics · Physics 2025-06-26 Seiya Endo , Shohei Kawakatsu , Hiromichi Matsuyama , Kohei Suzuki , Yuichiro Matsuzaki