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The optimization of the power consumption of antenna networks is a problem with a potential impact in the field of telecommunications. In this work, we investigate the application of the quantum approximate optimization algorithm (QAOA) and…

Quantum Physics · Physics 2025-09-18 Matteo Vandelli , Alessandra Lignarolo , Carlo Cavazzoni , Daniele Dragoni

Quantum annealing is a promising method for solving combinational optimization problems and performing quantum chemical calculations. The main sources of errors in quantum annealing are the effects of decoherence and non-adiabatic…

Quantum Physics · Physics 2022-11-23 Takashi Imoto , Yuya Seki , Yuichiro Matsuzaki and , Shiro Kawabata

This paper presents a new method to reduce the optimization of a pseudo-Boolean function to QUBO problem which can be solved by quantum annealer. The new method has two aspects, one is coefficient optimization and the other is variable…

Cryptography and Security · Computer Science 2022-11-21 Anpeng Zhang , Xiutao Feng

Quantum phenomena have the potential to speed up the solution of hard optimization problems. For example quantum annealing, based on the quantum tunneling effect, has recently been shown to scale exponentially better with system size as…

Quantum Physics · Physics 2017-04-27 Simon E. Nigg , Niels Loerch , Rakesh P. Tiwari

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

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

We present a novel formulation of structural design optimization problems specifically tailored to be solved by quantum annealing (QA). Structural design optimization aims to find the best, i.e., material-efficient yet high-performance,…

Computational Engineering, Finance, and Science · Computer Science 2024-04-17 Fabian Key , Lukas Freinberger

Quantum annealing is a promising approach for solving combinatorial optimization problems. However, its performance is often limited by the overhead of additional qubits required for embedding logical QUBO models onto quantum annealers.…

Quantum Physics · Physics 2026-01-27 Kohei Suda , Soshun Naito , Yoshihiko Hasegawa

Resource allocation of wide-area internet networks is inherently a combinatorial optimization problem that if solved quickly, could provide near real-time adaptive control of internet-protocol traffic ensuring increased network efficacy and…

Quantum Physics · Physics 2024-05-21 Arthur Witt , Jangho Kim , Christopher Körber , Thomas Luu

Recent advances in quantum technology have led to the development and manufacturing of experimental programmable quantum annealers that promise to solve certain combinatorial optimization problems of practical relevance faster than their…

Quantum Physics · Physics 2016-05-31 Itay Hen , Federico M. Spedalieri

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

Quantum annealing is a framework for solving combinatorial optimization problems. While it offers a promising path towards a practical application of quantum hardware, its performance in real-world devices is severely limited by…

Discrete combinatorial optimization consists in finding the optimal configuration that minimizes a given discrete objective function. An interpretation of such a function as the energy of a classical system allows us to reduce the…

Quantum Physics · Physics 2015-06-22 Sergio Boixo , Gerardo Ortiz , Rolando Somma

This paper proposes a novel dispatch formulation for micro-mobility vehicles using a Quantum Annealer (QA). In recent years, QA has gained increasing attention as a high-performance solver for combinatorial optimization problems. Meanwhile,…

Quantum Physics · Physics 2026-01-30 Takeru Goto , Masayuki Ohzeki

Quantum annealing is a heuristic algorithm for searching the ground state of an Ising model. Heuristic algorithms aim to obtain near-optimal solutions with a reasonable computation time. Accordingly, many algorithms have so far been…

Quantum Physics · Physics 2022-11-09 Shuntaro Okada , Masayuki Ohzeki

We investigate the minimum edge multiway cut problem, a fundamental task in evaluating the resilience of telecommunication networks. This study benchmarks the problem across three quantum computing paradigms: quantum annealing on a D-Wave…

Quantum Physics · Physics 2026-01-05 Ali Abbassi , Yann Dujardin , Eric Gourdin , Philippe Lacomme , Caroline Prodhon

The development of a future, global quantum communication network (or quantum internet) will enable high rate private communication and entanglement distribution over very long distances. However, the large-scale performance of ground-based…

Quantum Physics · Physics 2022-03-29 Cillian Harney , Stefano Pirandola

In this paper, we review some features of quantum annealing and related topics from viewpoints of statistical physics, condensed matter physics, and computational physics. We can obtain a better solution of optimization problems in many…

Disordered Systems and Neural Networks · Physics 2017-08-23 Shu Tanaka , Ryo Tamura

Recent technological advancements in satellite based quantum communication has made it a promising technology for realizing global scale quantum networks. Due to better loss distance scaling compared to ground based fiber communication,…

Quantum Physics · Physics 2022-05-27 Nitish K. Panigrahy , Prajit Dhara , Don Towsley , Saikat Guha , Leandros Tassiulas

Energy materials with disorder in site occupation are challenging for computational studies due to an exponential scaling of the configuration space. We herein present a grand-canonical optimization method that enables the use of quantum…

Materials Science · Physics 2024-11-28 Tobias Binninger , Yin-Ying Ting , Piotr M. Kowalski , Michael H. Eikerling