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The Traveling Salesman Problem is a classical NP-hard combinatorial optimization problem that has been extensively studied in operations research. A major challenge in Traveling Salesman Problem formulations is the large number of subtour…

Quantum Physics · Physics 2026-04-23 Alessia Ciacco , Luigi Di Puglia Pugliese , Francesca Guerriero

Hybrid algorithms that combine quantum and classical resources have become commonplace in quantum computing. The variational quantum eigensolver (VQE) is routinely used to solve prototype problems. Currently, hybrid algorithms use no more…

Quantum Physics · Physics 2024-08-27 Manpreet Singh Jattana

As quantum computing advances towards practical applications, quantum operating systems become inevitable, where multi-programming -- the core functionality of operating systems -- enables concurrent execution of multiple quantum programs…

Quantum Physics · Physics 2025-07-08 Wenjie Sun , Xiaoyu Li , Zhigang Wang , Geng Chen , Lianhui Yu , Guowu Yang

We propose and compare Constraint Programming (CP) and Quantum Annealing (QA) approaches for rolling stock assignment optimisation considering necessary maintenance tasks. In the CP approach, we model the problem with an Alldifferent…

Artificial Intelligence · Computer Science 2023-09-26 Patricia Bickert , Cristian Grozea , Ronny Hans , Matthias Koch , Christina Riehn , Armin Wolf

Quantum computing promises to speed up some of the most challenging problems in science and engineering. Quantum algorithms have been proposed showing theoretical advantages in applications ranging from chemistry to logistics optimization.…

Quantum Physics · Physics 2021-11-12 Niklas Heim , Atiyo Ghosh , Oleksandr Kyriienko , Vincent E. Elfving

Optimal parameter setting for applications problems embedded into hardware graphs is key to practical quantum annealers (QA). Embedding chains typically crop up as harmful Griffiths phases, but can be used as a resource as we show here: to…

Quantum Physics · Physics 2021-01-04 Sergey Knysh , Eugeniu Plamadeala , Davide Venturelli

I provide an alternative way of seeing quantum computation. First, I describe an idealized classical problem solving machine that, thanks to a many body interaction, reversibly and nondeterministically produces the solution of the problem…

Quantum Physics · Physics 2007-10-10 Giuseppe Castagnoli

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

Analog Quantum Computers are promising tools for improving performance on applications such as modeling behavior of quantum materials, providing fast heuristic solutions to optimization problems, and simulating quantum systems. Due to the…

Quantum Physics · Physics 2024-07-31 Zachary Morrell , Marc Vuffray , Sidhant Misra , Carleton Coffrin

Quantum computing is gaining popularity across a wide range of scientific disciplines due to its potential to solve long-standing computational problems that are considered intractable with classical computers. One promising area where…

Quantum Physics · Physics 2023-05-15 Benjamin C. B. Symons , David Galvin , Emre Sahin , Vassil Alexandrov , Stefano Mensa

The quantum approximate optimisation algorithm was proposed as a heuristic method for solving combinatorial optimisation problems on near-term quantum computers and may be among the first algorithms to perform useful computations in the…

Quantum Physics · Physics 2022-11-10 David Headley , Thorge Müller , Ana Martin , Enrique Solano , Mikel Sanz , Frank K. Wilhelm

Hard combinatorial optimization problems, often mapped to Ising models, promise potential solutions with quantum advantage but are constrained by limited qubit counts in near-term devices. We present an innovative quantum-inspired framework…

Quantum Physics · Physics 2024-12-25 Co Tran , Quoc-Bao Tran , Hy Truong Son , Thang N Dinh

Quadratic Unconstrained Binary Optimization (QUBO) problems are NP-hard problems and many real-world problems can be formulated as QUBO. Currently there are no algorithms known that can solve arbitrary instances of NP-hard problems…

Quantum Physics · Physics 2023-12-20 Christian Münch , Fritz Schinkel , Sebastian Zielinski , Stefan Walter

Some approaches to solving challenging dynamic programming problems, such as Q-learning, begin by transforming the Bellman equation into an alternative functional equation, in order to open up a new line of attack. Our paper studies this…

Optimization and Control · Mathematics 2019-12-05 Qingyin Ma , John Stachurski

Adiabatic quantum computing has evolved in recent years from a theoretical field into an immensely practical area, a change partially sparked by D-Wave System's quantum annealing hardware. These multimillion-dollar quantum annealers offer…

Quantum Physics · Physics 2017-07-28 Timothy D. Goodrich , Travis S. Humble , Blair D. Sullivan

We propose a practical, physics-inspired benchmarking suite to challenge both quantum and classical computers by mapping real-time quantum dynamics to a common optimization format. Using a parallel-in-time encoding, we convert the real-time…

Quantum Physics · Physics 2026-04-23 Philipp Hanussek , Jakub Pawłowski , Zakaria Mzaouali , Bartłomiej Gardas

Recent advances in quantum technology have led to the development and manufacturing of experimental programmable quantum annealing optimizers that contain hundreds of quantum bits. These optimizers, named `D-Wave' chips, promise to solve…

Quantum Physics · Physics 2015-10-23 Victor Martin-Mayor , Itay Hen

There has been considerable progress in the design and construction of quantum annealing devices. However, a conclusive detection of quantum speedup over traditional silicon-based machines remains elusive, despite multiple careful studies.…

Quantum Physics · Physics 2015-09-03 Helmut G. Katzgraber , Firas Hamze , Zheng Zhu , Andrew J. Ochoa , H. Munoz-Bauza

Recent demonstrations on specialized benchmarks have reignited excitement for quantum computers, yet whether they can deliver an advantage for practical real-world problems remains an open question. Here, we show that probabilistic…

Quantum computing is rapidly advancing, harnessing the power of qubits' superposition and entanglement for computational advantages over classical systems. However, scalability poses a primary challenge for these machines. By implementing a…