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The first quantum computers are expected to perform well at quadratic optimisation problems. In this paper a quadratic problem in finance is taken, the Portfolio Optimisation problem. Here, a set of assets is chosen for investment, such…

Portfolio Management · Quantitative Finance 2020-12-03 Frank Phillipson , Harshil Singh Bhatia

The most advanced D-Wave Advantage quantum annealer has 5000+ qubits, however, every qubit is connected to a small number of neighbors. As such, implementation of a fully-connected graph results in an order of magnitude reduction in qubit…

Quantum technology is maturing to the point where quantum devices, such as quantum communication systems, quantum random number generators and quantum simulators, may be built with capabilities exceeding classical computers. A quantum…

This paper introduces a novel edge-based encoding technique for solving the Traveling Salesman Problem (TSP) on a quantum computer, reducing the required number of qubits. For implementation in real quantum devices, we applied the subspace…

Quantum Physics · Physics 2025-12-22 Anandu Kalleri Madhu , Chi-Kwong Li , Jami Rönkkö , Mikio Nakahara , Ray-Kuang Lee

In this paper, we explore the potential for quantum annealing to solve realistic routing problems. We focus on two NP-Hard problems, including the Traveling Salesman Problem with Time Windows and the Capacitated Vehicle Routing Problem with…

Emerging Technologies · Computer Science 2025-04-01 James B. Holliday , Darren Blount , Eneko Osaba , Khoa Luu

A solution to the benchmark ATT48 Traveling Salesman Problem (from the TSPLIB95 library) results from isolating the set of vertices into ten open-ended zones with nine lengthwise boundaries. In each zone, a minimum-length Hamiltonian Path…

Data Structures and Algorithms · Computer Science 2007-10-03 Anthony A. Ruffa

We propose a framework to solve non-linear and history-dependent mechanical problems based on a hybrid classical computer -- quantum annealer approach. Quantum Computers are anticipated to solve particular operations exponentially faster.…

Computational Engineering, Finance, and Science · Computer Science 2024-02-20 Van-Dung Nguyen , Ling Wu , Françoise Remacle , Ludovic Noels

In this paper we study the viability of solving the Chinese Postman Problem, a graph routing optimization problem, and many of its variants on a quantum annealing device. Routing problem variants considered include graph type, directionally…

Quantum Physics · Physics 2022-08-18 Joel E. Pion , Christian F. A. Negre , Susan M. Mniszewski

Benchmarking Quantum Process Units (QPU) at an application level usually requires considering the whole programming stack of the quantum computer. One critical task is the minor-embedding (resp. transpilation) step, which involves…

Quantum Physics · Physics 2024-08-02 Valentin Gilbert , Julien Rodriguez , Stéphane Louise

One of the problems frequently mentioned as a candidate for quantum advantage is that of selecting a portfolio of financial assets to maximize returns while minimizing risk. In this paper we formulate several real-world constraints for use…

Materials Science · Physics 2022-03-10 Salvatore Certo , Anh Dung Pham , Daniel Beaulieu

The D-Wave quantum annealers make it possible to obtain high quality solutions of NP-hard problems by mapping a problem in a QUBO (quadratic unconstrained binary optimization) or Ising form to the physical qubit connectivity structure on…

Quantum Physics · Physics 2022-12-29 Elijah Pelofske , Georg Hahn , Hristo Djidjev

The spread of intelligent transportation systems in urban cities has caused heavy computational loads, requiring a novel architecture for managing large-scale traffic. In this study, we develop a method for globally controlling traffic…

Optimization and Control · Mathematics 2021-02-02 Daisuke Inoue , Akihisa Okada , Tadayoshi Matsumori , Kazuyuki Aihara , Hiroaki Yoshida

Quantum Computing is an emerging paradigm which is gathering a lot of popularity in the current scientific and technological community. Widely conceived as the next frontier of computation, Quantum Computing is still at the dawn of its…

Quantum annealers, such as the device built by D-Wave Systems, Inc., offer a way to compute solutions of NP-hard problems that can be expressed in Ising or QUBO (quadratic unconstrained binary optimization) form. Although such solutions are…

Quantum Physics · Physics 2022-10-27 Aaron Barbosa , Elijah Pelofske , Georg Hahn , Hristo N. Djidjev

Adiabatic quantum computers, such as the quantum annealers commercialized by D-Wave Systems Inc., are routinely used to tackle combinatorial optimization problems. In this article, we show how to exploit them to accelerate equilibrium…

Disordered Systems and Neural Networks · Physics 2023-07-12 Giuseppe Scriva , Emanuele Costa , Benjamin McNaughton , Sebastiano Pilati

In this work, a novel idea is presented for combinatorial optimization problems, a hybrid network, which results in a superior outcome. We applied this method to graph pointer networks [1], expanding its capabilities to a higher level. We…

This paper presents a novel and efficient heuristic framework for approximating the solutions to the multiple traveling salesmen problem (m-TSP) and other variants on the TSP. The approach adopted in this paper is an extension of the…

Optimization and Control · Mathematics 2016-04-15 Mayank Baranwal , Brian Roehl , Srinivasa M. Salapaka

We evaluate the application of quantum annealing (QA) to a real-world combinatorial optimisation problem-room scheduling for sports camps at the Australian Institute of Sport-using both classical and quantum approaches. Due to current…

Quantum Physics · Physics 2025-09-08 Krzysztof Giergiel , Y. Sam Yang , Anthony B. Murphy

Emerging quantum processors provide an opportunity to explore new approaches for solving traditional problems in the post Moore's law supercomputing era. However, the limited number of qubits makes it infeasible to tackle massive real-world…

The Traveling-Salesperson-Problem (TSP) is arguably one of the best-known NP-hard combinatorial optimization problems. The two sophisticated heuristic solvers LKH and EAX and respective (restart) variants manage to calculate close-to…

Artificial Intelligence · Computer Science 2020-05-28 Jakob Bossek , Pascal Kerschke , Heike Trautmann
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