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Quantum annealers of D-Wave Systems, Inc., offer an efficient way to compute high quality solutions of NP-hard problems. This is done by mapping a problem onto the physical qubits of the quantum chip, from which a solution is obtained after…

Quantum Physics · Physics 2022-11-30 Elijah Pelofske , Georg Hahn , Hristo N. Djidjev

In this work, we develop a new quantum algorithm to solve a combinatorial problem with significant practical relevance occurring in clutch manufacturing. It is demonstrated how quantum optimization can play a role in real industrial…

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

Quantum annealing has emerged as a powerful tool for solving combinatorial optimization problems efficiently, making use of the principles of quantum mechanics. Companies are increasingly investing in the market of quantum computers,…

Quantum Physics · Physics 2025-09-29 Lorenzo Mazzei , Giada Beccari , Mirko Laruina , Marco Cococcioni

Over the past decade, the usefulness of quantum annealing hardware for combinatorial optimization has been the subject of much debate. Thus far, experimental benchmarking studies have indicated that quantum annealing hardware does not…

Optimization and Control · Mathematics 2022-10-11 Byron Tasseff , Tameem Albash , Zachary Morrell , Marc Vuffray , Andrey Y. Lokhov , Sidhant Misra , Carleton Coffrin

A quantum annealer heuristically minimizes quadratic unconstrained binary optimization (QUBO) problems, but is limited by the physical hardware in the size and density of the problems it can handle. We have developed a meta-heuristic solver…

Discrete Mathematics · Computer Science 2016-05-20 Gili Rosenberg , Mohammad Vazifeh , Brad Woods , Eldad Haber

To increase efficiency in automotive manufacturing, newly produced vehicles can move autonomously from the production line to the distribution area. This requires an optimal placement of sensors to ensure full coverage while minimizing the…

Emerging Technologies · Computer Science 2025-07-23 Nico Kraus , Marvin Erdmann , Alexander Kuzmany , Daniel Porawski , Jonas Stein

We continue to investigate the use of quantum computers for building an optimal portfolio out of a universe of 60 U.S. listed, liquid equities. Starting from historical market data, we apply our unique problem formulation on the D-Wave…

General Finance · Quantitative Finance 2020-08-21 Jeffrey Cohen , Alex Khan , Clark Alexander

Hybrid-quantum classical optimization has emerged as a promising direction for addressing financial decision problems under current quantum hardware constraints. In this work we present a practical end-to-end portfolio optimization pipeline…

Quantum computing is developing fast. Real world applications are within reach in the coming years. One of the most promising areas is combinatorial optimisation, where the Quadratic Unconstrained Binary Optimisation (QUBO) problem…

Quantum Physics · Physics 2020-07-06 Frank Phillipson , Irina Chiscop

Given an undirected graph, the stable set problem asks to determine the cardinality of the largest subset of pairwise non-adjacent vertices. This value is called the stability number of the graph, and its computation is an NP-hard problem.…

Optimization and Control · Mathematics 2025-11-14 Aljaž Krpan , Janez Povh , Dunja Pucher

Quantum annealing is getting increasing attention in combinatorial optimization. The quantum processing unit by D-Wave is constructed to approximately solve Ising models on so-called Chimera graphs. Ising models are equivalent to quadratic…

Data Structures and Algorithms · Computer Science 2019-04-30 Michael Juenger , Elisabeth Lobe , Petra Mutzel , Gerhard Reinelt , Franz Rendl , Giovanni Rinaldi , Tobias Stollenwerk

Optimizing the training of a machine learning pipeline helps in reducing training costs and improving model performance. One such optimizing strategy is quantum annealing, which is an emerging computing paradigm that has shown potential in…

Quantum Physics · Physics 2021-06-08 Rajdeep Kumar Nath , Himanshu Thapliyal , Travis S. Humble

We assess the performance of D-wave quantum solvers for solving the stable set problem in a graph, one of the most studied NP-hard problems. We perform computations on some instances from the literature with up to 125 vertices and compare…

Optimization and Control · Mathematics 2023-08-28 Janez Povh , Dunja Pucher

In this work we investigate the capabilities of a hybrid quantum-classical procedure to explore the solution space using the D-Wave $2000Q^{TM}$ Quantum Annealer device. Here we study the ability of the Quantum hardware to solve the Number…

Quantum Physics · Physics 2020-03-10 Luca Asproni , Davide Caputo , Blanca Silva , Giovanni Fazzi , Marco Magagnini

We present a comparison study of state-of-the-art classical optimisation methods to a D-Wave 2000Q quantum annealer for the planning of Earth observation missions. The problem is to acquire high value images while obeying the attitude…

This paper assesses the performance of the D-Wave 2X (DW) quantum annealer for finding a maximum clique in a graph, one of the most fundamental and important NP-hard problems. Because the size of the largest graphs DW can directly solve is…

Quantum Physics · Physics 2018-04-25 Guillaume Chapuis , Hristo N. Djidjev , Georg Hahn , Guillaume Rizk

The D-Wave quantum annealing machine can quickly find the optimal solution for quadratic unconstrained binary optimization (QUBO). One of the applications where the use of quantum annealing is desired is in problems requiring rapid…

Quantum Physics · Physics 2024-12-11 Reo Shikanai , Masayuki Ohzeki , Kazuyuki Tanaka

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

We investigate a hybrid quantum-classical solution method to the mean-variance portfolio optimization problems. Starting from real financial data statistics and following the principles of the Modern Portfolio Theory, we generate…

Quantum Physics · Physics 2019-07-01 Davide Venturelli , Alexei Kondratyev