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We demonstrate that the performance of a quantum annealer on hard random Ising optimization problems can be substantially improved using quantum annealing correction (QAC). Our error correction strategy is tailored to the D-Wave Two device.…

Quantum Physics · Physics 2015-04-03 Kristen L. Pudenz , Tameem Albash , Daniel A. Lidar

Qubit-efficient optimization studies how large combinatorial problems can be addressed with quantum circuits whose width is far smaller than the number of logical variables. In quadratic unconstrained binary optimization (QUBO), objective…

Quantum Physics · Physics 2026-01-13 Gordon Ma , Dimitris G. Angelakis

In recent years, there has been significant research interest in solving Quadratic Unconstrained Binary Optimisation (QUBO) problems. Physics-inspired optimisation algorithms have been proposed for deriving optimal or sub-optimal solutions…

Artificial Intelligence · Computer Science 2023-09-12 Mayowa Ayodele , Richard Allmendinger , Manuel López-Ibáñez , Matthieu Parizy

As contemporary quantum computers do not possess error correction, any calculation performed by these devices can be considered an involuntary approximation. To solve a problem on a quantum annealer, it has to be expressed as an instance of…

We study quantum computing algorithms for solving certain constrained resource allocation problems we coin as Mission Covering Optimization (MCO). We compare formulations of constrained optimization problems using Quantum Annealing…

Quantum Physics · Physics 2022-05-05 Massimiliano Cutugno , Annarita Giani , Paul M. Alsing , Laura Wessing , Austars Schnore

Modern quantum annealers can find high-quality solutions to combinatorial optimisation objectives given as quadratic unconstrained binary optimisation (QUBO) problems. Unfortunately, obtaining suitable QUBO forms in computer vision remains…

In many applications, it makes sense to solve the least square problems with nonnegative constraints. In this article, we present a new multiplicative iteration that monotonically decreases the value of the nonnegative quadratic programming…

Numerical Analysis · Mathematics 2014-06-05 Xiao Xiao , Donghui Chen

An l0-regularized linear regression for a sparse signal reconstruction is implemented based on the quadratic unconstrained binary optimization (QUBO) formulation. In this method, the signal values are quantized and expressed as bit…

Information Theory · Computer Science 2022-03-01 Naoki Ide , Masayuki Ohzeki

Quantum annealing is a type of analog computation that aims to use quantum mechanical fluctuations in search of optimal solutions of QUBO (quadratic unconstrained binary optimization) or, equivalently, Ising problems. Since NP-hard problems…

Quantum Physics · Physics 2023-04-14 Elijah Pelofske , Georg Hahn , Hristo N. Djidjev

In this paper,we propose a Multi-Objective Sequential Quadratic Programming (MOSQP) algorithm for constrained multi-objective optimization problems,basd on a low-order smooth penalty function as the merit function for line search. The…

Optimization and Control · Mathematics 2025-03-13 Zanyang Kong

We present a method for improving the $b$-jet energy resolution in order to improve the signal sensitivity in searches for particles decaying to a $b$ quark and anti-$b$ quark. A correction function is computed for individual jets, which…

High Energy Physics - Experiment · Physics 2011-07-18 T. Aaltonen , A. Buzatu , B. Kilminster , Y. Nagai , W. Yao

This paper investigates smart home energy management in consideration of tradeoffs between residential privacy and energy costs. A multiobjective approach that minimizes energy costs and maximizes privacy protection is proposed. The…

Systems and Control · Electrical Eng. & Systems 2026-01-16 Hsuan-Hao Chang , Wei-Yu Chiu , Hongjian Sun , Chia-Ming Chen

Quantum devices can be used to solve constrained combinatorial optimization (COPT) problems thanks to the use of penalization methods to embed the COPT problem's constraints in its objective to obtain a quadratic unconstrained binary…

Quantum Physics · Physics 2021-01-26 Rodolfo Quintero , David Bernal , Tamás Terlaky , Luis F. Zuluaga

Simulating a quantum system is more efficient on a quantum computer than on a classical computer. The time required for solving the Schr\"odinger equation to obtain molecular energies has been demonstrated to scale polynomially with system…

Quantum Physics · Physics 2019-03-27 Hefeng Wang , Sabre Kais , Alán Aspuru-Guzik , Mark R. Hoffmann

In this article we want to demonstrate the effectiveness of the new D-Wave quantum annealer, D-Wave 2000Q, in dealing with real world problems. In particular, it is shown how the quantum annealing process is able to find global optima even…

Quantum Physics · Physics 2018-08-28 Daniele Ottaviani , Alfonso Amendola

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

Quantum annealing devices such as the ones produced by D-Wave systems are typically used for solving optimization and sampling tasks, and in both academia and industry the characterization of their usefulness is subject to active research.…

It is shown that by means of the approach based on the Quantum Hamilton-Jacobi equation, it is possible to modify the WKB expressions for the energy levels of quantum systems, when incorrect, obtaining exact WKB-like formulae. This extends…

Quantum Physics · Physics 2022-04-07 Mario Fusco Girard

We study the energy-critical wave equation in three dimensions, focusing on its ground state soliton, denoted by $W$. Using the Poincar\'e symmetry inherent in the equation, boosting $W$ along any timelike geodesic yields another solution.…

Analysis of PDEs · Mathematics 2024-09-10 Istvan Kadar

A recursive approach for shrinking coefficients of an atomic decomposition is proposed. The corresponding algorithm evolves so as to provide at each iteration a) the orthogonal projection of a signal onto a reduced subspace and b) the index…

General Mathematics · Mathematics 2009-11-10 M. Andrle , L. Rebollo-Neira , E. Sagianos