Results 41 to 50 of about 2,742,325 (160)

Finding Debt Cycles: QUBO Formulations for the Maximum Weighted Cycle Problem Solved Using Quantum Annealing

Mathematics, 2023
The problem of finding the maximum weighted cycle in a directed graph map to solve optimization problems is NP-hard, implying that approaches in classical computing are inefficient. Here, Quantum computing might be a promising alternative.
Hendrik Künnemann, Frank Phillipson
doaj   +1 more source

Quantum Spectral Clustering Framework via Compact Circuit Structures

Advanced Quantum Technologies, Volume 9, Issue 10, October 2026.
Can a quantum computer cluster data without ever reading the full kernel? This work shows that compact, parameterized circuits estimate the Laplacian quadratic forms directly and perform clustering, without explicitly constructing the full quantum fidelity‐kernel matrix.
Hyeong‐gyu Kim, Siheon Park, June‐Koo Kevin Rhee   +2 more
wiley   +1 more source

Quantum Annealing for Resource Allocation in Next-Generation Wireless Communication Networks: A QUBO Modeling Guide

IEEE Open Journal of the Communications Society
Resource allocation in next-generation (NG) wireless communication networks, including uncrewed aerial vehicle (UAV)-assisted networks, and space-air-ground integrated networks (SAGINs), often involves discrete-variable combinatorial formulations ...
Nguyen Xuan Tung, Le Tung Giang, Mai Dinh Cong, Pham Dang Anh Duc, Nguyen Hoang Viet, Trinh van Chien, Lajos Hanzo   +6 more
doaj   +1 more source

Device‐to‐System Perspectives on Scalable Ising Machines for Physics‐Driven Computing

Advanced Quantum Technologies, Volume 9, Issue 10, October 2026.
Emerging‐device‐based Ising machines exploit conductance programmability, intrinsic stochasticity, and oscillator dynamics as physical primitives for combinatorial optimization. This review establishes a device‐to‐system framework linking these physical properties to computational functions and crossbar‐based, stochastic p‐bit, and oscillator‐based ...
Sangwook Youn, Hwiho Hwang, Jaeung Lee, Heesu Seo, Hyungjin Kim   +4 more
wiley   +1 more source

Development of Hamiltonian for Structural Applications by Quantum Annealing Assuming Finite Element Method

International Journal for Numerical Methods in Engineering, Volume 127, Issue 17, 15 September 2026.
ABSTRACT Quantum annealing is emerging as a practical tool for large‐scale combinatorial optimization. We map continuum displacements and element densities to binary variables, turning both deformation analysis and topology optimization into quadratic unconstrained binary optimization (QUBO) problems that run on today's annealers.
Rio Honda, Katsuhiro Endo, Yudai Suzuki, Yoshiki Matsuda, Shu Tanaka, Mayu Muramatsu   +5 more
wiley   +1 more source

Multi-Objective Portfolio Optimization Using a Quantum Annealer

Mathematics
In this study, the portfolio optimization problem is explored, using a combination of classical and quantum computing techniques. The portfolio optimization problem with specific objectives or constraints is often a quadratic optimization problem, due to
Esteban Aguilera, Jins de Jong, Frank Phillipson, Skander Taamallah, Mischa Vos   +4 more
doaj   +1 more source

Fundamental Challenges, Physical Implementations, and Integration Strategies for Ising Machines in Large‐Scale Optimization Tasks

Advanced Electronic Materials, Volume 12, Issue 17, 7 September 2026.
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley   +1 more source

On some features of Quadratic Unconstrained Binary Optimization with random coefficients [PDF]

Quadratic Unconstrained Binary Optimization (QUBO or UBQP) is concerned with maximizing/minimizing the quadratic form $H(J, η) = W \sum_{i,j} J_{i,j} η_{i} η_{j}$ with $J$ a matrix of coefficients, $η\in \{0, 1\}^N$ and $W$ a normalizing constant.
Scoppola, Benedetto, Troiani, Alessio, Isopi, Marco   +2 more
core   +3 more sources

Lagrangian duality in quantum optimization: Overcoming QUBO limitations for constrained problems

Physical Review Research
We propose an approach to solving constrained combinatorial optimization problems based on embedding the concept of Lagrangian duality into the framework of adiabatic quantum computation.
Einar Gabbassov, Gili Rosenberg, Artur Scherer   +2 more
doaj   +1 more source

Analysis of the relation between quadratic unconstrained binary optimization and the spin-glass ground-state problem

Physical Review Research, 2019
We analyze the transformation of quadratic unconstrained binary optimization (QUBO) from its conventional Boolean presentation into an equivalent spin-glass problem with coupled ±1 spin variables exposed to a site-dependent external field.
Stefan Boettcher
doaj   +1 more source