Results 51 to 60 of about 1,254,139 (165)
Load Balancing For High Performance Computing Using Quantum Annealing
Load balancing is the distribution of computational work between available processors. Here, we investigate the application of quantum annealing to load balance two paradigmatic algorithms in high performance computing.
Chancellor, Nicholas +3 more
core +1 more source
Quantum annealing for combinatorial optimization: a benchmarking study
npj Quantum InformationQuantum annealing (QA) has the potential to significantly improve solution quality and reduce time complexity in solving combinatorial optimization problems compared to classical optimization methods.
Seongmin Kim +5 more
doaj +1 more source
IEEE Transactions on Quantum EngineeringThe manufacturing industry encounters numerous optimization problems, one of which is the optimization of storage location assignment (OSLA) problem in logistics. OSLA is a combinatorial optimization problem focused on improving the efficiency of picking
Hiromitsu Kigure +3 more
doaj +1 more source
Scientific ReportsDiverse cases regarding the impact, with its related factors, of the COVID-19 pandemic on mental health have been reported in previous studies. In this study, multivariable datasets were collected from 751 college students who could be easily affected by
Junggu Choi +7 more
doaj +1 more source
Deterministic quantum annealing expectation-maximization algorithm
, 2017 Maximum likelihood estimation (MLE) is one of the most important methods in machine learning, and the expectation-maximization (EM) algorithm is often used to obtain maximum likelihood estimates.
Yuki Sughiyama +2 more
core +1 more source
Quantum Annealing for Staff Scheduling in Educational Environments
Publisher Copyright: © 2026 IEEE.We address a novel staff allocation problem that arises in the organization of collaborators among multiple school sites and educational levels.
Osaba, Eneko +2 more
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Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing
Advanced Intelligent Systems, Volume 8, Issue 4, April 2026.This Roadmap outlines the transformative role of artificial intelligence‐augmented additive manufacturing, highlighting advances in design, monitoring, and product development. By integrating tools such as generative design, computer vision, digital twins, and closed‐loop control, it presents pathways toward smart, scalable, and autonomous additive ...
Ali Zolfagharian +37 more
wiley +1 more source
Quantum Optimization, Machine Learning, Annealing, and Neural Networks
6896This chapter investigates the application of quantum computing to optimization, a field traditionally dominated by classical methods but increasingly limited by computational demands in tackling complex, large-scale problems.
Sharma, Shivam, Halffmann, Pascal
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End‐to‐End Portfolio Optimization with Hybrid Quantum Annealing
Advanced Quantum Technologies, Volume 9, Issue 4, April 2026.This works presents a hybrid quantum‐classical framework for portfolio optimization that combines quantum assisted asset selection and rebalancing with classical weight allocation. The approach processes real market data, embeds it into Quadratic Unconstrained Binary Optimization formulations, and evaluates performance within a unified workflow ...
Sai Nandan Morapakula +5 more
wiley +1 more source
Deterministic and stochastic quantum annealing approaches
, 2005 "Quantum annealing employs quantum fluctuations in frustrated systems or networks to anneal the system down to its ground state, or more generally to its so-called minimum cost state.
Santoro, Giuseppe Ernesto +9 more
core +1 more source