Results 41 to 50 of about 18,556 (186)
IEEE AccessIsing machines, including quantum annealing machines, are promising next-generation computers for combinatorial optimization problems. However, due to hardware limitations, most Ising-type hardware can only solve objective functions expressed in linear ...
Kazuki Ikeuchi +2 more
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Analog Neural Programmable Optimizers in CMOS VLSI Technologies [PDF]
, 1992 A 3-μm CMOS IC is presented demonstrating the concept of an analog neural system for constrained optimization. A serial time-multiplexed general-purpose architecture is introduced for the real-time solution of this kind of problem in MOS VLSI.
Domínguez Castro, Rafael +3 more
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Iterated Tabu Search for the Unconstrained Binary Quadratic Optimization Problem [PDF]
Informatica, 2006 Given a set of objects with profits (any, even negative, numbers) assigned not only to separate objects but also to pairs of them, the unconstrained binary quadratic optimization problem consists in finding a subset of objects for which the overall profit is maximized.
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Quantum-enhanced reinforcement learning for finite-episode games with discrete state spaces
, 2017 Quantum annealing algorithms belong to the class of metaheuristic tools, applicable for solving binary optimization problems. Hardware implementations of quantum annealing, such as the quantum annealing machines produced by D-Wave Systems, have been ...
Compostella, Gabriele +3 more
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QUBO.jl: A Julia Ecosystem for Quadratic Unconstrained Binary Optimization
, 2023 We present QUBO.jl, an end-to-end Julia package for working with QUBO (Quadratic Unconstrained Binary Optimization) instances. This tool aims to convert a broad range of JuMP problems for straightforward application in many physics and physics-inspired solution methods whose standard optimization form is equivalent to the QUBO.
Xavier, Pedro Maciel +5 more
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Multi-Objective Optimization Technique Based on QUBO and an Ising Machine
IEEE AccessWith an increase in the complexity of society, solving multi-objective optimization problems (MOPs) has become crucial. In this study, we introduced a novel method called “quadratic unconstrained binary optimization based on the weighted normal ...
Hiroshi Ikeda, Takashi Yamazaki
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Prime factorization using quantum annealing and computational algebraic geometry
, 2016 We investigate prime factorization from two perspectives: quantum annealing and computational algebraic geometry, specifically Gr\"obner bases. We present a novel scalable algorithm which combines the two approaches and leads to the factorization of all ...
Alghassi, Hedayat, Dridi, Raouf
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Advanced Science, EarlyView.A probabilistic framework based on random time‐space coding metasurfaces enables control of the spatial distribution of electromagnetic fields temporal statistics. By tailoring the marginal and joint distributions of random codes, electromagnetic fields with desired mean and variance patterns are realized, enabling simultaneous transmission and jamming.
Jia Cheng Li +3 more
wiley +1 more source
Advanced Electronic Materials, EarlyView.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
Solving (Max) 3-SAT via Quadratic Unconstrained Binary Optimization
, 2023 We introduce a novel approach to translate arbitrary 3-SAT instances to Quadratic Unconstrained Binary Optimization (QUBO) as they are used by quantum annealing (QA) or the quantum approximate optimization algorithm (QAOA). Our approach requires fewer couplings and fewer physical qubits than the current state-of-the-art, which results in higher ...
Jonas Nüßlein +4 more
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