Results 41 to 50 of about 3,222 (193)
Posiform planting: generating QUBO instances for benchmarking
Frontiers in Computer Science, 2023 We are interested in benchmarking both quantum annealing and classical algorithms for minimizing quadratic unconstrained binary optimization (QUBO) problems. Such problems are NP-hard in general, implying that the exact minima of randomly generated instances are hard to find and thus typically unknown. While brute forcing smaller instances is possible,
Georg Hahn +3 more
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QUBO Simplification by Singular Value Decomposition and Coefficient Elimination for Ising Machines
IEEE AccessIsing machines, including quantum annealing machines, can efficiently solve combinatorial optimization problems by formulating them as Quadratic Unconstrained Binary Optimization (QUBO). However, it is known that the solving performance of Ising machines
Shinnosuke Inaba +2 more
doaj +1 more source
Mapping Quantum Circuits to Modular Architectures with QUBO
2023 IEEE International Conference on Quantum Computing and Engineering (QCE), 2023 Submitted to IEEE QCE ...
Bandic, Medina +10 more
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PLoS ONE, 2022 The most advanced D-Wave Advantage quantum annealer has 5000+ qubits, however, every qubit is connected to a small number of neighbors. As such, implementation of a fully-connected graph results in an order of magnitude reduction in qubit count.
Alexander Teplukhin +4 more
doaj +1 more source
Advanced Intelligent Discovery, EarlyView.This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley +1 more source
On good encodings for quantum annealer and digital optimization solvers
Scientific Reports, 2023 Several optimization solvers inspired by quantum annealing have been recently developed, either running on actual quantum hardware or simulating it on traditional digital computers.
Alberto Ceselli, Marco Premoli
doaj +1 more source
QuDASH: Quantum-Inspired Rate Adaptation Approach for DASH Video Streaming
IEEE Access, 2023 Internet traffic is dramatically increasing with the development of network technologies and video streaming traffic accounts for large amount within the total traffic, which reveals the importance to guarantee the quality of content delivery service ...
Bo Wei +5 more
doaj +1 more source
A note on QUBO instances defined on Chimera graphs [PDF]
, 2013 McGeoch and Wang (2013) recently obtained optimal or near-optimal solutions to some quadratic unconstrained boolean optimization (QUBO) problem instances using a 439 qubit D-Wave Two quantum computing system in much less time than with the IBM ILOG CPLEX
Dash, Sanjeeb
core
Applying Ising Machines to Multi-objective QUBOs
Proceedings of the Companion Conference on Genetic and Evolutionary Computation, 2023 Multi-objective optimisation problems involve finding solutions with varying trade-offs between multiple and often conflicting objectives. Ising machines are physical devices that aim to find the absolute or approximate ground states of an Ising model.
Mayowa Ayodele +4 more
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Advanced Intelligent Discovery, EarlyView.Factorization machine with iterative quantum reverse annealing (FMIRA) leverages quantum reverse annealing to perform batch black‐box optimization. Factorization machine with quantum annealing (FMQA) is a widely used python package for solving black‐box optimization problems using D‐Wave quantum annealers.
Andrejs Tučs, Ryo Tamura, Koji Tsuda
wiley +1 more source