Accessing intermediate states in quantum annealing via quench readout or ideal measurements reveals a timing trade-off that improves diversity and convergence for non-convex Pareto fronts in multi-objective optimization.
Zitzler:Evolutionary algorithms for multiobjective optimization: Methods and applications(Shaker Ithaca, 1999), V ol
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Utilizing intermediate states in quantum annealing for multi-objective optimization
Accessing intermediate states in quantum annealing via quench readout or ideal measurements reveals a timing trade-off that improves diversity and convergence for non-convex Pareto fronts in multi-objective optimization.