Numerical simulations of a box model for quantum annealing reveal residual energy largely independent of landscape roughness and annealing depth, with flat energy gaps proposed to explain diabatic trapping.
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MTQA embeds multiple NP-hard problems such as minimum vertex cover and graph partitioning into spatially distinct regions on quantum hardware, delivering comparable solution quality to single-task annealing with reduced time-to-solution.
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Box model of quantum annealing
Numerical simulations of a box model for quantum annealing reveal residual energy largely independent of landscape roughness and annealing depth, with flat energy gaps proposed to explain diabatic trapping.
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Multi-tasking through quantum annealing
MTQA embeds multiple NP-hard problems such as minimum vertex cover and graph partitioning into spatially distinct regions on quantum hardware, delivering comparable solution quality to single-task annealing with reduced time-to-solution.