
Quantum computers hold the promise of solving certain problems that lie beyond the reach of conventional computers. However, establishing this capability, especially for impactful and meaningful problems, remains a central challenge. Here, we show that superconducting quantum annealing processors can rapidly generate samples in close agreement with solutions of the Schrödinger equation. We demonstrate area-law scaling of entanglement in the model quench dynamics of two-, three-, and infinite-dimensional spin glasses, supporting the observed stretched-exponential scaling of effort for matrix-product-state approaches. We show that several leading approximate methods based on tensor networks and neural networks cannot achieve the same accuracy as the quantum annealer within a reasonable time frame. Thus, quantum annealers can answer questions of practical importance that may remain out of reach for classical computation.
Quantum Physics, Statistical Mechanics (cond-mat.stat-mech), FOS: Physical sciences, Disordered Systems and Neural Networks (cond-mat.dis-nn), Disordered Systems and Neural Networks, Quantum Physics (quant-ph), Statistical Mechanics
Quantum Physics, Statistical Mechanics (cond-mat.stat-mech), FOS: Physical sciences, Disordered Systems and Neural Networks (cond-mat.dis-nn), Disordered Systems and Neural Networks, Quantum Physics (quant-ph), Statistical Mechanics
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