  Quantum computers hold the promise of solving certain problems that lie
beyond the reach of conventional computers. Establishing this capability,
especially for impactful and meaningful problems, remains a central challenge.
One such problem is the simulation of nonequilibrium dynamics of a magnetic
spin system quenched through a quantum phase transition. State-of-the-art
classical simulations demand resources that grow exponentially with system
size. Here we show that superconducting quantum annealing processors can
rapidly generate samples in close agreement with solutions of the Schr\"odinger
equation. We demonstrate area-law scaling of entanglement in the model quench
in two-, three- and infinite-dimensional spin glasses, supporting the observed
stretched-exponential scaling of effort for classical approaches. We assess
approximate methods based on tensor networks and neural networks and conclude
that no known approach can achieve the same accuracy as the quantum annealer
within a reasonable timeframe. Thus quantum annealers can answer questions of
practical importance that classical computers cannot.
