Simulating dynamics of the two-dimensional transverse-field Ising model: A comparative study of large-scale classical numerics

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The quantum dynamics of many-qubit systems is an outstanding problem that has recently driven significant advances in both numerical methods and programmable quantum processing units (QPUs). In this work, we employ a comprehensive toolbox of state-of-the-art numerical approaches to classically simulate the dynamics of the two-dimensional transverse-field Ising model. Our methods include three different tensor-network techniques—matrix product states, tree tensor networks, and two-dimensional tensor networks under the belief propagation approximation—as well as time-dependent variational Monte Carlo with neural quantum states. We focus on two paradigmatic dynamical protocols: (1) quantum annealing through a critical point and (2) postquench dynamics. Our extensive results show the quantitative predictions of various state-of-the-art numerical methods providing a benchmark for future numerical investigations and experimental studies with the aim to push the limitations on classical and QPUs. In particular, our work connects classical simulability to different regimes associated with quantum dynamics in Rydberg arrays—namely, quasiadiabatic dynamics, the Kibble-Zurek mechanism, and quantum quenches.