发表机构
Center for Computational Quantum Physics, Flatiron Institute（平顿研究所计算量子物理中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文用含时变分蒙特卡洛（t-VMC）模拟D-Wave量子退火实验，通过改进方法解决数值失效问题，成功逼近量子处理单元结果并拓展经典模拟前沿。
AI 中文摘要
可编程量子退火器可在大型非平凡图上实现受挫横场伊辛模型的实时动力学。King等人近期研究指出，张量网络、神经量子态等经典方法对这类实验进行经典模拟需要指数级计算资源。本文采用适配自旋玻璃动力学的关联态，通过含时变分蒙特卡洛（t-VMC）对D-Wave自旋玻璃退火协议进行数值模拟。针对所考虑的二维圆柱、三维二聚体、金刚石及双团实例，在7ns和20ns退火时间下，研究表明系统增大变分近似规模可使t-VMC逼近量子处理单元（QPU）的最终两自旋关联误差。本文还对一个无已知其他变分方法可行的挑战性双团实例开展了精确大规模模拟，发现其与量子退火器结果高度吻合。通过消融研究，本文确定马尔可夫链混合差、高方差局域能量估计器及随机龙格-库塔误差估计是主要数值失效模式，采用并行调温、模糊采样及重要性加权微分方程求解器解决了这些数值问题，明确了稳定大规模t-VMC模拟的数值要求。本文结果拓展了经典模拟的前沿，同时对该尺度量子动力学模拟的计算成本给出了现实评估。
英文摘要
Programmable quantum annealers can realize real-time dynamics of frustrated transverse-field Ising models on large, nontrivial graphs. Recent work by King et al. argued that the classical simulation of such experiments would require exponential computational resources for classical methods such as tensor networks and neural quantum states. Here, we numerically simulate the D-Wave spin-glass annealing protocol with time-dependent variational Monte Carlo (t-VMC) using a correlator state tailored to spin-glass dynamics. For the two-dimensional cylinder, three-dimensional dimer, diamond, and biclique instances considered, at annealing times of 7 and 20 ns, we show that systematically increasing the variational ansatz size enables t-VMC to approximate the final two-spin correlation errors of the quantum processing unit (QPU). We also perform an accurate large-scale simulation of a challenging biclique instance for which no other variational method is known to work, and we find close agreement with the quantum annealer. Through ablation studies, we identify poor Markov-chain mixing, high-variance local-energy estimators, and stochastic Runge-Kutta error estimates as the principal numerical failure modes. We address these numerical issues by using parallel tempering, blurred sampling and an importance-weighted differential equation solver, thereby clarifying the numerical requirements for stable, large-scale t-VMC simulations. Our results extend the frontier of classical simulation while providing a realistic assessment of the computational costs of simulating quantum dynamics at this scale.
