论文标题
动力学三重动力学：可逆动力学的量子蒙特卡洛算法
Dynamical Triplet Unravelling: A quantum Monte Carlo algorithm for reversible dynamics
论文作者
论文摘要
我们引入了一种量子蒙特卡洛方法，以模拟相关多体系统的可逆动力学。我们的方法基于时间进化运算符的拉普拉斯变换，该操作员与大多数量子蒙特卡洛方法相反，可以在更长的时间访问动力学。蒙特卡洛轨迹是通过在零件随机确定的可逆进化中实现的，其中自由动力学与两个过程中的量子跳跃散布在一起。动态标志问题通过所谓的死权近似绕过，该近似在更长的时间内稳定了多体相。我们通过模拟XXZ模型中的自旋激发传播和量子链链中的动态限制来基准我们的方法，并展示如何从Laplace表示中提取动态信息。
We introduce a quantum Monte Carlo method to simulate the reversible dynamics of correlated many-body systems. Our method is based on the Laplace transform of the time-evolution operator which, as opposed to most quantum Monte Carlo methods, makes it possible to access the dynamics at longer times. The Monte Carlo trajectories are realised through a piece-wise stochastic-deterministic reversible evolution where free dynamics is interspersed with two-process quantum jumps. The dynamical sign problem is bypassed via the so-called deadweight approximation, which stabilizes the many-body phases at longer times. We benchmark our method by simulating spin excitation propagation in the XXZ model and dynamical confinement in the quantum Ising chain, and show how to extract dynamical information from the Laplace representation.
