Grimm Ryan T, Eaves Joel D
Department of Chemistry, University of Colorado Boulder, Boulder, Colorado 80309, USA.
Phys Rev Lett. 2024 Jun 28;132(26):267101. doi: 10.1103/PhysRevLett.132.267101.
Inspired by path integral solutions to the quantum relaxation problem, we develop a numerical method to solve classical stochastic differential equations with multiplicative noise that avoids averaging over trajectories. To test the method, we simulate the dynamics of a classical oscillator multiplicatively coupled to non-Markovian noise. When accelerated using tensor factorization techniques, it accurately estimates the transition into the bifurcation regime of the oscillator and outperforms trajectory-averaging simulations with a computational cost that is orders of magnitude lower.
受量子弛豫问题的路径积分解启发，我们开发了一种数值方法来求解具有乘性噪声的经典随机微分方程，该方法避免了对轨迹进行平均。为了测试该方法，我们模拟了一个与非马尔可夫噪声乘性耦合的经典振子的动力学。当使用张量分解技术加速时，它能准确估计振子进入分岔区域的转变，并且在计算成本低几个数量级的情况下优于轨迹平均模拟。
