论文标题
介绍用于模拟动态属性的步骤蒙特卡洛方法
Introducing the step Monte Carlo method for simulating dynamic properties
论文作者
论文摘要
在这项工作中，我们引入了对蒙特卡洛算法的简单修改，我们称之为蒙特卡洛（SMC）。 SMC方法允许模拟远离平衡的过程，并获取有关正在研究的系统动态特性的信息。在此处提出的方法中，接受最终（试验）状态的概率取决于激活能量，而不取决于最终状态和初始状态之间的相对能量。通过沿着连接初始位置和试验位置的路径产生中间状态，可以持续探测此障碍高度。重要的是，要计算激活能量，我们的模型只需要了解哈密顿量的知识，而不必引入其他输入参数，例如过渡速率等。对于简单的自旋模型，可以解释SMC的详细信息。其结果与在随机Landau-Lifshitz-Gilbert框架内获得的结果的比较表明SMC的正确性。我们认为，这里提出的方法可以应用于模拟其他过程，例如经典原子和复杂流体的动力学，扩散，成核，表面吸附和晶体生长过程。
In this work, we introduce a simple modification of the Monte Carlo algorithm, which we call step Monte Carlo (sMC). The sMC approach allows to simulate processes far from equilibrium and obtain information about the dynamic properties of the system under investigation. In the approach proposed here the probability of accepting the final (trial) state depends on the activation energy, not on the relative energy between the final and initial state. This barrier height is probed on an ongoing basis, by generating intermediate states along the path connecting the initial and trial positions. Importantly, to calculate the activation energy, our model only requires knowledge of the Hamiltonian without having to introduce additional input parameters such as transition rates etc. The details of sMC are explained for the case of a simple spin model. The comparison of its results with the ones obtained within the frame of stochastic Landau-Lifshitz-Gilbert indicates the correctness of sMC. In our opinion, the proposed here method can be applied to simulate other processes, for example dynamics of classical atoms and complex fluids, diffusion, nucleation, surface adsorption and crystal growth processes.
