具有随机路径积分超动力学的周期势中的驱动扩散
Driven Diffusion in Periodic Potentials with Stochastic Path Integral Hyperdynamics
摘要：
本文利用最近提出的随机路径积分超动力学（SPHD）方法[L.Y. Chen和L.J.M. Horing，J. Chem. Phys. { \bf 126}，224103（2007）]。首先，我们考虑单个布朗粒子在空间周期势中运动并受到外部交流驱动力的情况。我们证实，在这个系统中没有随机共振，并发现在较高的频率的扩散系数$D$强烈抑制。第二种情况是二聚体在具有静态偏置的周期势中运动。对于这种情况，当二聚体键长是势晶格常数的整数倍时，对$D$有很强的抑制作用。对于这两种情况下，我们演示了如何SPHD允许我们提取的动态信息，正是在不同的偏差水平从一个单一的模拟运行，通过计算相应的统计重新加权因子。
英文摘要：
We consider the driven diffusion of Brownian particles in 1D periodic potentials using the recently proposed Stochastic Path Integral Hyperdynamics (SPHD) scheme [L.Y. Chen and L.J.M. Horing, J. Chem. Phys. {\bf 126}, 224103 (2007)]. First, we consider the case where a single Brownian particle is moving in a spatially periodic potential and subjected to an external ac driving force. We confirm that there is no stochastic resonance in this system and find that at higher frequencies the diffusion coefficient $D$ is strongly suppressed. The second case is that of a dimer moving in a periodic potential with a static bias. For this case, there's a strong suppression of $D$ when the dimer bond length is an integer multiple of the lattice constant of the potential. For both cases, we demonstrate how the SPHD allows us to extract the dynamical information exactly at different bias levels from a single simulation run, by calculating the corresponding statistical re-weighting factors.
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