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首页> 外文期刊>Journal of chemical theory and computation: JCTC >A Stochastic, Resonance-Free Multiple Time-Step Algorithm for Polarizable Models That Permits Very Large Time Steps
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A Stochastic, Resonance-Free Multiple Time-Step Algorithm for Polarizable Models That Permits Very Large Time Steps

机译:极化模型的随机,无共振多时步算法,允许非常大的时步

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Molecular dynamics remains one of the most widely used computational tools in the theoretical molecular sciences to sample an equilibrium ensemble distribution and/or to study the dynamical properties of a system. The efficiency of a molecular dynamics:calculation is limited by the size of the time step that can be employed, which is dictated by the highest frequencies in the system. However, many properties of interest are connected to low-frequency, long time-scale phenomena, requiring many small time steps to capture. This ubiquitous problem can be ameliorated by employing multiple time-step algorithms, which assign different time steps to forces acting on different time scales. In such a scheme, fast forces are evaluated more frequently than slow forces, and as the former are often computationally much cheaper to evaluate, the savings can be significant. Standard multiple time-step approaches are limited, however, by resonance phenomena,, wherein motion on the fastest time scales limits the step sizes that can be chosen for the slower time scales. In atomistic models of biomolecular systems, for example, the largest time step is typically limited to around 5 fs. Previously, we introduced an isokinetic extended phase-space algorithm (Minary et al. Phys. Rev. Lett. 2004, 93, 150201) and its stochastic analog (Leimkuhler et al. Mol. Phys. 2013, 111, 3579) that eliminate resonance phenomena through a set of kinetic energy constraints. In simulations of a fixed-charge flexible model of liquid water, for example, the time step that could be assigned to the slow forces approached 100 fs. In this paper, we develop a stochastic isokinetic algorithm for multiple time-step molecular dynamics calculations using a polarizable model based on fluctuating dipoles. The scheme developed here employs two sets of induced dipole moments, specifically, those associated with short-range interactions and those associated with a full set of interactions. The scheme is demonstrated on the polarizable AMOEBA water model. As was seen with fixed-charge models, we are able to obtain large time steps exceeding 100 fs, allowing calculations to be performed 10 to 20 times faster than standard thermostated molecular dynamics.
机译:在理论分子科学中,分子动力学仍然是最广泛使用的计算工具之一,用于采样平衡总体分布和/或研究系统的动力学特性。分子动力学的效率:计算受到可以采用的时间步长的限制,该时间步长取决于系统中的最高频率。但是,许多感兴趣的属性与低频长时标现象有关,需要许多小的时间步长才能捕获。普遍存在的问题可以通过采用多个时间步长算法来解决,该算法将不同的时间步长分配给作用在不同时间尺度上的力。在这种方案中,快速力的评估要比慢速力的评估更为频繁,并且由于前者在计算上通常要便宜得多,因此节省下来的费用可观。但是,标准的多个时间步长方法受到共振现象的限制,其中,最快时标上的运动会限制可为较慢时标选择的步长。例如,在生物分子系统的原子模型中,最大时间步长通常限制在5 fs左右。以前,我们引入了等速扩展相空间算法(Minary等人,Phys。Rev. Lett。2004,93,150201)及其随机模拟(Leimkuhler等人,Mol。Phys。2013,111,3579)来消除共振。通过一组动能约束现象。例如,在液态水的固定电荷柔性模型的仿真中,可以分配给慢力的时间步长接近100 fs。在本文中,我们使用基于波动偶极子的可极化模型,开发了用于多个时间步分子动力学计算的随机等速算法。这里开发的方案采用了两组感应偶极矩,特别是与短程相互作用相关的磁矩和与整套相互作用相关的偶极矩。该方案在极化的AMOEBA水模型上得到了证明。从固定电荷模型可以看出,我们能够获得超过100 fs的较大时间步长,从而使计算速度比标准恒温分子动力学快10至20倍。

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