Codebase release 0.2 for Pychastic

R. Waszkiewicz, Maciej Bartczak, Kamil Kolasa, M. Lisicki
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Abstract

In the last decade, Python-powered physics simulations ecosystem has been growing steadily, allowing greater interoperability, and becoming an important tool in numerical exploration of physical phenomena, particularly in soft matter systems. Driven by the need for fast and precise numerical integration in colloidal dynamics, here we formulate the problem of Brownian Dynamics (BD) in a mathematically consistent formalism of the Itō calculus, and develop a Python package to assist numerical computations. We show that, thanks to the automatic differentiation packages, the classical truncated Taylor-Itō integrators can be implemented without the burden of computing the derivatives of the coefficient functions beforehand. Furthermore, we show how to circumvent the difficulties of BD simulations such as calculations of the divergence of the mobility tensor in the diffusion equation and discontinuous trajectories encountered when working with dynamics on S^2S2 and SO(3)SO(3). The resulting Python package, Pychastic, is capable of performing BD simulations including hydrodynamic interactions at speeds comparable to dedicated implementations in lower-level programming languages, but with a much simpler end-user interface.
Codebase release 0.2 for Pychastic
在过去的十年中,python驱动的物理模拟生态系统一直在稳步发展,允许更大的互操作性,并成为物理现象数值探索的重要工具,特别是在软物质系统中。在胶体动力学中需要快速和精确的数值积分,在这里,我们将布朗动力学(BD)问题以数学上一致的ithi微积分形式表述,并开发了一个Python包来辅助数值计算。我们证明,由于自动微分包,经典截断泰勒-伊特基积分器可以在不需要事先计算系数函数导数的情况下实现。此外,我们还展示了如何绕过BD模拟的困难,例如扩散方程中迁移率张量散度的计算以及在处理S^2S2和SO(3)SO(3)上的动力学时遇到的不连续轨迹。由此产生的Python包Pychastic能够以与低级编程语言的专用实现相当的速度执行包括流体动力学交互在内的BD模拟,但具有更简单的最终用户界面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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