arXiv subjects

Vyas Ramasubramani

Publications and source records attributed to Vyas Ramasubramani.

3 recordsLinked to original sources

arXiv2021

Shape-Driven Caging Dynamics of Hard Polygons

The fundamentals of Brownian motion have been largely well understood since the early 20th century, with most recent additions focusing on understanding anomalous diffusion via rescaling of drag coefficents. That focus emphasizes long-time dynamic behavior, but recent results indicate that additional, secondary modes are also present at short and intermediate times in fluids of anisotropic particles. Here, we study the dynamics of a representative family of nearly-hard n-gons. Using molecular dynamics simulations, we study a distinct form of caging only present in anisotropic systems. We show that this caging behavior emerges in the mean squared displacement of n-gons at intermediate particle volume fractions. We then develop an extended Langevin theory directly coupling translational and rotational motion as a function of the relative anisotropy for different n-gons that predicts the observed caging behavior. Extending our theory to incorporate secondary, off-phase cross-correlations between particles further enables the prediction of both translational and rotational relaxation times of the system.

cond-mat.soft↗

arXiv2020

freud: A Software Suite for High Throughput Analysis of Particle Simulation Data

The freud Python package is a powerful library for analyzing simulation data. Written with modern simulation and data analysis workflows in mind, freud provides a Python interface to fast, parallelized C++ routines that run efficiently on laptops, workstations, and supercomputing clusters. The package provides the core tools for finding particle neighbors in periodic systems, and offers a uniform API to a wide variety of methods implemented using these tools. As such, freud users can access standard methods such as the radial distribution function as well as newer, more specialized methods such as the potential of mean force and torque and local crystal environment analysis with equal ease. While many comparable tools place a heavy emphasis on reading and operating on trajectory file formats, freud instead accepts numerical arrays of data directly as inputs. By remaining agnostic to its data source, freud is suitable for analyzing any coarse-grained particle simulation, regardless of the original data representation or simulation method. When used for on-the-fly analysis in conjunction with scriptable simulation software such as HOOMD-blue, freud enables smart simulations that adapt to the current state of the system, allowing users to study phenomena such as nucleation and growth.

physics.comp-ph↗

arXiv2018

Simple Data and Workflow Management with the signac Framework

Researchers in the field of materials science, chemistry, and computational physics are regularly posed with the challenge of managing large and heterogeneous data spaces. The amount of data increases in lockstep with computational efficiency multiplied by the amount of available computational resources, which shifts the bottleneck in the scientific process from data acquisition to data processing and analysis. We present a framework designed to aid in the integration of various specialized data formats, tools and workflows. The signac framework provides all basic components required to create a well-defined and thus collectively accessible and searchable data space, simplifying data access and modification through a homogeneous data interface that is largely agnostic to the data source, i.e., computation or experiment. The framework's data model is designed to not require absolute commitment to the presented implementation, simplifying adaption into existing data sets and workflows. This approach not only increases the efficiency with which scientific results can be produced, but also significantly lowers barriers for collaborations requiring shared data access.

cs.DB↗