Data-driven quantitative modeling of bacterial active nematics

TL;DR

This paper presents a data-driven approach to quantitatively model bacterial active nematics by combining comprehensive experimental measurements with a new microscopic model, enabling precise parameter estimation and understanding of active matter dynamics.

Contribution

The study introduces a novel active nematics system with bacterial swarms and develops a microscopic model fitted directly to experimental data, advancing quantitative active matter modeling.

Findings

Complex dynamics accurately reproduced by the model

All key parameters estimated from experimental data

Applicable to various dense suspension systems

Abstract

Active matter comprises individual units that convert energy into mechanical motion. In many examples, such as bacterial systems and biofilament assays, constituent units are elongated and can give rise to local nematic orientational order. Such `active nematics' systems have attracted much attention from both theorists and experimentalists. However, despite intense research efforts, data-driven quantitative modeling has not been achieved, a situation mainly due to the lack of systematic experimental data and to the large number of parameters of current models. Here we introduce a new active nematics system made of swarming filamentous bacteria. We simultaneously measure orientation and velocity fields and show that the complex spatiotemporal dynamics of our system can be quantitatively reproduced by a new type of microscopic model for active suspensions whose important parameters are all estimated from comprehensive experimental data. This provides unprecedented access to key effective parameters and mechanisms governing active nematics. Our approach is applicable to different types of dense suspensions and shows a path towards more quantitative active matter research.