Nevin Manimala Statistics

Data-Driven Discovery of Active Nematic Hydrodynamics

Phys Rev Lett. 2022 Dec 16;129(25):258001. doi: 10.1103/PhysRevLett.129.258001.


Active nematics can be modeled using phenomenological continuum theories that account for the dynamics of the nematic director and fluid velocity through partial differential equations (PDEs). While these models provide a statistical description of the experiments, the relevant terms in the PDEs and their parameters are usually identified indirectly. We adapt a recently developed method to automatically identify optimal continuum models for active nematics directly from spatiotemporal data, via sparse regression of the coarse-grained fields onto generic low order PDEs. After extensive benchmarking, we apply the method to experiments with microtubule-based active nematics, finding a surprisingly minimal description of the system. Our approach can be generalized to gain insights into active gels, microswimmers, and diverse other experimental active matter systems.

PMID:36608242 | DOI:10.1103/PhysRevLett.129.258001

By Nevin Manimala

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