Sparse Identification of Continuum Theories of 2D Active Nematics

Active nematics are a class of non-equilibrium systems with constituents that consume energy at the molecular level to generate motion. 2D active nematics are often modeled using continuum theories that describe the dynamics of coarse-grained quantities, e.g. nematic director and fluid velocity, through partial differential equations (PDEs). While these models provide a statistically accurate description of the experiments, the identification of the right hydrodynamic parameters usually involves extensive simulations for a given choice of model. In this work, we employ a recently developed method to automatically identify the optimal continuum models, along with their parameters, directly from the spatio-temporal director and velocity data, via sparse fitting of the coarse-grained fields on to generic low order PDEs. This approach also provides a new way of testing existing theories of active nematics, since it makes minimal assumptions about the model structure.