The University of Arizona
Please note that this event has ended!

Symmetry-informed model inference for active matter

Program in Applied Mathematics Colloquium

Symmetry-informed model inference for active matter
Series: Program in Applied Mathematics Colloquium
Location: MATH 501
Presenter: Jorn Dunkel, Department of Mathematics, MIT

Recent experimental advances enable high-resolution observations of biological and synthetic active matter across a wide range of length and time scales. A major challenge is to translate high-dimensional live-imaging data into PDE models that will allow us to predict and understand the emergent collective dynamics seen in experiments. Here, I will describe our current efforts to implement computational frameworks capable of learning interpretable continuum models directly from spatio-temporal tracking data. After outlining theoretical and computational challenges posed by state-of-the-art microscopy and sequencing data, we will show how symmetry concepts and recent algorithmic advances can be combined to construct efficient mode representations and robust inference schemes for automated model discovery. To illustrate the practical potential, we present example applications ranging from the undulatory locomotion of worms and snakes [1] to the collective dynamics of cells [2], active colloids and fish [3].

[1] Cohen, Hastewell, et al., PRL 130: 258402, 2023 [2] Romeo, Hastewell, et al., eLife  10: e68679, 2021 [3] Supekar et al., PNAS 120: e2206994120, 2023

 

Place: Math Building, Room 501  https://map.arizona.edu/89