5 papers
Local imperfect feedback control in non-equilibrium biophysical systems enabled by thermodynamic constraints
Carlos Floyd, Aaron R. Dinner, Suriyanarayanan Vaikuntanathan
How biological networks achieve robust control despite relying on imperfect, local information remains an important open question. Here, we identify thermodynamic constraints that…
In-context learning emerges in chemical reaction networks without attention
Carlos Floyd, Hector Manuel Lopez Rios, Aaron R. Dinner +1
We investigate whether chemical processes can perform in-context learning (ICL), a mode of computation typically associated with transformer architectures. ICL allows a system to i…
Renormalized mechanics and stochastic thermodynamics of growing vesicles
Jordan L. Shivers, Michael Nguyen, Aaron R. Dinner +2
Uncovering the rules governing the nonequilibrium dynamics of the membranes that define biological cells is of central importance to understanding the physics of living systems. We…
Learning to control non-equilibrium dynamics using local imperfect gradients
Carlos Floyd, Aaron R. Dinner, Suriyanarayanan Vaikuntanathan
Standard approaches to controlling dynamical systems involve biologically implausible steps such as backpropagation of errors or intermediate model-based system representations. Re…
Tailoring interactions between active nematic defects with reinforcement learning
Carlos Floyd, Aaron R. Dinner, Suriyanarayanan Vaikuntanathan
Active nematics, formed from a liquid crystalline suspension of active force dipoles, are a paradigmatic active matter system whose study provides insights into how chemical drivin…