Grantee: ** Massachusetts Institute of Technology**, Cambridge, MA, USA

Researcher: Jeremy England, Ph.D.

Grant Title: Self-organization in driven many-body assemblies: Predictive principles from non-equilibrium statistical thermodynamics

https://doi.org/10.37717/220020476

Program Area: Studying Complex Systems

Grant Type: Scholar Award

Amount: $450,000

Year Awarded: 2016

Duration: 6 years

**Self-organization in driven many-body assemblies: Predictive principles from non-equilibrium statistical thermodynamics**

The study of complexity encompasses a sometimes dauntingly wide range of scientific fields. Nonetheless, a significant plurality of complex systems satisfy the following conditions: they are made of many interacting particles that can be assumed to obey Newton‘s Laws, and they are driven by external forces while surrounded by a thermal bath with a well-defined temperature. Within this “big tent” of nonequilibrium many-body assemblies we can fit subjects as diverse as turbulent fluids, active gels, classical computers, and even living organisms. And, despite their great disparity, we expect that all of these phenomena will be constrained in what physical properties they exhibit by the dictates of general theoretical results that have been proven for the far-from-equilibrium regime in the last two decades.

In particular, it has been established that the probability distributions for dynamics of systems thus described obey a general thermodynamic constraint: the probability of seeing the system execute a particular trajectory is exponentially greater than that of the trajectory’s time-reversed movie in proportion to the amount of heat dissipated during the forward movie. Put another way, as a result of the underlying time-reversibility of Newtonian mechanics, any apparent statistical irreversibility in the dynamical direction of a driven system’s stochastic evolution has to be ‘paid for’ with the transfer of energy to the surrounding thermal bath. This heat can either be supplied by going downhill in internal energy, or, more intriguingly, through the absorption of work from surrounding drives.

The central goal of England Group at MIT is to exploit this general relationship between statistical irreversibility and the absorption and dissipation of work to derive and test predictive principles for understanding the physics of many types of complex systems.