The world surrounding us, including all living matter and various artificial complex systems, mostly operates far from thermal equilibrium. A major goal of current statistical physics and thermodynamics is to unravel the fundamental principles that govern the individual dynamics and collective behavior of such nonequilibrium systems. A novel key concept to describe and classify nonequilibrium systems is the stochastic entropy production, which explicitly quantifies the breaking of time-reversal symmetry. However, so far, little attention has been paid to the implications of non-conservative interactions, such as time-delayed or non-reciprocal interactions, which cannot be represented by Hamiltonians contrasting all interactions traditionally considered in statistical physics. Non-conservative interactions indeed emerge commonly in biological, chemical and feedback systems, and are widespread in engineering and machine learning. In this talk, I will use simple stochastic models to discuss technical challenges and unexpected physical phenomena induced by non-reciprocity [1,2] and time delay [3,4].
[1] Loos and Klapp, NJP 22, 123051 (2020)
[2] Loos, Hermann, and Klapp, Entropy 23, 696 (2021)
[3] Loos and Klapp, Sci. Rep. 9, 2491 (2019)
[4] Holubec, Geiss, Loos, Kroy, and Cichos, PRL 127, 258001 (2021)
Marco Baiesi, Gianmaria Falasco
