Speaker
Description
Stochastic thermodynamics explores the thermodynamic structure of small systems based on stochastic processes. However, conventional stochastic thermodynamics has relied on the Markov assumption---the assumption that the system's history dependence is negligible---except for a few specific non-Markov models. Since many real physical phenomena have history dependence, it is important to develop stochastic thermodynamics for more general non-Markov processes with memory effects. In this talk, we present stochastic thermodynamics for non-Markov jump processes. We develop the Fourier embedding and derive the master equation for general non-Markov jump processes as a new tool to formulate the time-reversal symmetry. We show the first and second laws for non-Markov jump processes. Finally, we present two new non-Markov models that can be investigated by our framework from thermodynamic viewpoints.
