Decomposition of metric tensor in thermodynamic geometry in terms of relaxation timescales

TL;DR

This paper demonstrates that the metric tensor in thermodynamic geometry for underdamped Langevin systems can be decomposed into relaxation times, enabling heat engines to reach Carnot efficiency at finite power.

Contribution

It introduces a decomposition of the thermodynamic metric tensor in terms of relaxation times, linking timescale analysis to thermodynamic performance optimization.

Findings

Decomposition of the metric tensor in terms of relaxation times.

Achieving Carnot efficiency at finite power without trade-off.

Application to underdamped Langevin dynamics.

Abstract

Geometrical methods are extensively applied to thermodynamics including stochastic thermodynamics. In the case of slow-driving linear response regime, a geometrical framework, known as thermodynamic geometry, is established. The key of this framework is the thermodynamic length characterized by a metric tensor defined on the space of controlling variables. As the metric tensor is given in terms of the equilibrium time-correlation functions of the thermodynamic forces, it contains the information of timescales, which may be useful for analyzing the performance of heat engines. In this paper, we show that the metric tensor for underdamped Langevin dynamics can be decomposed in terms of the relaxation times of a system itself, which govern the timescales of the equilibrium time-correlation functions of the thermodynamic forces. As an application of the decomposition of the metric tensor, we demonstrate that it is possible to achieve Carnot efficiency at finite power by taking the vanishing limit of relaxation times without breaking trade-off relations between efficiency and power of heat engines in terms of thermodynamic geometry.