Signature of topology via heat transfer analysis in the Su-Schrieffer-Heeger (SSH) model

TL;DR

This study investigates how heat transfer analysis can reveal topological phase transitions in the SSH model, showing heat flow suppression and asymmetry changes as indicators of different phases.

Contribution

It introduces thermodynamic heat flow analysis as a novel method to identify topological phases in the SSH model, including effects of system size and bath types.

Findings

Heat flow significantly decreases during topological transition.

Heat flow asymmetry appears only with bosonic baths, not fermionic.

Edge effects influence heat rectification in small systems.

Abstract

In this work, we explore the potential of thermodynamics as a tool for identifying the topological phase transition. Specifically, we focus on a one-dimensional Su-Schrieffer-Heeger (SSH) chain sandwiched between two fermionic baths. To investigate distinctive thermodynamic signatures associated with the topological phase, we employ heat flow analysis. Our results, derived using a global master equation, unveil a significant suppression of heat flow as we transition from the trivial to the topological phase. This decline in heat flow can be attributed to the reduction in transmission coefficients of non-zero energy modes within the topological phase. It may serve as an indicator of a phase transition. Furthermore, we investigate the heat flow asymmetry to search for phase transition indicators. Interestingly, no asymmetry is observed when employing fermionic baths. However, upon substituting fermionic baths with bosonic ones, we report a non-zero heat flow asymmetry. For the SSH model with a few fermionic sites, this asymmetry is more pronounced in the topological phase compared to the trivial phase. Therefore, the observed behavior of the heat diode provides an additional means of distinguishing between the topological and trivial phases. Finally, we delve into the contributions from both bulk and edge effects in heat flow and rectification to explore the impact of small system sizes on our findings.