Energy Transport in Sachdev-Ye-Kitaev Networks Coupled to Thermal Baths

TL;DR

This paper develops a framework to analyze energy transport in Sachdev-Ye-Kitaev networks coupled to thermal baths, revealing diffusive behavior, the influence of bath configurations, and a bound relating diffusion to quantum chaos.

Contribution

It introduces a new method to study non-equilibrium energy transport in SYK networks, including analytical expressions for diffusion constants and insights into chaos-transport relationships.

Findings

Diffusive energy transport in SYK networks confirmed.

Bulk bath driving accelerates steady state convergence.

Diffusion constant bounds by chaos propagation rate.

Abstract

We develop a general framework for studying the equilibrium and non-equilibrium properties of arbitrary networks of Sachdev-Ye-Kitaev clusters coupled to thermal baths. We proceed to apply this technique to the problem of energy transport, which is known to be diffusive due to the strange metal behavior of these models. We use the external baths to impose a temperature gradient in the system and study the emerging non-equilibrium steady state using the Schwinger-Keldysh formalism. We consider two different configurations for the baths, implementing either a boundary or bulk driving, and show that the latter leads to a significantly faster convergence to the steady state. This setup allows us to compute both the temperature and frequency dependence of the diffusion constant. At low temperatures, our results agree perfectly with the previously known values for diffusivity in the conformal limit. We also establish a relationship between energy transport and quantum chaos by showing that the diffusion constant is upper bounded by the chaos propagation rate at all temperatures. Moreover, we find a simple analytical form for the non-equilibrium Green's functions in the linear response regime and use it to derive exact closed-form expressions for the diffusion constant in various limits. We mostly focus on uniform one-dimensional chains, but we also discuss higher-dimensional generalizations.