Tensor Network study of the (1+1)-dimensional Thirring Model

TL;DR

This paper uses Tensor Network methods, specifically Matrix Product States, to explore the phase diagram, soliton dynamics, and topological phase transitions in the (1+1)-dimensional massive Thirring model, a strongly-correlated system.

Contribution

It demonstrates the application of Tensor Network techniques to analyze the Thirring model's phase structure and topological features, advancing computational approaches in low-dimensional quantum field theories.

Findings

Mapped the phase diagram of the Thirring model

Showed the feasibility of studying soliton dynamics

Identified signatures of topological phase transitions

Abstract

Tensor Network methods have been established as a powerful technique for simulating low dimensional strongly-correlated systems for over two decades. Employing the formalism of Matrix Product States, we investigate the phase diagram of the massive Thirring model. We also show the possibility of studying soliton dynamics and topological phase transition via the Thirring model.