Phase structure and real-time dynamics of the massive Thirring model in 1+1 dimensions using the tensor-network method

TL;DR

This paper investigates the phase structure and real-time dynamics of the massive Thirring model in 1+1 dimensions using tensor-network methods, providing numerical evidence of a BKT phase transition and exploring dynamic behavior.

Contribution

The study applies matrix product states and variational methods to analyze the phase transition and real-time dynamics of the massive Thirring model, a novel approach in this context.

Findings

Evidence of Berezinskii-Kosterlitz-Thouless phase transition

Numerical analysis of correlators supporting phase transition

Exploratory results on real-time dynamics using tensor networks

Abstract

We present concluding results from our study for zero-temperature phase structure of the massive Thirring model in 1+1 dimensions with staggered regularisation. Employing the method of matrix product states, several quantities, including two types of correlators, are investigated, leading to numerical evidence of a Berezinskii-Kosterlitz-Thouless phase transition. Exploratory results for real-time dynamics pertaining to this transition, obtained using the approaches of variational uniform matrix product state and time-dependent variational principle, are also discussed.