# Applying the tempered Lefschetz thimble method to the Hubbard model away from half-filling

## TL;DR

This paper advances the tempered Lefschetz thimble method to effectively address the sign problem in quantum Monte Carlo simulations of the Hubbard model away from half-filling, achieving accurate results on small lattices.

## Contribution

It develops a refined algorithm for precise expectation value estimation and demonstrates its effectiveness on the Hubbard model.

## Key findings

- The method accurately reproduces exact results for the Hubbard model.
- The algorithm effectively mitigates the sign problem in small lattice simulations.
- Global equilibrium and sample sufficiency criteria improve estimation accuracy.

## Abstract

The tempered Lefschetz thimble method is a parallel-tempering algorithm towards solving the numerical sign problem. It uses the flow time of the gradient flow as a tempering parameter and is expected to tame both the sign and multimodal problems simultaneously. In this paper, we further develop the algorithm so that the expectation values can be estimated precisely with a criterion ensuring global equilibrium and the sufficiency of the sample size. To demonstrate that this algorithm works well, we apply it to the quantum Monte Carlo simulation of the Hubbard model away from half-filling on a two-dimensional lattice of small size, and show that the numerical results agree nicely with exact values.