Numerical study of boson mixtures with multi-component continuous matrix product states

TL;DR

This paper introduces an improved optimization scheme for multi-component continuous matrix product states, enabling more accurate simulations of bosonic quantum mixtures in continuous space.

Contribution

The authors develop a new optimization method for multi-component cMPS, allowing simulations with larger bond dimensions and better accuracy for quantum mixture systems.

Findings

Successfully benchmarked on the two-component Lieb-Liniger model

Achieved good agreement with analytical predictions

Enabled simulations of larger bond dimensions than previous methods

Abstract

The continuous matrix product state (cMPS) ansatz is a promising numerical tool for studying quantum many-body systems in continuous space. Although it provides a clean framework that allows one to directly simulate continuous systems, the optimization of cMPS is known to be a very challenging task, especially in the case of multi-component systems. In this work, we have developed an improved optimization scheme for multi-component cMPS that enables simulations of bosonic quantum mixtures with substantially larger bond dimensions than previous works. We benchmark our method on the two-component Lieb-Liniger model, obtaining numerical results that agree well with analytical predictions. Our work paves the way for further numerical studies of quantum mixture systems using the cMPS ansatz.