Work

Variational preparation of normal matrix product states on quantum computers

Year: 2025

Type: article

Abstract: Preparing matrix product states (MPSs) on quantum computers is an essential routine in the simulation of many-body physics. However, widely used schemes based on staircase circuits are often too deep to execute on current hardware. Here, we demonstrate that MPSs with short-range correlations can be prepared with shallow circuits by leveraging heuristics from approximate quantum compiling (AQC). We achieve this with ADAPT-AQC, an adaptive-ansatz preparation algorithm, and introduce a generalized initialization procedure for the existing AQC-Tensor algorithm. We first compare these methods for the task of preparing a molecular electronic structure ground state. We then use them to prepare an antiferromagnetic (AFM) ground state of the 50-site Heisenberg XXZ spin chain near the AFM-XY phase boundary. Through the execution of circuits with up to 59 depth and 1251 gates, we perform a global quench and observe the relaxation of magnetic ordering in a parameter regime previously inaccessible due to deep ground-state preparation circuits. Our results demonstrate how the integration of quantum and classical resources can push the boundary of what can be studied on quantum computers.

Source: Physical Review Research

DOI: 10.1103/m5kb-4f43