Quasi-adiabatic quantum Monte Carlo algorithm for quantum evolution in imaginary time

TL;DR

This paper introduces a quasi-adiabatic quantum Monte Carlo algorithm for simulating non-equilibrium quantum dynamics in imaginary time, enabling efficient analysis of static and dynamic properties across a range of parameters.

Contribution

The paper presents a novel QAQMC method that extends standard QMC to non-equilibrium dynamics, capturing quasi-adiabatic evolution and critical behavior in quantum systems.

Findings

Accurately estimates the quantum-critical point of the 2D transverse-field Ising model.

Demonstrates the method's ability to analyze critical scaling and dynamic properties.

Shows potential to extract Berry curvature and metric tensor from simulations.

Abstract

We propose a quantum Monte Carlo (QMC) algorithm for non-equilibrium dynamics in a system with a parameter varying as a function of time. The method is based on successive applications of an evolving Hamiltonian to an initial state and delivers results for a whole range of the tuning parameter in a single run, allowing for access to both static and dynamic properties of the system. This approach reduces to the standard Schr\"odinger dynamics in imaginary time for quasi-adiabatic evolutions, i.e., including the leading non-adiabatic correction to the adiabatic limit. We here demonstrate this quasi-adiabatic QMC (QAQMC) method for linear ramps of the transverse-field Ising model across its quantum-critical point in one and two dimensions. The critical behavior can be described by generalized dynamic scaling. For the two-dimensional square-lattice system we use the method to obtain a high-precision estimate of the quantum-critical point $(h/J)_c=3.04463(12)$, where $h$ is the transverse magnetic field and $J$ the nearest-neighbor Ising coupling. The QAQMC method can also be used to extract the Berry curvature and the metric tensor.