Stochastic approximation of dynamical exponent at quantum critical point

TL;DR

This paper introduces a finite-size scaling method for quantum phase transitions that automatically estimates the dynamical exponent without prior knowledge, demonstrated on a 2D quantum XY model using quantum Monte Carlo simulations.

Contribution

The authors develop a novel, unified method to determine the dynamical exponent at quantum critical points during Monte Carlo simulations without prior assumptions.

Findings

Confirmed Lorentz invariance with z=1 at zero magnetic field

Identified dynamical exponent z=2 under finite magnetic field

Validated the method on the 2D quantum XY model

Abstract

We have developed a unified finite-size scaling method for quantum phase transitions that requires no prior knowledge of the dynamical exponent $z$. During a quantum Monte Carlo simulation, the temperature is automatically tuned by the Robbins-Monro stochastic approximation method, being proportional to the lowest gap of the finite-size system. The dynamical exponent is estimated in a straightforward way from the system-size dependence of the temperature. As a demonstration of our novel method, the two-dimensional $S=1/2$ quantum $XY$ model in uniform and staggered magnetic fields is investigated in the combination of the world-line quantum Monte Carlo worm algorithm. In the absence of the uniform magnetic field, we obtain the fully consistent result with the Lorentz invariance at the quantum critical point, $z=1$, i.e., the three-dimensional classical $XY$ universality class. Under a finite uniform magnetic field, on the other hand, the dynamical exponent becomes two, and the mean-field universality with effective dimension $(2+2)$ governs the quantum phase transition.