Berezinskii-Kosterlitz-Thouless phase transitions in a kagome spin ice by a quantifying Monte Carlo process: Distribution of Hamming distances
Wen-Yu Su, Feng Hu, Chen Cheng, Nvsen Ma
Abstract
We reinvestigate the phase transitions of the Ising model on the kagome lattice with antiferromagnetic nearest-neighbor and ferromagnetic next-nearest-neighbor interactions, which has a six-state-clock spin ice ground state and two consecutive Berezinskii-Kosterlitz-Thouless (BKT) phase transitions. Employing the classical Monte Carlo (MC) simulations, the phases are characterized by the magnetic order parameter and the critical temperatures are obtained by the finite-size scaling of related physical quantities. Moreover, we attempt to gain general information on the phase transitions from the MC process instead of MC results and successfully extract the correct transition points. Specifically, we focus on the selected data set of uncorrelated MC configurations and quantify the MC process using the distribution of two-configuration Hamming distances in this small data collection. This distribution is more than a quantity that features different behaviors in different phases but also nicely supports the same BKT scaling form as the order parameter, from which we successfully determine the two BKT transition points with surprisingly high accuracy. More strikingly, the distribution of Hamming distances can even determine the transition type without the help of the order parameter. We also discuss the connection between the phase transitions and the intrinsic dimension extracted from the Hamming distances, which is widely used in the growing field of machine learning and is reported to be able to detect critical points. Besides providing a new understanding of the spin ice transitions in the kagome lattice, we hope our proposal can be used to tackle the complicated phase transitions in the newly found compound HoAgGe.