activity
19932023
most citedProbability-Changing Cluster Algorithm for Two-Dimensional XY and Clock Models

89 citations · 1.2k across the 61 of their papers we have counts for

collaborators

61 papers

cond-mat.stat-mech2023★ 5 cited

Comprehensive studies on the universality of BKT transitions -- Machine-learning study, Monte Carlo simulation, and Level-spectroscopy method

Hiromi Otsuka, Kenta Shiina, Yutaka Okabe

Comprehensive studies are made on the six-state clock universality of two models using several approaches. We apply the machine-learning technique of phase classification to the an…

cond-mat.stat-mech2021

Super-resolution of spin configurations based on flow-based generative models

Kenta Shiina, Lee Hwee Kuan, Hiroyuki Mori +2

We present a super-resolution method for spin systems using a flow-based generative model that is a deep generative model with reversible neural network architecture. Starting from…

cond-mat.dis-nn2021★ 13 cited

Large peaks in the entropy of the diluted nearest-neighbor spin-ice model on the pyrochlore lattice in a [111] magnetic field

Petr Andriushchenko, Konstantin Soldatov, Alexey Peretyatko +4

We study the residual entropy of the nearest-neighbor spin-ice model in a magnetic field along the [111] direction using the Wang-Landau Monte Carlo method, with a special attentio…

cond-mat.stat-mech2021

Weakly-supervised learning on Schrodinger equation

Kenta Shiina, Hwee Kuan Lee, Yutaka Okabe +1

We propose a machine learning method to solve Schrodinger equations for a Hamiltonian that consists of an unperturbed Hamiltonian and a perturbation. We focus on the cases where th…

cond-mat.stat-mech2021★ 19 cited

Inverse Renormalization Group based on Image Super-Resolution using Deep Convolutional Networks

Kenta Shiina, Hiroyuki Mori, Yusuke Tomita +2

The inverse renormalization group is studied based on the image super-resolution using the deep convolutional neural networks. We consider the improved correlation configuration in…

cond-mat.stat-mech2020★ 16 cited

Machine-Learning Study using Improved Correlation Configuration and Application to Quantum Monte Carlo Simulation

Yusuke Tomita, Kenta Shiina, Yutaka Okabe +1

We use the Fortuin-Kasteleyn representation based improved estimator of the correlation configuration as an alternative to the ordinary correlation configuration in the machine-lea…