activity
19952026
most citedExchange Monte Carlo Method and Application to Spin Glass Simulations

2.5k citations · 3.4k across the 65 of their papers we have counts for

collaborators

66 papers

cond-mat.stat-mech2026

Fast free-energy estimation for complex systems with nonreversible simulated tempering

Yoshihiko Nishikawa, Koji Hukushima

We discuss free-energy estimation for complex systems using simulated tempering with Wang--Landau-type feedback. We show that introducing nonreversible dynamics in temperature spac…

quant-ph2023

Proof of avoidability of the quantum first-order transition in transverse magnetization in quantum annealing of finite-dimensional spin glasses

Mizuki Sanatani, Naoto Shiraishi, Koji Hukushima

It is rigorously shown that an appropriate quantum annealing for any finite-dimensional spin system has no quantum first-order transition in transverse magnetization. This result c…

cond-mat.dis-nn2023

Effect of global shrinkage parameter of horseshoe prior in compressed sensing

Yasushi Nagano, Koji Hukushima

In sparse signal processing, this study investigates the effect of the global shrinkage parameter of a horseshoe prior, one of the global-local shrinkage prior, on the linear r…

cond-mat.stat-mech2023★ 1 cited

Higher-order tensor renormalization group study of the - Ising model on a square lattice

Kota Yoshiyama, Koji Hukushima

Phase transitions of the - Ising model on a square lattice are studied using the higher-order tensor renormalization group(HOTRG) method. This system involves a competiti…

cond-mat.dis-nn2022★ 3 cited

Phase transition in compressed sensing with horseshoe prior

Yasushi Nagano, Koji Hukushima

In Bayesian statistics, horseshoe prior has attracted increasing attention as an approach to the sparse estimation. The estimation accuracy of compressed sensing with the horseshoe…

cond-mat.dis-nn2022★ 8 cited

Statistical-mechanical study of deep Boltzmann machine given weight parameters after training by singular value decomposition

Yuma Ichikawa, Koji Hukushima

Deep learning methods relying on multi-layered networks have been actively studied in a wide range of fields in recent years, and deep Boltzmann machines(DBMs) is one of them. In t…