3 papers
cond-mat.stat-mech2025
Tensor Network Markov Chain Monte Carlo: Efficient Sampling of Three-Dimensional Spin Glasses and Beyond
Tao Chen, Jing Liu, Youjin Deng +1
Sampling the three-dimensional (3D) spin glass -- i.e., generating equilibrium configurations of a 3D lattice with quenched random couplings -- is widely regarded as one of the cen…
cond-mat.stat-mech2025
BatchTNMC: Efficient sampling of two-dimensional spin glasses using tensor network Monte Carlo
Tao Chen, Jingtong Zhang, Jing Liu +2
Efficient sampling of two-dimensional statistical physics systems remains a central challenge in computational statistical physics. Traditional Markov chain Monte Carlo (MCMC) meth…
cond-mat.stat-mech2024
Universal Scaling of Gap Dynamics in Percolation
Sheng Fang, Qing Lin, Jun Meng +4
Percolation is a cornerstone concept in physics, providing crucial insights into critical phenomena and phase transitions. In this study, we adopt a kinetic perspective to reveal t…