153 citations · 567 across the 30 of their papers we have counts for
11 papers · 1 filter
Tensor-network Monte Carlo approach based on time-evolving block decimation
Shimpei Goto, Hidemaro Suwa, Synge Todo
We propose a tensor-network Monte Carlo (TNMC) approach for unitary evolution following the compression sequence of the time-evolving block decimation (TEBD) algorithm. In the TNMC…
Reducing rejection exponentially improves Markov chain Monte Carlo sampling
Hidemaro Suwa
The choice of transition kernel critically influences the performance of the Markov chain Monte Carlo method. Despite the importance of kernel choice, guiding principles for optima…
Lifted directed-worm algorithm
Hidemaro Suwa
Nonreversible Markov chains can outperform reversible chains in the Markov chain Monte Carlo method. Lifting is a versatile approach to introducing net stochastic flow in state spa…
Geometric allocation approach to accelerating directed worm algorithm
Hidemaro Suwa
The worm algorithm is a versatile technique in the Markov chain Monte Carlo method for both classical and quantum systems. The algorithm substantially alleviates critical slowing d…
Upper and Lower Critical Decay Exponents of Ising Ferromagnets with Long-range Interaction
Toshiki Horita, Hidemaro Suwa, Synge Todo
We investigate the universality class of the finite-temperature phase transition of the two-dimensional Ising model with the algebraically decaying ferromagnetic long-range interac…
Stochastic approximation of dynamical exponent at quantum critical point
Shinya Yasuda, Hidemaro Suwa, Synge Todo
We have developed a unified finite-size scaling method for quantum phase transitions that requires no prior knowledge of the dynamical exponent . During a quantum Monte Carlo si…