69 citations · 296 across the 15 of their papers we have counts for
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Distance between configurations in MCMC simulations and the geometrical optimization of the tempering algorithms
Masafumi Fukuma, Nobuyuki Matsumoto, Naoya Umeda
For a given Markov chain Monte Carlo (MCMC) algorithm, we define the distance between configurations that quantifies the difficulty of transitions. This distance enables us to inve…
Tempered Lefschetz thimble method and its application to the Hubbard model away from half filling
Masafumi Fukuma, Nobuyuki Matsumoto, Naoya Umeda
The tempered Lefschetz thimble method (TLTM) is a parallel-tempering algorithm towards solving the numerical sign problem. It tames both the sign and ergodicity problems simultaneo…
Implementation of the HMC algorithm on the tempered Lefschetz thimble method
Masafumi Fukuma, Nobuyuki Matsumoto, Naoya Umeda
The tempered Lefschetz thimble method (TLTM) is a parallel-tempering algorithm towards solving the numerical sign problem, where the system is tempered by the antiholomorphic gradi…
Distance between configurations in Markov chain Monte Carlo simulations
Masafumi Fukuma, Nobuyuki Matsumoto, Naoya Umeda
For a given Markov chain Monte Carlo algorithm we introduce a distance between two configurations that quantifies the difficulty of transition from one configuration to the other c…
Parallel tempering algorithm for integration over Lefschetz thimbles
Masafumi Fukuma, Naoya Umeda
The algorithm based on integration over Lefschetz thimbles is a promising method to resolve the sign problem for complex actions. However, this algorithm often meets a difficulty i…