Corpus ID: 237532245

Accurate and robust splitting methods for the generalized Langevin equation with a positive Prony series memory kernel

@inproceedings{Duong2021AccurateAR,
  title={Accurate and robust splitting methods for the generalized Langevin equation with a positive Prony series memory kernel},
  author={Manh Hong Duong and Xiaocheng Shang},
  year={2021}
}
We study numerical methods for the generalized Langevin equation (GLE) with a positive Prony series memory kernel, in which case the GLE can be written in an extended variable Markovian formalism. We propose a new splitting method that is easy to implement and is able to substantially improve the accuracy and robustness of GLE simulations in a wide range of the parameters. An error analysis is performed in the case of a one-dimensional harmonic oscillator, revealing that all but one averages… Expand
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