2020/11/09 by Sergio Blanes, M. P. Calvo, Blanes, S. +5
Mathematics · Physics and Astronomy · #FOS: Mathematics #Model Reduction and Neural Networks #NMR spectroscopy and applications #Numerical Analysis (math.NA) #Numerical methods for differential equations
paper · pdf · doi:10.48550/arxiv.2011.04401
openalex publication_date 2020/11/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30
We construct integrators to be used in Hamiltonian (or Hybrid) Monte Carlo sampling. The new integrators are easily implementable and, for a given computational budget, may deliver five times as many accepted proposals as standard leapfrog/Verlet without impairing in any way the quality of the samples. They are based on a suitable modification of the processing technique first introduced by J.C. Butcher. The idea of modified processing may also be useful for other purposes, like the construction of high-order splitting integrators with positive coefficients.