2022
DOI: 10.1088/1751-8121/ac508a
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Direction-sweep Markov chains

Abstract: We discuss a non-reversible, lifted Markov-chain Monte Carlo (MCMC) algorithm for particle systems in which the direction of proposed displacements is changed deterministically. This algorithm sweeps through directions analogously to the popular MCMC sweep methods for particle or spin indices. Direction-sweep MCMC can be applied to a wide range of reversible or non-reversible Markov chains, such as the Metropolis algorithm or the event-chain Monte Carlo algorithm. For a single two-dimensional tethered hard-… Show more

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Cited by 4 publications
(1 citation statement)
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“…Consider atoms and let be the physical all-atom configuration that collects all three-dimensional atom positions with . For generalized Newtonian event-chain Monte Carlo, the lifting framework 59 , 60 (see also Refs 36 and 61 , Appendix A) extends the physical all-atom configuration to , with auxiliary lifting variables that represent an all-atom velocity and an activity label i , respectively. The physical sample space is extended to the lifted sample space , where is the set of atom indices, and with a positive-definite symmetric mass matrix and conserved total kinetic energy .…”
Section: Methodsmentioning
confidence: 99%
“…Consider atoms and let be the physical all-atom configuration that collects all three-dimensional atom positions with . For generalized Newtonian event-chain Monte Carlo, the lifting framework 59 , 60 (see also Refs 36 and 61 , Appendix A) extends the physical all-atom configuration to , with auxiliary lifting variables that represent an all-atom velocity and an activity label i , respectively. The physical sample space is extended to the lifted sample space , where is the set of atom indices, and with a positive-definite symmetric mass matrix and conserved total kinetic energy .…”
Section: Methodsmentioning
confidence: 99%