ECMC 2021 Maggs

From Werner KRAUTH

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	Event chain algorithms give us the freedom to split potentials into non-equivalent forms displaying very different large scale behaviour in their time evolution. All splittings guarantee convergence to the equilibrium Boltzmann distribution. We study the dynamics of different splittings and show that good choices can lead to an accelerated sampling of the equilibrium state.		Event chain algorithms give us the freedom to split potentials into non-equivalent forms displaying very different large scale behaviour in their time evolution. All splittings guarantee convergence to the equilibrium Boltzmann distribution. We study the dynamics of different splittings and show that good choices can lead to an accelerated sampling of the equilibrium state.
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		+	'''Slides'''
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		+	'''Recording'''
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		+	'''Further material'''
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		+	[[Workshop_ECMC_11_May_2021|back to 2021 ECMC workshop]]

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Revision as of 11:56, 10 May 2021

Exploring factorizations in the event chain algorithm

Anthony Maggs, Ze Lei, Werner Krauth

Event chain algorithms give us the freedom to split potentials into non-equivalent forms displaying very different large scale behaviour in their time evolution. All splittings guarantee convergence to the equilibrium Boltzmann distribution. We study the dynamics of different splittings and show that good choices can lead to an accelerated sampling of the equilibrium state.

Slides

Recording

Further material

back to 2021 ECMC workshop