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BEGIN:VEVENT
UID:news220@dmi.unibas.ch
DTSTAMP;TZID=Europe/Zurich:20180716T175646
DTSTART;TZID=Europe/Zurich:20180504T110000
SUMMARY:Seminar in Numerical Analysis: Jan Hamaekers (Fraunhofer SCAI)
DESCRIPTION:In this talk\, we introduce a new scheme for the efficient nume
 rical treatment of the electronic Schrödinger equation for molecules. It 
 is based on the combination of a many-body expansion\, which corresponds t
 o the so-called bond order dissection Anova approach\, with a hierarchy of
  basis sets of increasing order. Here\, the energy is represented as a fin
 ite sum of contributions associated to subsets of nuclei and basis sets in
  a telescoping sum like fashion. Under the assumption of data locality of 
 the electronic density (nearsightedness of electronic matter)\, the terms 
 of this expansion decay rapidly and higher terms may be neglected. We furt
 her extend the approach in a dimension-adaptive fashion to generate quasi-
 optimal approximations\, i.e. a specific truncation of the hierarchical se
 ries such that the total benefit is maximized for a fixed amount of costs.
  This way\, we are able to achieve substantial speed up factors compared t
 o conventional first principles methods depending on the molecular system 
 under consideration. In particular\, the method can deal efficiently with 
 molecular systems which include only a small active part that needs to be 
 described by accurate but expensive models. Finally\, we discuss to apply 
 such a multi-level many-body decomposition in the context of machine learn
 ing for many-body systems.
X-ALT-DESC:In this talk\, we introduce a new scheme for the efficient numer
 ical treatment of the electronic Schrödinger equation for molecules. It i
 s based on the combination of a many-body expansion\, which corresponds to
  the so-called bond order dissection Anova approach\, with a hierarchy of 
 basis sets of increasing order. Here\, the energy is represented as a fini
 te sum of contributions associated to subsets of nuclei and basis sets in 
 a telescoping sum like fashion. Under the assumption of data locality of t
 he electronic density (nearsightedness of electronic matter)\, the terms o
 f this expansion decay rapidly and higher terms may be neglected. We furth
 er extend the approach in a dimension-adaptive fashion to generate quasi-o
 ptimal approximations\, i.e. a specific truncation of the hierarchical ser
 ies such that the total benefit is maximized for a fixed amount of costs. 
 This way\, we are able to achieve substantial speed up factors compared to
  conventional first principles methods depending on the molecular system u
 nder consideration. In particular\, the method can deal efficiently with m
 olecular systems which include only a small active part that needs to be d
 escribed by accurate but expensive models. Finally\, we discuss to apply s
 uch a multi-level many-body decomposition in the context of machine learni
 ng for many-body systems. 
DTEND;TZID=Europe/Zurich:20180504T120000
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