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researcher

M. Tuckerman

21 papers hereh-index 7529.6k citations297 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author8
  • last author13

Across the 21 of 21 papers where every author was matched, so the position is known.

fields
  • physics.chem-ph7
  • cond-mat.mtrl-sci5
  • physics.comp-ph3
  • cond-mat.stat-mech2
  • cs.LG2
  • cond-mat.dis-nn1

identity via Semantic Scholar / OpenAlex

activity
20012026
most citedBy-passing the Kohn-Sham equations with machine learning

729 citations · 1.3k across the 19 of their papers we have counts for

collaborators
Showing physics.comp-phShow all

3 papers · 1 filter

physics.comp-ph2018★ 11 cited

Efficient prediction of 3D electron densities using machine learning

Mihail Bogojeski, Felix Brockherde, Leslie Vogt-Maranto +4

The Kohn-Sham scheme of density functional theory is one of the most widely used methods to solve electronic structure problems for a vast variety of atomistic systems across diffe…

physics.comp-ph2016★ 729 cited

By-passing the Kohn-Sham equations with machine learning

Felix Brockherde, Leslie Vogt, Li Li +3

Last year, at least 30,000 scientific papers used the Kohn-Sham scheme of density functional theory to solve electronic structure problems in a wide variety of scientific fields, r…

physics.comp-ph2013★ 76 cited

Stochastic resonance-free multiple time-step algorithm for molecular dynamics with very large time steps

Ben Leimkuhler, Daniel T. Margul, Mark E. Tuckerman

Molecular dynamics is one of the most commonly used approaches for studying the dynamics and statistical distributions of many physical, chemical, and biological systems using atom…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.