Neuhauser Group

UCLA Department of Chemistry and Biochemistry

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• StochasticGW

Selected recent publications

A GW approach that gives accurate charging energies for very large molecules and clusters (thousands of electrons and more, scaling linearly with system size due to the use of stochastic algorithms) [PDF]

A linear-scaling embedded-fragment stochastic approach to the densities and energies of large molecules (thousands of electrons or more). The method is non-approximate, and its new, embedded-fragment version uses very few stochastic orbitals (tens to few hundred orbitals regarless of system size) since the stochastic averaging only needs to model the small difference between the true (unbknown) density and the sum of fragment densities. [PDF]

Principal Investigator

Daniel Neuhauser

Current Graduate Students

5th Year Students

Minh Nguyen

Nadine Bradbury

Nick Sereda

2nd Year Students

Tucker Allen

Dimitri Bazile

Undergraduates and Exchange Students

Tim Duong

Justin Purnomo