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ETSF online seminar by Carla Verdi: Friday Decem ... (No replies)

berger

3 years ago

berger 3 years ago

Dear colleagues,

 

The next ETSF seminar will be given by Carla Verdi from the University of Sydney on Friday December 16 at 14:00 CET. 

The title of the talk is “Machine learning the random-phase approximation”. 

Below you will find an abstract of the seminar.

 

All ETSF members will receive an email with a zoom link a couple of days before the seminar.

If you are not an ETSF member and you would like to follow the seminar, please send an email to [email protected].

 

Best wishes,
Arjan Berger

 

 

Abstract:

The random-phase approximation (RPA) is a successful, but computationally costly, many-body approach to compute the electronic correlation. In this talk I will show how to accelerate RPA calculations via machine learning in two ways. First, we train machine-learned potentials based on the RPA using the principles of ∆-machine learning. As an example, we apply this method to a prototypical anharmonic solid, strontium titanate, and we show that the RPA delivers a quantitative understanding of the quantum paraelectric behavior. Second, we develop a machine learning approach that maps the RPA to a pure density functional that can be considered a non-local extension to the usual gradient approximations. To train our functional we use both RPA energies and exchange-correlation potentials obtained via the optimized effective potential method. We apply our scheme to create an RPA substitute functional for diamond and water. Overall, we demonstrate how machine learning techniques can be used to extend the applicability of mehods beyond density functional theory to larger system sizes and time scales.