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BEGIN:VEVENT
DTSTAMP:20260427T064342Z
DTSTART;VALUE=DATE-TIME:20241111T130000
DTEND;VALUE=DATE-TIME:20241111T140000
SUMMARY:WCPM: Michael Herbst\, EPFL\, Institute of Mathematics and Instit
 ute of Materials
TZID:Europe/London
UID:20241111-8a1785d891c69ed40191ccc1fc2e0ef0@warwick.ac.uk
CREATED:20241125T142156Z
DESCRIPTION:Time: 13.00-14.00 Seminar location: A2.05B There will be an i
 nformal sandwich lunch outside D2.02 at 12.30. To join this meeting onli
 ne click here. Title: Robust error-controlled materials simulations Abst
 ract: Systematic first-principle simulations are nowadays a key componen
 t when developing novel materials. Usually the resulting simulation data
  is not directly used to drive the search\, but instead employed to trai
 n a considerable cheaper statistical surrogate. In this setting of poten
 tially millions of simulations as well as these multiple layers of appro
 ximations (physical\, numerical\, statistical) obtaining robust computat
 ional workflows and tracking simulation errors remains challenging. In t
 his talk I will report on progress along two axes of research to tackle 
 these challenges. The first concerns the development of robust numerical
  algorithms for density-functional theory (DFT) --- the most widely empl
 oyed family of first-principle models in the field. The focus of the dev
 elopment here is to obtain black-box methods that are able to automatica
 lly adapt to the physics of the simulated system. Secondly\, I will disc
 uss first results on employing multi-task statistical surrogate models\,
  a surrogatisation technique\, which enables the use of data of heteroge
 neous quality when training a single surrogate. By combining materials s
 imulation approaches of different cost/accuracy balances this not only u
 nlocks computational savings to generate training data\, but also allows
  to opportunistically exploit heterogeneous databases of already existin
 g simulation data. In both efforts software has played a key role to pro
 vide an accessible platform fostering such interdisciplinary development
 s. In our work we develop and extend the density-functional toolkit (DFT
 K)\, a Julia-based DFT code\, suitable to mathematical research (only 75
 00 lines of code)\, but at the same time integrated into standard tools 
 for materials discovery.
LOCATION:A2.05B
CATEGORIES:WCPM
LAST-MODIFIED:20241125T142156Z
ORGANIZER;CN=Sarah Jarratt:
END:VEVENT
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