#densityfunctionaltheory — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #densityfunctionaltheory, aggregated by home.social.
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Our work is also described in a scientific highlight from the NCCR Marvel collaboration: https://nccr-marvel.ch/highlights/AD-DFPT-Herbst
#dftk #algorithmicdifferentiation #densityfunctionaltheory #dft
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New publication https://doi.org/10.1038/s41524-025-01880-3
Our work on AD-DFPT, a unification of #automaticdifferentiation with linear response for #densityfunctionaltheory is published in npj Computational Materials. We show examples for #property predition, #uncertainty propagation, the design of #materials and #machinelearning of new #dft models. #condensedmatter #dftk -
New preprint https://arxiv.org/abs/2511.06957
A #perspective discussing Moreau-Yosida (MY) techniques in #densityfunctionaltheory.
MY regularisation has enabled to import tools from #convexanalysis into #dft
providing a new mathematical understanding of the most important atomistic simulation approach
and new robust algorithms for Kohn-Sham #dft.Thanks to my co-authors from the #hylleraas centre and #oslomet for insightful discussions.
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New preprint: https://arxiv.org/abs/2509.07785
We present an implementation of AD-DFPT, a unification of #automaticdifferentiation with classical #dfpt response techniques for #densityfunctionaltheory (#dft). We demonstrate its use for #property predition, #uncertainty propagation, design of new #materials as well as the #machinelearning of new #dft models.
#condensedmatter #planewave #response #physics #simulation #computation
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New publication https://doi.org/10.1103/PhysRevB.111.205143
New algorithm for the #inverseproblem of Kohn-Sham #densityfunctionaltheory (#dft), i.e. to find the #potential from the #density.
Outcome of a fun collaboration of @herbst with the group of Andre Laestadius at #oslomet to derive first mathematical error bounds for this problem
#condensedmatter #planewave #numericalanalysis #convexanalysis #dftk
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New preprint from our team: https://arxiv.org/abs/2409.04372
A new algorithm for computing #material properties in #densityfunctionaltheory (#dft) based on inexact #krylov methods: we safe 40% computational cost by an adaptive selection of convergence tolerances inspired from #mathematical analysis.