Released DFTK version 0.7.22: https://dftk.org/releases with initial support for exact exchange and #HybridDFT and notable #performance engineering for #GPU-based #response calculations. Special thanks to Augustin Bussy (CSCS) and Tobias Schäfer (TU Wien) as well as all other #dftk contributors.
#densityfunctionaltheory #condensedmatter #dfpt #physics #simulation #planewave
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
Yesterday our #cecam workshop on #uncertainty quantification (#uq)
for atomistic modelling and #machinelearning for #materials #modelling
and #chemistry started.
The opening contribution was by Niklas Schmitz from @MatMat
on #uq for #densityfuncitionaltheory:
https://github.com/niklasschmitz/tutorial-cecam-workshop-dftk-2025
building upon our recent preprint https://arxiv.org/abs/2509.07785.
Released #dftk version 0.7.19: https://dftk.org/releases with support for #hubbard corrections (#DFT+U) and various #gpu-related #performance improvements.
#densityfunctionaltheory #condensedmatter #dfpt #response #physics #simulation #planewave
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.
Within density-functional theory, Moreau-Yosida regularization enables both a reformulation of the theory and a mathematically well-defined definition of the Kohn-Sham approach. It is further employed in density-potential inversion schemes and, through the choice of topology for the density and potential space, can be directly linked to classical field theories. This perspective collects various appearances of the regularization technique within density-functional theory alongside possibilities for their future development.
This week the @MatMat group takes part in the #psik conference (https://www.psik2025.net/) at #epfl
with plentey of cutting-edge talks on #materials #modeling and simulations of #condensedmatter.
My contribution has been a short talk on #error quantification and propagation in #densityfunctionaltheory simulations leveraging the built-in #automaticdifferentiation framework of the #dftk code for automatic
gradient computation.
Slides: https://michael-herbst.com/talks/2025.08.25_Psik.pdf
As part of the #cecam workshop on perspectives of the atomistic simulation environment (#ase) I delivered a talk on our #materials #modeling ecosystem juliamolsim.org written in the #julialang
programming language and showed some examples: #automaticdifferentiation through the simulation pipeline, seamless #gpu usage, #error propagation and many more
Slides: https://michael-herbst.com/talks/2025.06.23_ASE_perspectives.pdf
#julialang demo: https://michael-herbst.com/talks/2025.06.23_ASE_perspectives_demo.tar.gz
#dftk #densityfunctionaltheory #condensedmatter #planewave #simulation
Released #dftk version 0.7.14: https://dftk.org/releases with another round of #performance improvements for #nvidia GPUs as well as a faster algorithm for response calculations based on our recent #preprint http://arxiv.org/abs/2505.02319.
#densityfunctionaltheory #condensedmatter #dfpt #response #physics #simulation #planewave
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
Michael Herbst
MatMat