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

Just delivered a talk on algorithmic differentiation in our #dftk density-functional theory code at the #cecam workshop on #dft and #ai

Slides: https://michael-herbst.com/talks/2025.03.04_DFT_AI_Learning_each_other.pdf
#julialang demo: https://michael-herbst.com/talks/2025.03.04_DFT_AI_Learning_each_other_design.html

We just released #DFTK version 0.7.10: http://dftk.org/releases with an important bug fix for meta-GGA band structure computations and some details how to use DFTK on GPUs. Either #cuda (#nvidia GPUs) or #rocm (#AMD GPUs) are supported.

@schmitz (left) explaining his recent work on making #dftk algorithmically #differentiable at the #cecam workshop on #dft and #ai (https://www.cecam.org/workshop-details/1281). With his work derivatives of key density-functional theory quantities like forces or band structures wrt. model parameters can now be easily computed.

Hello #fediverse #introduction

I'm Michael, professor in the institutes of #mathematics and #materials science and head of the @MatMat group at #EPFL.

I work on the #atomistic simulations of materials, mainly density-functional theory (DFT) methods, understanding #simulation errors and #uncertainties in predicted materials properties.

I use techniques from
#physics #computerscience #machinelearning and
develop related #julialang packages such as the density-functional toolkit (#dftk).