### Speaker

Daniel Lukic
(Graz University of Technology)

### Description

The main goal of the project is to find a machine learning approximation for the kinetic energy functional of orbital-free density functional theory,

\begin{equation}

T[n] = \int \tau[n] \,\mathrm{d}x,

\end{equation}

where the function $\tau[n]$ is represented using a feed forward neural network. Since it is known that the function $\tau$ is translationally invariant and non-local, i.e. a function of the values of $n$ at various positions $x$, the structure of a convolutional neural network seems like a reasonable choice.

### Primary authors

Prof.
Andreas Hauser
(Graz University of Technology - Institute of Experimental Physics)
Daniel Lukic
(Graz University of Technology)
Dr
Meyer Ralf