activity
20182026
most citedRoadmap on Advancements of the FHI-aims Software Package

8 citations · 9 across the 4 of their papers we have counts for

collaborators

5 papers

quant-ph2026

Encoding Numerical Data for Generative Quantum Machine Learning

Michael Krebsbach, Florentin Reiter, Thomas Wellens +2

Generative quantum machine learning models are trained to deduce the probability distribution underlying a given dataset, and to produce new, synthetic samples from it. The majorit…

cond-mat.mtrl-sci2025★ 8 cited

Roadmap on Advancements of the FHI-aims Software Package

Joseph W. Abbott, Carlos Mera Acosta, Alaa Akkoush +203

Electronic-structure theory is the foundation of the description of materials including multiscale modeling of their properties and functions. Obviously, without sufficient accurac…

quant-ph2024

Denoising Gradient Descent in Variational Quantum Algorithms

Lars Simon, Holger Eble, Hagen-Henrik Kowalski +1

In this article we introduce an algorithm for mitigating the adverse effects of noise on gradient descent in variational quantum algorithms. This is accomplished by computing a {\e…

quant-ph2023★ 1 cited

Interpolating Parametrized Quantum Circuits using Blackbox Queries

Lars Simon, Holger Eble, Hagen-Henrik Kowalski +1

This article focuses on developing classical surrogates for parametrized quantum circuits using interpolation via (trigonometric) polynomials. We develop two algorithms for the con…

cs.MS2018

Optimizations of the Eigensolvers in the ELPA Library

P. Kus, A. Marek, S. S. Koecher +6

The solution of (generalized) eigenvalue problems for symmetric or Hermitian matrices is a common subtask of many numerical calculations in electronic structure theory or materials…