93 citations · 363 across the 16 of their papers we have counts for
16 papers
RuNNer 2.0: A Software Suite for High-Dimensional Neural Network Potentials
Alexander L. M. Knoll, Moritz R. Schäfer, K. Nikolas Lausch +11
We present RuNNer 2.0, the "Ruhr University Neural Network energy representation", a highly optimized software suite for training and evaluating high-dimensional neural network pot…
QDK/Chemistry: A Modular Toolkit for Quantum Chemistry Applications
Nathan A. Baker, Brian Bilodeau, Chi Chen +23
We present QDK/Chemistry, a software toolkit for quantum chemistry workflows targeting quantum computers. The toolkit addresses a key challenge in the field: while quantum algorith…
How to use quantum computers for biomolecular free energies
Jakob Günther, Thomas Weymuth, Moritz Bensberg +18
Free energy calculations are at the heart of physics-based analyses of biochemical processes. They allow us to quantify molecular recognition mechanisms, which determine a wide ran…
Lifelong Machine Learning Potentials for Chemical Reaction Network Explorations
Marco Eckhoff, Markus Reiher
Recent developments in computational chemistry facilitate the automated quantum chemical exploration of chemical reaction networks for the in-silico prediction of synthesis pathway…
Machine Learning Enhanced Calculation of Quantum-Classical Binding Free Energies
Moritz Bensberg, Marco Eckhoff, F. Emil Thomasen +10
Binding free energies are a key element in understanding and predicting the strength of protein--drug interactions. While classical free energy simulations yield good results for m…
Hierarchical quantum embedding by machine learning for large molecular assemblies
Moritz Bensberg, Marco Eckhoff, Raphael T. Husistein +9
We present a quantum-in-quantum embedding strategy coupled to machine learning potentials to improve on the accuracy of quantum-classical hybrid models for the description of large…