9 citations · 20 across the 5 of their papers we have counts for
5 papers
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…
phase2: Full-State Vector Simulation of Quantum Time Evolution at Scale
Marek Miller, Jakob Günther, Freek Witteveen +5
Classical simulation of quantum computers is essential for designing and benchmarking quantum algorithms. Here we present phase2, a full-state-vector simulator optimised for sequen…
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…
Repeated Interaction Scheme for the Quantum Simulation of Non-Markovian Electron Transfer Dynamics
Lea K. Northcote, Matthew S. Teynor, Gemma C. Solomon
Quantum algorithms have the potential to revolutionize our understanding of open quantum systems in chemistry. In this work, we demonstrate that a repeated interaction model, which…