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physics.chem-ph2025
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…
physics.chem-ph2025
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…
physics.chem-ph2024
Multiscale Embedding for Quantum Computing
Leah P. Weisburn, Minsik Cho, Moritz Bensberg +3
We present a novel multi-scale embedding scheme that links conventional QM/MM embedding and bootstrap embedding (BE) to allow simulations of large chemical systems on limited quant…