Cleveland Clinic Explores Hybrid Quantum-Classical Model for Predicting Proton Affinities

Researchers at the Cleveland Clinic have developed a hybrid quantum-classical machine learning model to predict proton affinities (PAs) of molecules with improved efficiency and competitive accuracy. The model, described in the Journal of Chemical Theory and Computation, integrates classical molecular descriptors with quantum circuits serving as feature encoders, offering a practical approach compatible with current […]

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