Hybrid Quantum Generative Adversarial Networks for Molecular Simulation and Drug Discovery

ArXi:2212.07826v2 Announce Type: replace-cross In molecular research, the modelling and analysis of molecules through simulation is an important part that has a direct influence on medical development, material science and drug discovery. The processing power required to design protein chains with hundreds of peptides is huge. Classical computing techniques, including state-of-the-art machine learning models being deployed on classical computing machines, have proven to be inefficient in this task, though they have been successful in a limited way.