AI Helps Quantum Chemists Determine Molecular Wave Functions

Whether it's monitoring vehicles for lane drift, recognizing human faces or voices to unlock a phone, or recommending e-commerce products or streaming movies -- most people know that AI is watching and interacting with us more than ever before. What is not so well-known is how much AI has also established itself as a crucial tool in academics, particularly for scientific discovery. An interdisciplinary team of chemists, physicists, and computer scientists from the University of Warwick, the Technical University of Berlin, and the University of Luxembourg have developed a deep learning algorithm that leverages fundamental quantum mechanics equations to accurately predict the quantum mechanical wave functions of molecules. This provides a probability distribution for the value of each observable of the quantum system, from which additional ground-truth properties of the molecules can be derived. The research team say the study "opens promising avenues to perform inverse design of molecular structures for targeting electronic property optimization and a clear path towards increased synergy of machine learning and quantum chemistry," The team was assembled through a UCLA fellowship program on machine learning in quantum physics and has been working together for three years.