^{By Dr. Inés Urdaneta / Physicist at Resonance Science Foundation}

As many theoretical and computational chemists and physicists know, quantum chemical calculations involving more than an electron and nuclei are very difficult to solve. They belong to a field called many body problems and require an extensive amount of computational infrastructure and hours of calculations depending on the size (the number of particles) of the system.

Here is where artificial intelligence – a combination of artificial neural networks and machine learning – comes into play. Neural networks have been around for more than 50 years, and they are more actualized than ever before. This is because they can learn through something called backward propagation, reaching a high level of predictability and increasing accuracy by training the network.

Quantum theoretical models, together with their computational packages, have been outstandingly successful in describing the quantum regime. While...