Computazione quantistica e machine learning per simulazioni chimiche

One of the most interesting use of quantum computing is its application to chemistry problems. Traditional computational chemistry has struggled to answer questions about phenomena like: high temperature superconductivity, solid-state physics, transition metal catalysis, or certain biochemical reactions. A quantum computer might one day be able not only to model this systems correctly, but also design new important substances for industry and healthcare. At the present time, building a large-scale quantum computer is a serious challenge, thought to take place in the forthcoming decades. However, it might possible to tackle some of these ques- tions with fewer quantum resources, already obtaining results better than classical machines with noisy quantum devices. In this work, I describe the nascient field of quantum computational chemistry, a mix of computational chemistry and quantum computing. I will focus particularly on near-term quantum computation, illustrating how to solve chemical problems on a quantum computer. Furthermore, I show how the problem can be simplified in order to save important computational resources. Finally, I conclude with an outlook on future studies.