Simulating Thermal and Quantum Fluctuations in Materials and Molecules

          @misc{ scivideos_PIRSA:19070004,
            doi = {10.48660/19070004},
            url = {https://pirsa.org/19070004},
            author = {Ceriotti, Michele},
            keywords = {Quantum Matter},
            language = {en},
            title = {Simulating Thermal and Quantum Fluctuations in Materials and Molecules },
            publisher = {Perimeter Institute for Theoretical Physics},
            year = {2019},
            month = {jul},
            note = {PIRSA:19070004 see, \url{https://scivideos.org/index.php/pirsa/19070004}}
          }
          

Abstract

Both electrons and nuclei follow the laws of quantum mechanics, and even though classical approximations and/or empirical models can be quite successful in many cases, a full quantum description is needed to achieve predictive simulations of matter. Traditionally, simulations that treat both electrons and nuclei as quantum particles have been prohibitively demanding. I will present several recent algorithmic advances that have increased dramatically the range of systems that are amenable to quantum modeling: on one hand, by using accelerated path integral schemes to treat the nuclear degrees of freedom, and on the other by using machine-learning potentials to reproduce inexpensively high-end electronic-structure calculations. I will give examples of both approaches, and discuss how the two can be used in synergy to make fully quantum modeling affordable.