PIRSA:19070004 Conference Condensed Matter

DOI10.48660/19070004

Conference/School: Machine Learning for Quantum Design

Ceriotti, M. (2019). Simulating Thermal and Quantum Fluctuations in Materials and Molecules . Perimeter Institute. https://pirsa.org/19070004

Ceriotti, Michele. Simulating Thermal and Quantum Fluctuations in Materials and Molecules . Perimeter Institute, Jul. 08, 2019, https://pirsa.org/19070004 

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

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.

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