BECAS
MENDEZ Marta Patricia Alejandra
artículos
Título:
Bayesian atomic structure calculations for collisional problems
Autor/es:
MENDEZ, ALEJANDRA MARTA PATRICIA; DI FILIPPO, JUAN IGNACIO; LÓPEZ, SEBASTIÁN DAVID; MITNIK, DARIO MARCELO
Revista:
Journal of Physics: Conference Series
Editorial:
IOP Publishing
Referencias:
Año: 2020 vol. 1412
ISSN:
1742-6588
Resumen:
The calculations of collisional processes require an accurate description of the target. In general, the atomic structure is obtained through tedious iterations in which a variety of configurations and parameters are chosen to minimize the differences between the numerical and experimental values of the energies and the oscillator strengths. Using a Bayesian machine learning analysis through a Tree?structured Parzen Estimator, we can reproduce the experimental atomic structure with high accuracy. Results for neutral beryllium are presented.
