报告题目：Computational Methods in Atomic Physics
报告人：Prof. Darío M. Mitnik
Dr. Darío Mitnik is a researcher at IAFE, the Instituto de Astronomía and Física del Espacio (CONICET–Universidad de Buenos Aires), Argentina. He studied Mathematics and Physics at the Hebrew University of Jerusalem (Israel) and obtained his M.Sc and Ph.D. specializing in Plasma Spectroscopy of heavy highly–ionized ions. In his postdoctoral research at Auburn University and Rollins College (United States), he undertook the search for fully-quantum mechanical solutions to few–body collisional problems, working in the development of time–dependent close–coupling methods. He also was devoted to the generation of high–performance computational methods for large–scale electron–impact excitation calculations. Back in Argentina, he established a research group, developing spectral methods for the solution of few–body atomic and molecular collisional problems. He also was involved in the investigation of many atomic physics problems, like laser interaction with metallic surfaces, the determination of Compton profiles, and astrophysical spectroscopy, among others. Over the last few years, he has been applying machine–learning methods for the calculation of different atomic physics collisional processes. He published more than 100 recognized scientific papers and has about 170 presentations at international conferences.
The reliable electron–impact rate coefficients are crucial for understanding the properties of fusion and astrophysical plasmas, including charge state distribution, thermal structure, and elemental abundances. However, it is still challenging to calculate the data of multi–electron ions with sufficient precision. Processes like electron–impact ionization and dielectronic recombination, involve an infinite number of states. For highly charged ions, relativistic many–body effects should be considered with high orders in the theoretical calculations. In general, plasma diagnostic researchers reckon on databases that collect results produced in different ways, some of which are the outcome of sophisticated calculations. Others are just calculated by semiempirical approximation formulae. In this talk, I will try to unfold what is behind these databases. I will describe some of the existent methods, covering a wide range of approaches, among them: perturbation–theories, fully–quantal mechanics methods, spectral methods, and a novel technique based on machine– learning.