Ponente
Fabio Iocco
(Università di Napoli "Federico II")
Descripción
I will illustrate the development of new methods, and their results, to determine the dark matter distribution in field galaxies.
Machine learning algorithms trained within the synthetic environment of numerical cosmological simulations -such as the IllustrisTNG- offer the potential to validate and test the reliability of the Dark Matter distribution in such controlled environment, before being applied to real Universe targets.
I will show recent developments in this field commenting on advantages and drawbacks of this innovative methodology.
Autores primarios
Fabio Iocco
(Università di Napoli "Federico II")
Martín de los Rios
(IFT-UAM)
