Star Formation with Big Data and Machine Learning

Project Acronym: BigSF

Topics: Data Base, Digital, Galaxy, Stellar Formation

Disciplinary Fields: Astrophysics, Computer Science

Summary: The BigSF project proposes to use the very large masses of data available on our Galaxy to build, through numerical learning methods, a new empirical model of stellar formation. In our Galaxy, the great richness of existing data allows to describe in a very precise way the formation of stars, from very small scales to very large scales describing the structure of the Galaxy. This richness imposes a processing beyond what human research is capable of achieving and therefore requires the use of computers and learning algorithms to extract the knowledge from the combination of all available data. This combination has never been achieved before and promises to offer a new vision of stellar formation in our Galaxy, a vision in which our current understanding of this process could be modified.

Project Interlocutor: Annie Zavagno (LAM, UMR 7326)

Mediterranean Cooperation:
– France: Laboratoire d’Astrophysique de Marseille ; Laboratoire d’Informatique et Systèmes
– Italy: Istituto Nazionale di Astrofisica, Istituto di Astrofisica e Planetologia Spaziali (Rome) ; Osservatorio Astronomico di Capodimonte (Naples)

Project Duration: 01/01/2020 – 12/31/2021

Call of Proposal: Méditerranée 2018

Photography Credits: Photo by Guillermo Ferla on Unsplash

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