NPF has a new master in astrophysics: Catalina Zamora

Since April 2021, the Millennium Nucleus of Planetary Formation has a new master in astrophysics. The now former master student at the Institute of Physics and Astronomy of the UV, Catalina Zamora, defended her thesis after an intense research on the influence of stellar activity on the evolution of dust grains in the debris disks around red dwarf stars. This thesis work was guided by NPF director Amelia Bayo.

Due to the expansion of COVID-19 in the country, this defense was conducted virtually through the ZOOM platform. However, it was a public examination as is tradition in graduate defenses, with about 50 people witnessing the presentation.

To conduct the research, Zamora used data obtained with the HARPS spectrograph (located at the La Silla Observatory in Chile) from a sample of red dwarfs with and without debris disks. The goal: to identify by machine learning techniques, from good indirect tracers, the presence of debris disks, since it has only been possible to obtain a direct image of less than a dozen of these disks.

“We were able to successfully classify stars with debris disks, based on their activity,” explains Catalina Zamora, who will continue this research by expanding the sample to obtain more robust results. “We also want to repeat this procedure, but using photometric data to compare them with the results obtained with spectroscopy,” she indicates.

Amelia Bayo, who is also an academic at the Institute of Physics and Astronomy of the University of Valparaiso, emphasizes that, although direct images of very few debris disks around red dwarfs have been obtained, statistically the vast majority of these stars have rocky planets orbiting them. So, if such planets form in these disks, they can be found using an efficient method, which was the goal of this research.

The interesting thing about the project is its originality, taking advantage of the large amount of archival data available on M stars. “This large amount of data is what allows us to use machine learning techniques and, in particular, to relate the activity to the presence or not of debris disks,” says Bayo.

“The success in the classification suggests that the hypothesis that the current activity indicators of M stars can be used to infer the presence of disks, which can be confirmed later with instruments such as SPHERE at the VLT, is verified,” concludes Catalina Zamora.

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