Aarhus Universitets segl

SAC Seminar - Enrico Corsaro, INAF Osservatorio Astrofisico di Catania: Fast and automated peak bagging of solar-like oscillations using FAMED

Oplysninger om arrangementet

Tidspunkt

Fredag 19. november 2021,  kl. 14:15 - 15:15

Sted

Zoom

Abstract:

Stars of low and intermediate mass that exhibit oscillations may show tens of detectable oscillation modes each. Oscillation modes are a powerful tool to constrain the internal structure and rotational dynamics of the star, hence allowing one to obtain an accurate stellar age. The tens of thousands of solar-like oscillators that have been discovered thus far are representative of the large diversity of fundamental stellar properties and evolutionary stages available. Because of the wide range of oscillation features that can be recognized in such stars, it is particularly challenging to properly characterize the oscillation modes in detail, especially in light of large stellar samples. Overcoming this issue requires an automated approach, which has to be fast, reliable, and flexible at the same time. In addition, this approach should not only be capable of extracting the oscillation mode properties of frequency, linewidth, and amplitude from stars in di erent evolutionary stages, but also able to assign a correct mode identification for each of the modes extracted. In this seminar I will first discuss the preliminary and mandatory step of estimating the background signal in the stellar power spectrum by showing a semi-automated way to address it using the public code Background. I will thus focus on presenting the publicly available pipeline FAMED (Fast and AutoMated pEak bagging with Diamonds), which is capable of performing an automated and detailed asteroseismic analysis (peak bagging) in stars ranging from the main sequence up to the core-helium-burning phase of stellar evolution and beyond.

Below you find the connection details for the seminar:

Join Zoom Meeting

https://aarhusuniversity.zoom.us/j/65974972623?pwd=a3V6Tmx3V1NqTEdhWmRySVp1Y3RxQT09

Meeting ID: 659 7497 2623

Passcode: SAC2021Sem