Events Calendar
Secondary distance estimates to evolved stars using Spectral energy distributions and Machine Learning.
Wednesday May 1, 2024
| 2:00 pm
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Presenter: | Rajorshi Bhattacharya |
|---|---|---|
| Series: | Center for Astrophysics Research and Technologies Seminar Series | |
| Abstract: | The Bulge Asymmetries and Dynamical Evolution (BAaDE) radio-wavelength survey aims to present a comprehensive study of the inner regions of the Galaxy to improve our understanding of Galactic structure and dynamics, with a focus on the bulge stellar population distribution and age. The BAaDE survey consists of 28,062 infrared color-selected red giant stars, the majority of which are of Mira-type and lie on the Asymptotic Giant Branch (AGB). To date, approximately 15,000 of these stars have measured line-of-sight velocities determined from SiO maser lines. To optimize how these velocities are incorporated into dynamical models, and to allow any existing spatial separation between populations to be distinguished, 3D positions are desirable. Distances will also enable us to estimate luminosities and mass loss rates. Due to the sizeable AGB sample in our survey, we explored methods which can consistently be applied to any AGB star within the full sample. We present our results from using distance-calibrated infrared (IR) Spectral Energy Distribution (SED) templates to estimate distance for our sources. Also discussed will be preliminary results related to the estimation of luminosities for these sources using the obtained distances. We will then extend the discussion into how by applying Supervised Machine Learning on large astronomical datasets, we can successfully regress/classify different parameters, for example, distances or stellar periods. To test the accuracy of our machine learning models we also show results from their application on the BAaDE survey. | |
| Host: | Diana Dragomir | |
| Location: | PAIS-3205, PAIS | |
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