Published October 17, 2024 | Version v1

Young Stellar Objects in the Carina Nebula: Insights from DECam Data and Implications for Rubin LSST

  • 1. ROR icon University of Palermo
  • 2. ROR icon Osservatorio Astronomico di Palermo
  • 3. ROR icon Vera C. Rubin Observatory
  • 4. ROR icon Search for Extraterrestrial Intelligence
  • 5. ROR icon Rice University

Description

The Rubin LSST telescope, with its deep filters (ugrizy) and the multi-band information, will provide us with the ability to extract complete catalogues of young stellar object populations and to study their peculiar physical processes.
As a precursor for Rubin LSST, we will present DECam data of Carina Nebula star forming region, relevant for both star forming region investigation and for source extraction in a crowded field. In particular, we will discuss the main issues related to the analysis of such fields, using an instrument very similar to Rubin LSST. This will be useful as a guide to also extract reliable sources and do photometry in star forming regions or in crowded fields in general.
After introducing the whole DECam multi-band survey of the Carina Nebula, this talk will focus on our goal to obtain a complete and detailed stellar catalogue of Carina Nebula in the '2' band. We will discuss our approach and highlight its significance in the context of future Rubin LSST data (that will need to be studied in the same way), and we will show how we can use the Rubin Science Platform as an instrument for visual representation of these data.

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Tramuto_LSST@EUROPE6 (1).pdf

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Additional details

Funding

Osservatorio Astronomico di Palermo
INAF MINI-GRANTS (2023) di RSN2 “Physical properties of Accreting young stellar objects: exploration of their light Curves and Emission (PACE)” 1.05.23.04.02
Osservatorio Astronomico di Palermo
"LSST-Discovery Alliance 2024 Science Catalyst Small Grant Proposal of the INAF team PI: Rosaria (Sara) Bonito; co-Is: Alessandro Salvatore Tramuto and Laura Venuti" in "Young stellar objects and their variability with Rubin LSST: combining observations and 3D models for a more inclusive Science (ref. Rosaria Bonito)" 1.05.03.18.03