{"id":3359,"date":"2024-06-19T20:31:09","date_gmt":"2024-06-19T23:31:09","guid":{"rendered":"https:\/\/astro.uc.cl\/?post_type=charlas&p=3359"},"modified":"2024-06-19T20:31:19","modified_gmt":"2024-06-19T23:31:19","slug":"a-multi-wavelength-study-of-baryonic-structures-in-the-fornax-galaxy-cluster-yasna-ordenes-briceno","status":"publish","type":"charlas","link":"https:\/\/astro.uc.cl\/en\/charlas\/a-multi-wavelength-study-of-baryonic-structures-in-the-fornax-galaxy-cluster-yasna-ordenes-briceno\/","title":{"rendered":"A Multi-wavelength Study of Baryonic Structures in the Fornax Galaxy Cluster \u2013 Yasna Ordenes Brice\u00f1o"},"content":{"rendered":"\n

The multi-wavelength analysis of various astronomical objects and their environments, with homogeneous and deep mapping, has become feasible with the advent of large cameras installed on some of the largest telescopes (primary >4 meters) over the last decade. Several surveys have utilized cameras such as HSC, CFHT, and DES to target specific objects or large sky areas. The next generation of cameras and telescopes, such as LSST at the Vera Rubin Observatory, will surpass these efforts by increasing sky coverage in a homogeneous and panchromatic manner.<\/p>\n\n\n\n

This presentation will showcase the results of one such survey in the Southern Hemisphere, covering the nearby Fornax galaxy cluster located 20 Mpc from Earth. The Next Generation Fornax Survey (NGFS) has obtained deep images in optical filters u’, g’, i’ using CTIO\/DECam, and near-infrared J, Ks filters using ESO\/VIRCAM, covering ~55deg2 (~virial radius) and ~30deg2, respectively.<\/p>\n\n\n\n

I will present updates on the low surface brightness galaxy population within the virial sphere of Fornax. However, most of the results will focus on the photometric analysis of globular clusters (GCs) in u’g’i’JKs within the Fornax core region (<350 kpc), located around both bright and faint galaxies as well as within the intracluster medium. I will describe the implemented method for GC detection and selection using a machine learning classification approach, as well as methods for characterizing them in terms of magnitude, color, metallicity, age, and mass. Finally, based on their properties and spatial distribution information, we will discuss possible scenarios for the mass assembly of the Fornax galaxy cluster.<\/p>\n\n\n\n

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