A Multiwavelength Study of a Sample of 70 micron Selected Galaxies in the COSMOS Field I: Spectral Energy Distributions and Luminosities
Jeyhan S. Kartaltepe, D. B. Sanders, E. Le Floc'h, D. T. Frayer, H., Aussel, S. Arnouts, O. Ilbert, M. Salvato, N. Z. Scoville, J. Surace, L. Yan,, M. Brusa, P. Capak, K. Caputi, C. M. Carollo, F. Civano, M. Elvis, C. Faure,, G. Hasinger, A. M. Koekemoer, N. Lee, S. Lilly

TL;DR
This study analyzes 1503 70-micron selected galaxies in the COSMOS field, deriving their spectral energy distributions and infrared luminosities, revealing diverse galaxy types and the prevalence of active galactic nuclei at high luminosities.
Contribution
It provides a comprehensive multiwavelength dataset and improved luminosity estimates for a large galaxy sample, including the first extensive SEDs from UV to FIR for these sources.
Findings
Wide range of infrared luminosities (10^8 to 10^14 L_sun)
High fraction of AGN in luminous infrared galaxies
Evidence for cooler ultraluminous objects than locally observed
Abstract
We present a large robust sample of 1503 reliable and unconfused 70microm selected sources from the multiwavelength data set of the Cosmic Evolution Survey (COSMOS). Using the Spitzer IRAC and MIPS photometry, we estimate the total infrared luminosity, L_IR (8--1000 microns), by finding the best fit template from several different template libraries. The long wavelength 70 and 160 micron data allow us to obtain a reliable estimate of L_IR, accurate to within 0.2 and 0.05 dex, respectively. The 70 micron data point enables a significant improvement over the luminosity estimates possible with only a 24 micron detection. The full sample spans a wide range in L_IR, L_IR ~ 10^8-10^14 L_sun, with a median luminosity of 10^11.4 L_sun. We identify a total of 687 luminous, 303 ultraluminous, and 31 hyperluminous infrared galaxies (LIRGs, ULIRGs, and HyLIRGs) over the redshift range 0.01<z<3.5…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
