Browsing by Author "Kartaltepe, Jeyhan S."
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- ItemCharacterization of Two 2 mm detected Optically Obscured Dusty Star-forming Galaxies(2022) Manning, Sinclaire M.; Casey, Caitlin M.; Zavala, Jorge A.; Magdis, Georgios E.; Drew, Patrick M.; Champagne, Jaclyn B.; Aravena, Manuel; Béthermin, Matthieu; Clements, David L.; Finkelstein, Steven L.; Fujimoto, Seiji; Hayward, Christopher C.; Hodge, Jacqueline A.; Ilbert, Olivier; Kartaltepe, Jeyhan S.; Knudsen, Kirsten K.; Koekemoer, Anton M.; Man, Allison W. S.; Sanders, David B.; Sheth, Kartik; Spilker, Justin S.; Staguhn, Johannes; Talia, Margherita; Treister, Ezequiel; Yun, Min S.The 2 mm Mapping Obscuration to Reionization with ALMA (MORA) Survey was designed to detect high-redshift (z greater than or similar to 4), massive, dusty star-forming galaxies (DSFGs). Here we present two likely high-redshift sources, identified in the survey, whose physical characteristics are consistent with a class of optical/near-infrared (OIR)-invisible DSFGs found elsewhere in the literature. We first perform a rigorous analysis of all available photometric data to fit spectral energy distributions and estimate redshifts before deriving physical properties based on our findings. Our results suggest the two galaxies, called MORA-5 and MORA-9, represent two extremes of the "OIR-dark" class of DSFGs. MORA-5 (z(phot) = 4.3(-1.3)(+1.5)) is a significantly more active starburst with a star formation rate (SFR) of 830(-190)(+340) M-circle dot yr(-1) compared to MORA-9 (z(phot) = 4.3(-1.0)(+1.3)), whose SFR is a modest 200(-60)(+250) M-circle dot yr(-1). Based on the stellar masses (M-star approximate to 10(10-11) M-circle dot), space density (n similar to (5 +/- 2) x 10(-6) Mpc(-3), which incorporates two other spectroscopically confirmed OIR-dark DSFGs in the MORA sample at z = 4.6 and z = 5.9), and gas depletion timescales (<1 Gyr) of these sources, we find evidence supporting the theory that OIR-dark DSFGs are the progenitors of recently discovered 3 < z < 4 massive quiescent galaxies.
- ItemInvestigating the Effect of Galaxy Interactions on the Enhancement of Active Galactic Nuclei at 0.5 < z < 3.0(2020) Shah, Ekta A.; Kartaltepe, Jeyhan S.; Magagnoli, Christina T.; Cox, Isabella G.; Wetherell, Caleb T.; Vanderhoof, Brittany N.; Calabro, Antonello; Chartab, Nima; Conselice, Christopher J.; Croton, Darren J.; Donley, Jennifer; de Groot, Laura; de la Vega, Alexander; Hathi, Nimish P.; Ilbert, Olivier; Inami, Hanae; Kocevski, Dale D.; Koekemoer, Anton M.; Lemaux, Brian C.; Mantha, Kameswara Bharadwaj; Marchesi, Stefano; Martig, Marie; Masters, Daniel C.; McGrath, Elizabeth J.; McIntosh, Daniel H.; Moreno, Jorge; Nayyeri, Hooshang; Pampliega, Belen Alcalde; Salvato, Mara; Snyder, Gregory F.; Straughn, Amber N.; Treister, Ezequiel; Weston, Madalyn E.Galaxy interactions and mergers are thought to play an important role in the evolution of galaxies. Studies in the nearby universe show a higher fraction of active galactic nuclei (AGNs) in interacting and merging galaxies than in their isolated counterparts, indicating that such interactions are important contributors to black hole growth. To investigate the evolution of this role at higher redshifts, we have compiled the largest known sample of major spectroscopic galaxy pairs (2381 with Delta V < 5000 km s(-1)) at 0.5 < z < 3.0 from observations in the COSMOS and CANDELS surveys. We identify X-ray and IR AGNs among this kinematic pair sample, a visually identified sample of mergers and interactions, and a mass-, redshift-, and environment-matched control sample for each in order to calculate AGN fractions and the level of AGN enhancement as a function of relative velocity, redshift, and X-ray luminosity. While we see a slight increase in AGN fraction with decreasing projected separation, overall, we find no significant enhancement relative to the control sample at any separation. In the closest projected separation bin (< 25 kpc, Delta V < 1000 km s(-1)), we find enhancements of a factor of 0.94(-0.16)(+0.21) and 1.00(-0.31)(+0.58) for X-ray and IR-selected AGNs, respectively. While we conclude that galaxy interactions do not significantly enhance AGN activity on average over 0.5 < z < 3.0 at these separations, given the errors and the small sample size at the closest projected separations, our results would be consistent with the presence of low-level AGN enhancement.
- ItemMorphological Parameters and Associated Uncertainties for 8 Million Galaxies in the Hyper Suprime-Cam Wide Survey(2023) Ghosh, Aritra; Urry, C. Megan; Mishra, Aayush; Perreault-Levasseur, Laurence; Natarajan, Priyamvada; Sanders, David B.; Nagai, Daisuke; Tian, Chuan; Cappelluti, Nico; Kartaltepe, Jeyhan S.; Powell, Meredith C.; Rau, Amrit; Treister, EzequielWe use the Galaxy Morphology Posterior Estimation Network (GaMPEN) to estimate morphological parameters and associated uncertainties for & SIM;8 million galaxies in the Hyper Suprime-Cam Wide survey with z & LE; 0.75 and m & LE; 23. GaMPEN is a machine-learning framework that estimates Bayesian posteriors for a galaxy's bulge-to-total light ratio (L ( B )/L ( T )), effective radius (R ( e )), and flux (F). By first training on simulations of galaxies and then applying transfer learning using real data, we trained GaMPEN with <1% of our data set. This two-step process will be critical for applying machine-learning algorithms to future large imaging surveys, such as the Rubin-Legacy Survey of Space and Time, the Nancy Grace Roman Space Telescope, and Euclid. By comparing our results to those obtained using light profile fitting, we demonstrate that GaMPEN's predicted posterior distributions are well calibrated (& LSIM;5% deviation) and accurate. This represents a significant improvement over light profile fitting algorithms, which underestimate uncertainties by as much as & SIM;60%. For an overlapping subsample, we also compare the derived morphological parameters with values in two external catalogs and find that the results agree within the limits of uncertainties predicted by GaMPEN. This step also permits us to define an empirical relationship between the Sersic index and L ( B )/L ( T ) that can be used to convert between these two parameters. The catalog presented here represents a significant improvement in size (& SIM;10x), depth (& SIM;4 mag), and uncertainty quantification over previous state-of-the-art bulge+disk decomposition catalogs. With this work, we also release GaMPEN's source code and trained models, which can be adapted to other data sets.
- ItemMorphological Parameters and Associated Uncertainties for 8 Million Galaxies in the Hyper Suprime-Cam Wide Survey(Wiley, 2023) Ghosh, Aritra; Urry, C. Megan; Mishra, Aayush; Perreault-Levasseur, Laurence; Natarajan, Priyamvada; Sanders, David B.; Nagai, Daisuke; Tian, Chuan; Cappelluti, Nico; Kartaltepe, Jeyhan S.; Powell, Meredith C.; Rau, Amrit; Treister, EzequielWe use the Galaxy Morphology Posterior Estimation Network (GaMPEN) to estimate morphological parameters and associated uncertainties for & SIM;8 million galaxies in the Hyper Suprime-Cam Wide survey with z & LE; 0.75 and m & LE; 23. GaMPEN is a machine-learning framework that estimates Bayesian posteriors for a galaxy's bulge-to-total light ratio (L ( B )/L ( T )), effective radius (R ( e )), and flux (F). By first training on simulations of galaxies and then applying transfer learning using real data, we trained GaMPEN with <1% of our data set. This two-step process will be critical for applying machine-learning algorithms to future large imaging surveys, such as the Rubin-Legacy Survey of Space and Time, the Nancy Grace Roman Space Telescope, and Euclid. By comparing our results to those obtained using light profile fitting, we demonstrate that GaMPEN's predicted posterior distributions are well calibrated (& LSIM;5% deviation) and accurate. This represents a significant improvement over light profile fitting algorithms, which underestimate uncertainties by as much as & SIM;60%. For an overlapping subsample, we also compare the derived morphological parameters with values in two external catalogs and find that the results agree within the limits of uncertainties predicted by GaMPEN. This step also permits us to define an empirical relationship between the Sersic index and L ( B )/L ( T ) that can be used to convert between these two parameters. The catalog presented here represents a significant improvement in size (& SIM;10x), depth (& SIM;4 mag), and uncertainty quantification over previous state-of-the-art bulge+disk decomposition catalogs. With this work, we also release GaMPEN's source code and trained models, which can be adapted to other data sets.
- ItemRest-frame optical emission lines in far-infrared-selected galaxies at z < 1.7 from the fmos-cosmos survey(2015) Kartaltepe, Jeyhan S.; Treister, Ezequiel; Sanders, David B.; Silverman, J. D.; Kashino, D.; Chu, J.; Zahid, H.; Hasinger, G.; Kewley, L.; Matsuoka, K.; Nagao, T.