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Title: Deriving Physical Properties from Broadband Photometry with Prospector: Description of the Model and a Demonstration of its Accuracy Using 129 Galaxies in the Local Universe

Abstract

Broadband photometry of galaxies measures an unresolved mix of complex stellar populations, gas, and dust. Interpreting these data is a challenge for models: many studies have shown that properties derived from modeling galaxy photometry are uncertain by a factor of two or more, and yet answering key questions in the field now requires higher accuracy than this. Here, we present a new model framework specifically designed for these complexities. Our model, Prospector- α , includes dust attenuation and re-radiation, a flexible attenuation curve, nebular emission, stellar metallicity, and a six-component nonparametric star formation history. The flexibility and range of the parameter space, coupled with Monte Carlo Markov chain sampling within the Prospector inference framework, is designed to provide unbiased parameters and realistic error bars. We assess the accuracy of the model with aperture-matched optical spectroscopy, which was excluded from the fits. We compare spectral features predicted solely from fits to the broadband photometry to the observed spectral features. Our model predicts H α luminosities with a scatter of ∼0.18 dex and an offset of ∼0.1 dex across a wide range of morphological types and stellar masses. This agreement is remarkable, as the H α luminosity is dependent on accurate starmore » formation rates, dust attenuation, and stellar metallicities. The model also accurately predicts dust-sensitive Balmer decrements, spectroscopic stellar metallicities, polycyclic aromatic hydrocarbon mass fractions, and the age- and metallicity-sensitive features D{sub n}4000 and H δ . Although the model passes all these tests, we caution that we have not yet assessed its performance at higher redshift or the accuracy of recovered stellar masses.« less

Authors:
; ;  [1];  [2];  [3]
  1. Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States)
  2. Department of Astronomy, Yale University, New Haven, CT 06511 (United States)
  3. Department of Astronomy, University of Washington, Seattle, WA 98185 (United States)
Publication Date:
OSTI Identifier:
22661278
Resource Type:
Journal Article
Resource Relation:
Journal Name: Astrophysical Journal; Journal Volume: 837; Journal Issue: 2; Other Information: Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
79 ASTROPHYSICS, COSMOLOGY AND ASTRONOMY; ATTENUATION; COMPUTERIZED SIMULATION; DUSTS; EMISSION; GALAXIES; LUMINOSITY; MASS; METALLICITY; MONTE CARLO METHOD; PHOTOMETRY; POLYCYCLIC AROMATIC HYDROCARBONS; RED SHIFT; SAMPLING; SPACE; SPECTROSCOPY; STARS; UNIVERSE

Citation Formats

Leja, Joel, Johnson, Benjamin D., Conroy, Charlie, Dokkum, Pieter G. van, and Byler, Nell. Deriving Physical Properties from Broadband Photometry with Prospector: Description of the Model and a Demonstration of its Accuracy Using 129 Galaxies in the Local Universe. United States: N. p., 2017. Web. doi:10.3847/1538-4357/AA5FFE.
Leja, Joel, Johnson, Benjamin D., Conroy, Charlie, Dokkum, Pieter G. van, & Byler, Nell. Deriving Physical Properties from Broadband Photometry with Prospector: Description of the Model and a Demonstration of its Accuracy Using 129 Galaxies in the Local Universe. United States. doi:10.3847/1538-4357/AA5FFE.
Leja, Joel, Johnson, Benjamin D., Conroy, Charlie, Dokkum, Pieter G. van, and Byler, Nell. Fri . "Deriving Physical Properties from Broadband Photometry with Prospector: Description of the Model and a Demonstration of its Accuracy Using 129 Galaxies in the Local Universe". United States. doi:10.3847/1538-4357/AA5FFE.
@article{osti_22661278,
title = {Deriving Physical Properties from Broadband Photometry with Prospector: Description of the Model and a Demonstration of its Accuracy Using 129 Galaxies in the Local Universe},
author = {Leja, Joel and Johnson, Benjamin D. and Conroy, Charlie and Dokkum, Pieter G. van and Byler, Nell},
abstractNote = {Broadband photometry of galaxies measures an unresolved mix of complex stellar populations, gas, and dust. Interpreting these data is a challenge for models: many studies have shown that properties derived from modeling galaxy photometry are uncertain by a factor of two or more, and yet answering key questions in the field now requires higher accuracy than this. Here, we present a new model framework specifically designed for these complexities. Our model, Prospector- α , includes dust attenuation and re-radiation, a flexible attenuation curve, nebular emission, stellar metallicity, and a six-component nonparametric star formation history. The flexibility and range of the parameter space, coupled with Monte Carlo Markov chain sampling within the Prospector inference framework, is designed to provide unbiased parameters and realistic error bars. We assess the accuracy of the model with aperture-matched optical spectroscopy, which was excluded from the fits. We compare spectral features predicted solely from fits to the broadband photometry to the observed spectral features. Our model predicts H α luminosities with a scatter of ∼0.18 dex and an offset of ∼0.1 dex across a wide range of morphological types and stellar masses. This agreement is remarkable, as the H α luminosity is dependent on accurate star formation rates, dust attenuation, and stellar metallicities. The model also accurately predicts dust-sensitive Balmer decrements, spectroscopic stellar metallicities, polycyclic aromatic hydrocarbon mass fractions, and the age- and metallicity-sensitive features D{sub n}4000 and H δ . Although the model passes all these tests, we caution that we have not yet assessed its performance at higher redshift or the accuracy of recovered stellar masses.},
doi = {10.3847/1538-4357/AA5FFE},
journal = {Astrophysical Journal},
number = 2,
volume = 837,
place = {United States},
year = {Fri Mar 10 00:00:00 EST 2017},
month = {Fri Mar 10 00:00:00 EST 2017}
}
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