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Details

Autor(en) / Beteiligte
Titel
High-redshift Galaxies and Black Holes Detectable with the JWST: A Population Synthesis Model from Infrared to X-Rays
Ist Teil von
  • The Astrophysical journal, 2017-11, Vol.849 (2), p.155
Ort / Verlag
Philadelphia: The American Astronomical Society
Erscheinungsjahr
2017
Link zum Volltext
Quelle
EZB Free E-Journals
Beschreibungen/Notizen
  • The first billion years of the Universe has been a pivotal time: stars, black holes (BHs), and galaxies formed and assembled, sowing the seeds of galaxies as we know them today. Detecting, identifying, and understanding the first galaxies and BHs is one of the current observational and theoretical challenges in galaxy formation. In this paper we present a population synthesis model aimed at galaxies, BHs, and active galactic nuclei (AGNs) at high redshift. The model builds a population based on empirical relations. The spectral energy distribution of galaxies is determined by age and metallicity, and that of AGNs by BH mass and accretion rate. We validate the model against observations, and predict properties of galaxies and AGN in other wavelength and/or luminosity ranges, estimating the contamination of stellar populations (normal stars and high-mass X-ray binaries) for AGN searches from the infrared to X-rays, and vice versa for galaxy searches. For high-redshift galaxies with stellar ages , we find that disentangling stellar and AGN emission is challenging at restframe UV/optical wavelengths, while high-mass X-ray binaries become more important sources of confusion in X-rays. We propose a color-color selection in the James Webb Space Telescope bands to separate AGN versus star-dominated galaxies in photometric observations. We also estimate the AGN contribution, with respect to massive, hot, and metal-poor stars, at driving high-ionization lines, such as C iv and He ii. Finally, we test the influence of the minimum BH mass and occupation fraction of BHs in low-mass galaxies on the restframe UV/near-IR and X-ray AGN luminosity function.

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