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Binary Population and Spectral Synthesis

Published online by Cambridge University Press:  28 July 2017

J. J. Eldridge ,
E. R. Stanway ,
L. Xiao ,
L. A. S. McClelland ,
J. C. Bray ,
G. Taylor  and
M. Ng
J. J. Eldridge*
Affiliation:
Department of Physics, University of Auckland, Private Bag 92019, Auckland, New Zealand
E. R. Stanway
Affiliation:
Department of Physics, University of Warwick, Gibbet Hill Road, Coventry, CV4 7AL, UK
L. Xiao
Affiliation:
Department of Physics, University of Auckland, Private Bag 92019, Auckland, New Zealand
L. A. S. McClelland
Affiliation:
Department of Physics, University of Auckland, Private Bag 92019, Auckland, New Zealand
J. C. Bray
Affiliation:
Department of Physics, University of Auckland, Private Bag 92019, Auckland, New Zealand
G. Taylor
Affiliation:
Department of Physics, University of Auckland, Private Bag 92019, Auckland, New Zealand
M. Ng
Affiliation:
Department of Physics, University of Auckland, Private Bag 92019, Auckland, New Zealand
*
†email: j.eldridge@auckland.ac.nz
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Abstract

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We have recently released version 2.0 of the Binary Population and Spectral Synthesis (BPASS) population synthesis code. This is designed to construct the spectra and related properties of stellar populations built from ~200,000 detailed, individual stellar models of known age and metallicity. The output products enable a broad range of theoretical predictions for individual stars, binaries, resolved and unresolved stellar populations, supernovae and their progenitors, and compact remnant mergers. Here we summarise key applications that demonstrate that binary populations typically reproduce observations better than single star models.

Keywords

methods: numericalstars: evolutionstars: statisticsgalaxies: stellar content

References

Eldridge, J. J., Stanway, E. R., 2016, MNRAS, 462, 3302 CrossRefGoogle Scholar
Eldridge, J. J., Maund, J. R., 2016, MNRAS, 461, L117 CrossRefGoogle Scholar
Moriya, T. J., Eldridge, J. J., 2016, MNRAS, 461, 2155 Google Scholar
Shenar, T., et al., 2016, A&A, 591, A22 Google Scholar
Stanway, E. R., Eldridge, J. J., & Becker, G. D., 2016, MNRAS, 456, 485 Google Scholar
Strom, A. L., et al., ApJ, 836, 164 Google Scholar
Wofford, A., et al., 2016, MNRAS, 457, 4296 Google Scholar