How Well Can We Measure Galaxy Dust Attenuation Curves? the Impact of the Assumed Star-dust Geometry Model in Spectral Energy Distribution Fitting

Sidney Lower, Desika Narayanan, Joel Leja, Benjamin D. Johnson, Charlie Conroy, Romeel Davé

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

One of the most common methods for inferring galaxy attenuation curves is via spectral energy distribution (SED) modeling, where the dust attenuation properties are modeled simultaneously with other galaxy physical properties. In this paper, we assess the ability of SED modeling to infer these dust attenuation curves from broadband photometry, and suggest a new flexible model that greatly improves the accuracy of attenuation curve derivations. To do this, we fit mock SEDs generated from the simba cosmological simulation with the prospector SED fitting code. We consider the impact of the commonly assumed uniform screen model and introduce a new nonuniform screen model parameterized by the fraction of unobscured stellar light. This nonuniform screen model allows for a nonzero fraction of stellar light to remain unattenuated, resulting in a more flexible attenuation curve shape by decoupling the shape of the UV attenuation curve from the optical attenuation curve. The ability to constrain the dust attenuation curve is significantly improved with the use of a nonuniform screen model, with the median offset in UV attenuation decreasing from -0.30 dex with a uniform screen model to -0.17 dex with the nonuniform screen model. With this increase in dust attenuation modeling accuracy, we also improve the star formation rates (SFRs) inferred with the nonuniform screen model, decreasing the SFR offset on average by 0.12 dex. We discuss the efficacy of this new model, focusing on caveats with modeling star-dust geometries and the constraining power of available SED observations.

Original languageEnglish (US)
Article number14
JournalAstrophysical Journal
Volume931
Issue number1
DOIs
StatePublished - May 1 2022

All Science Journal Classification (ASJC) codes

  • Astronomy and Astrophysics
  • Space and Planetary Science

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