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- W4280565240 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 non-uniform screen model parameterized by the fraction of unobscured stellar light. This non-uniform screen model allows for a non-zero 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 non-uniform 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 non-uniform screen model. With this increase in dust attenuation modeling accuracy, we also improve the star formation rates (SFRs) inferred with the non-uniform 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." @default.
- W4280565240 created "2022-05-22" @default.
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- W4280565240 date "2022-05-01" @default.
- W4280565240 modified "2023-09-30" @default.
- W4280565240 title "How Well Can We Measure Galaxy Dust Attenuation Curves? The Impact of the Assumed Star-dust Geometry Model in Spectral Energy Distribution Fitting" @default.
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- W4280565240 doi "https://doi.org/10.3847/1538-4357/ac6959" @default.
- W4280565240 hasPublicationYear "2022" @default.
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