The Astrophysical Journal · 2023 · 26 citations · 61 references
Natural SciencesAstronomyAtmospheric ScienceCloud PhysicsInfrared AstronomyCloud ParameterizationCloud PropertiesRed GiantsStellar AtmospheresAtmospheric Composition RetrievalAtmospheric RetrievalsChemical Abundance AnalysisChemical Abundance ModelingCloud Microphysics RetrievalsCloud RetrievalsRadiative Boundary ConditionsStellar Atmosphere Models
Abstract Constraining L dwarf properties from their spectra is challenging. Near-infrared (NIR) spectra probe a limited range of pressures, while many species condense within their photospheres. Condensation creates two complexities: gas-phase species “rain out” (decreasing in abundances by many orders of magnitude) and clouds form. We designed tests using synthetic data to determine the best approach for retrieving L dwarf spectra, isolating the challenges in the absence of cloud opacity. We conducted atmospheric retrievals on synthetic cloud-free L dwarf spectra derived from the Sonora Bobcat models at SpeX resolution using a variety of thermal and chemical abundance profile parameterizations. For objects hotter than L5 ( T eff ∼ 1700 K), the limited pressure layers probed in the NIR are mostly convective; parameterized pressure–temperature ( PT ) profiles bias results and free, unsmoothed profiles should be used. Only when many layers both above and below the radiative-convective boundary are probed can parameterized profiles provide accurate results. Furthermore, a nonuniform abundance profile for FeH is needed to accurately retrieve bulk properties of early-to-mid L dwarfs. Nonuniform prescriptions for other gases in NIR retrievals may also be warranted near the L/T transition (CH 4 ) and early Y dwarfs (Na and K). We demonstrate the utility of using realistic, self-consistent models to benchmark retrievals and suggest how they can be used in the future.
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