Brown Dwarfs and Starfish: Understanding Temperature and Chemistry
This presentation delves into the intriguing realms of brown dwarfs and starfish, focusing on temperature variations, carbon-oxygen ratios, surface gravity, vertical mixing, metallicity, and disequilibrium chemistry. The content explores models and errors in stellar atmosphere simulations, emphasizing factors such as radiative transfer, convection, and chemical equilibrium. Practical insights on sources of error, interpolation, noise, global systematics, and elaborate data analysis techniques are also covered.
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Presentation Transcript
BROWN DWARFS AND BROWN DWARFS AND STARFISH. STARFISH. Isabela Huckabee, Aishwarya Isabela Huckabee, Aishwarya Iyer Iyer, Michael Line , Michael Line Arizona State University Arizona State University Arizona/NASA Space Grant Consortium Symposium 2022 Arizona/NASA Space Grant Consortium Symposium 2022
Modified from Modified from Mainzer Mainzer et al. 2009 et al. 2009
Putting it all together Putting it all together Temperature Temperature Carbon to Oxygen Ratio Carbon to Oxygen Ratio Surface Gravity Surface Gravity Vertical Mixing Vertical Mixing Metallicity Metallicity
Putting it all together Putting it all together Carbon to Oxygen Ratio Carbon to Oxygen Ratio Temperature Temperature CH4 vs CO content, formation CH4 vs CO content, formation Surface Gravity Surface Gravity Vertical Mixing Vertical Mixing Metallicity Metallicity Disequilibrium chemistry Disequilibrium chemistry ( (logKzz logKzz) )
Model + Error Overview Model + Error Overview 1D stellar atmosphere model 1D stellar atmosphere model Radiative transfer, convection, Radiative transfer, convection, equilibrium and disequilibrium equilibrium and disequilibrium chemistry chemistry - - Model Interpolation Model Interpolation Correlation between data Correlation between data points points - - f fudge factor udge factor
Starfish: Sources of Error Starfish: Sources of Error Interpolation Interpolation Noise Noise Global Global Model systematics, Model systematics, wavelength correlated wavelength correlated data data- -model residuals model residuals Via total reconstruction Via total reconstruction of model grid of model grid Noise in data caused by Noise in data caused by random systematics random systematics Interpolation + Noise + Global = Fancy Error Covariance Matrix Interpolation + Noise + Global = Fancy Error Covariance Matrix Czekala Czekala et al. 2015 et al. 2015
C/O C/O logKzz logKzz
- Compare traditional fit Compare traditional fit to Starfish fit to Starfish fit - Clouds? Clouds? Disequilibrium? Both? Disequilibrium? Both? What s Next? What s Next? - T T- -dwarfs: dwarfs: test bed for disequilibrium disequilibrium - Low gravity M Low gravity M- -dwarfs: test bed for clouds test bed for clouds test bed for dwarfs:
Questions? Questions? ihuckabe@asu.edu ihuckabe@asu.edu Thank you to my mentors Aishwarya Thank you to my mentors Aishwarya Iyer Michael Line, as well as the AZ/NASA Space Michael Line, as well as the AZ/NASA Space Grant Program and ASU s School of Earth and Grant Program and ASU s School of Earth and Iyer and and Space Exploration Space Exploration
