Date: Monday 16-Oct-2023
Time: 11:30-12:30 pm
Location: ATL 1250 and Zoom (contact host for link)
Speaker: Matthew Nixon (UMD)
Title: Marginalising over the competition: Robust atmospheric inference in the face of multiple candidate models
Abstract: A key goal of exoplanet spectroscopy is to measure atmospheric properties, such as abundances of chemical species, in order to connect them to our understanding of atmospheric physics and planet formation. In this new era of high-quality JWST data, it is paramount that these measurement methods are robust. When comparing atmospheric models to observations, multiple candidate models may produce reasonable fits to the data. Typically, conclusions are reached by selecting the best-performing model according to some metric. This ignores model uncertainty in favour of specific model assumptions, potentially leading to measured atmospheric properties that are overconfident and/or incorrect. In this talk, I will discuss ensemble methods for addressing model uncertainty by combining posterior distributions from multiple analyses. These methods lead to uncertainties on retrieved parameters that are larger, but more realistic given our modelling capabilities. I will show an application to HST data of a hot Jupiter which demonstrates that uncertainties derived from retrievals of HST spectra have likely been underreported. These methods are widely applicable to other exoplanet analysis processes, such as combining results from different data reductions.
If you have any questions, contact the PALS hosts: Jacob Kloos (small bodies) and Matt Nixon (exoplanets).
SPECIAL ACCOMMODATIONS:Special accommodations for individuals with disabilities can be made by calling (301) 405-3001. It would be appreciated if we are notified at least one week in advance.
