The Challenge: To understand where exoplanets get their chemical inventories, we must look at their birthplaces: protoplanetary disks. Observing water in these disks is critical but computationally demanding.
My Work: As a capstone astronomy project, I successfully reproduced the radiative transfer retrieval results for water vapor distributions in protoplanetary disks observed with JWST using MIRI in MRS mode (based on Romero-Mirza et al., 2024). I utilized the IRIS physical disk model and coupled it with the dynesty nested sampling algorithm to perform complex parameter fitting and Bayesian inference.
The Challenge: Atmospheric retrievals are only as good as the molecular opacity data fed into them. Managing and computing opacities from massive databases is computationally intensive.
My Work: I developed a suite of Python notebooks designed to compute high-resolution molecular cross-sections and opacities. The tool ingests line list databases from both HITRAN and ExoMol. While the HITRAN implementation is currently robust and yielding excellent results, I am actively refining the ExoMol integration to handle its unique formatting and massive line lists more efficiently for our group's retrieval models.