NEMESISPY: A Python package for simulating and retrieving exoplanetary spectra

TL;DR

NEMESISPY is a Python package that enables atmospheric modeling and spectral retrievals for exoplanets, building on a proven Fortran library and facilitating analysis of data from telescopes like Hubble, Spitzer, and JWST.

Contribution

It introduces a Python-based tool for exoplanet spectral retrievals, integrating with Bayesian methods and extending the capabilities of the established NEMESIS library.

Findings

Successfully applied to Hubble and Spitzer data of hot Jupiters.

Extended to JWST/MIRI data for exoplanet atmospheres.

Demonstrates versatility in different observational geometries.

Abstract

NEMESISPY is a Python package developed to perform parametric atmospheric modelling and radiative transfer calculation for the retrievals of exoplanetary spectra. It is a recent development of the well-established Fortran NEMESIS library (P. G. J. Irwin et al., 2008), which has been applied to the atmospheric retrievals of both solar system planets and exoplanets employing numerous different observing geometries. NEMESISPY can be easily interfaced with Bayesian inference algorithms to retrieve atmospheric properties from spectroscopic observations. Recently, NEMESISPY has been applied to the retrievals of Hubble and Spitzer data of a hot Jupiter (Yang et al., 2023), as well as to JWST/Mid-Infrared Instrument (JWST/MIRI) data of a hot Jupiter (Yang et al., 2024).