On the Utility of Transmission Color Analysis I: Differentiating Super-Earths and Sub-Neptunes

TL;DR

This study explores a transmission color photometric method to efficiently differentiate super-Earths from sub-Neptunes, achieving over 90% accuracy with minimal filters, thus enabling large-scale exoplanet characterization.

Contribution

It introduces a novel, low-resolution transmission color analysis technique for rapid exoplanet classification, reducing reliance on extensive spectroscopic observations.

Findings

Achieves >90% accuracy in distinguishing planetary types with two filters.

Increasing the number of filters does not significantly improve classification performance.

Method enables efficient, large-scale exoplanet population studies.

Abstract

The majority of exoplanets found to date have been discovered via the transit method, and transmission spectroscopy represents the primary method of studying these distant worlds. Currently, in-depth atmospheric characterization of transiting exoplanets entails the use of spectrographs on large telescopes, requiring significant observing time to study each planet. Previous studies have demonstrated trends for solar system worlds using color-color photometry of reflectance spectra, as well as trends within transmission spectra for hot Jupiters. Building on these concepts, we have investigated the use of transmission color photometric analysis for efficient, coarse categorization of exoplanets and for assessing the nature of these worlds, with a focus on resolving the bulk composition degeneracy to aid in discriminating super-Earths and sub-Neptunes. We present our methodology and first results, including spectrum models, model comparison frameworks, and wave band selection criteria. We present our results for different transmission "color" metrics, filter selection methods, and numbers of filters. Assuming noise-free spectra of isothermal atmospheres in chemical equilibrium, with our pipeline, we are able to constrain atmospheric mean molecular weight in order to distinguish between super-Earth and sub-Neptune atmospheres with >90$\%$ overall accuracy using as few as two specific low-resolution filter combinations. We also found that increasing the number of filters does not substantially impact this performance. This method could allow for broad characterization of large numbers of planets much more efficiently than current methods permit, enabling population and system-level studies. Additionally, data collected via this method could inform follow-up observing time by large telescopes for more detailed studies of worlds of interest.