An Observational Diagnostic for Distinguishing Between Clouds and Haze in Hot Exoplanet Atmospheres

The nature of aerosols in hot exoplanet atmospheres is one of the primary vexing questions facing the exoplanet field. The complex chemistry, multiple formation pathways, and lack of easily identifiable spectral features associated with aerosols make it especially challenging to constrain their key properties. We propose a transmission spectroscopy technique to identify the primary aerosol formation mechanism for the most highly irradiated hot Jupiters (HIHJs). The technique is based on the expectation that the two key types of aerosols -- photochemically generated hazes and equilibrium condensate clouds -- are expected to form and persist in different regions of a highly irradiated planet's atmosphere. Haze can only be produced on the permanent daysides of tidally-locked hot Jupiters, and will be carried downwind by atmospheric dynamics to the evening terminator (seen as the trailing limb during transit). Clouds can only form in cooler regions on the night side and morning terminator of HIHJs (seen as the leading limb during transit). Because opposite limbs are expected to be impacted by different types of aerosols, ingress and egress spectra, which primarily probe opposing sides of the planet, will reveal the dominant aerosol formation mechanism. We show that the benchmark HIHJ, WASP-121b, has a transmission spectrum consistent with partial aerosol coverage and that ingress-egress spectroscopy would constrain the location and formation mechanism of those aerosols. In general, using this diagnostic we find that observations with JWST and potentially with HST should be able to distinguish between clouds and haze for currently known HIHJs.Comment: 10 pages, 4 figures, accepted to ApJ Letter

Deciphering the Atmospheric Composition of WASP-12b: A Comprehensive Analysis of its Dayside Emission

WASP-12b was the first planet reported to have a carbon-to-oxygen ratio (C/O) greater than one in its dayside atmosphere. However, recent work to further characterize its atmosphere and confirm its composition has led to incompatible measurements and divergent conclusions. Additionally, the recent discovery of stellar binary companions ~1" from WASP-12 further complicates the analyses and subsequent interpretations. We present a uniform analysis of all available Hubble and Spitzer Space Telescope secondary-eclipse data, including previously-unpublished Spitzer measurements at 3.6 and 4.5 microns. The primary controversy in the literature has centered on the value and interpretation of the eclipse depth at 4.5 microns. Our new measurements and analyses confirm the shallow eclipse depth in this channel, as first reported by Campo and collaborators and used by Madhusudhan and collaborators to infer a carbon-rich composition. To explain WASP-12b's observed dayside emission spectrum, we implemented several recent retrieval approaches. We find that when we exclude absorption due to C2H2 and HCN, which are not universally considered in the literature, our models require implausibly large atmospheric CO2 abundances, regardless of the C/O. By including C2H2 and HCN in our models, we find that a physically-plausible carbon-rich solution achieves the best fit to the available photometric and spectroscopic data. In comparison, the best-fit oxygen-rich models have abundances that are inconsistent with the chemical equilibrium expectations for hydrogen-dominated atmospheres and are 670 times less probable. Our best-fit solution is also 7.3*10^{6} times more probable than an isothermal blackbody model.Comment: 8 pages, 7 figures, accepted for publication in Ap

Teaching Reproducibility to First Year College Students: Reflections From an Introductory Data Science Course

Access the online Pressbooks version of this article here. Modern technology threatens traditional modes of classroom assessment by providing students with automated ways to write essays and take exams. At the same time, modern technology continues to expand the accessibility of computational tools that promise to increase the potential scope and quality of class projects. This paper presents a case study where students are asked to complete a “reproducible” final project in an introductory data science course using the R programming language. A reproducible project is one where an instructor can easily regenerate the results and conclusions from the submitted materials. Experiences in two small sections of this introductory class suggest that reproducible projects are feasible to implement with only a little increase in assessment difficulty. The sample assignment presented in this paper, along with some proposed adaptations for non-data science classes, provide a pattern for directly assessing a student’s analysis, rather than just the final results