12,939 research outputs found
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previously-unpublished Spitzer measurements at 3.6 and 4.5 microns.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
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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
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