Everett A Schlawin

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Journals/Publications

• Schlawin, E. A. (2020). Eigenspectra: A Framework for Identifying Spectra from 3D Eclipse Mapping. MNRAS.
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  Planetary atmospheres are inherently 3D objects that can have stronggradients in latitude, longitude, and altitude. Secondary eclipse mapping is apowerful way to map the 3D distribution of the atmosphere, but the data canhave large correlations and errors in the presence of photon and instrumentnoise. We develop a technique to mitigate the large uncertainties of eclipsemaps by identifying a small number of dominant spectra to make them moretractable for individual analysis via atmospheric retrieval. We use theeigencurves method to infer a multi-wavelength map of a planet fromspectroscopic secondary eclipse light curves. We then apply a clusteringalgorithm to the planet map to identify several regions with similar emergentspectra. We combine the similar spectra together to construct an"eigenspectrum" for each distinct region on the planetary map. We demonstratehow this approach could be used to isolate hot from cold regions and/or regionswith different chemical compositions in observations of hot Jupiters with theJames Webb Space Telescope (JWST). We find that our method struggles toidentify sharp edges in maps with sudden discontinuities, but generally can beused as a first step before a more physically motivated modeling approach todetermine the primary features observed on the planet.[Journal_ref: ]
• Schlawin, E. A. (2020). JWST Noise Floor II: Systematic Error Sources in JWST NIRCam Time Series. AJ.
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  JWST holds great promise in characterizing atmospheres of transitingexoplanets, potentially providing insights into Earth-sized planets within thehabitable zones of M dwarf host stars if photon-limited performance can beachieved. Here, we discuss the systematic error sources that are expected to bepresent in grism time series observations with the NIRCam instrument. We findthat pointing jitter and high gain antenna moves on top of the detectors'subpixel crosshatch patterns will produce relatively small variations (lessthan 6 parts per million, ppm). The time-dependent aperture losses due tothermal instabilities in the optics can also be kept to below 2 ppm. To achievethese low noise sources, it is important to employ a sufficiently large (morethan 1.1 arcseconds) extraction aperture. Persistence due to charge trappingwill have a minor (less than 3 ppm) effect on time series 20 minutes into anexposure and is expected to play a much smaller role than it does for the HSTWFC3 detectors. We expect temperature fluctuations to be less than 3 ppm. Intotal, our estimated noise floor from known systematic error sources is only 9ppm per visit. We do however urge caution as unknown systematic error sourcescould be present in flight and will only be measurable on astrophysical sourceslike quiescent stars. We find that reciprocity failure may introduce aperennial instrument offset at the 40 ppm level, so corrections may be neededwhen stitching together a multi-instrument multi-observatory spectrum over widewavelength ranges.[Journal_ref: AJ, 161, 115 (2021)]
• Schlawin, E. A. (2021). JWST Noise Floor I: Random Error Sources in JWST NIRCam Time Series. AJ.
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  JWST transmission and emission spectra will provide invaluable glimpses oftransiting exoplanet atmospheres, including possible biosignatures. Thispromising science from JWST, however, will require exquisite precision andunderstanding of systematic errors that can impact the time series of planetscrossing in front of and behind their host stars. Here, we provide estimates ofthe random noise sources affecting JWST NIRCam time-series data on theintegration-to-integration level. We find that 1/f noise can limit theprecision of grism time series for 2 groups (230 ppm to 1000 ppm depending onthe extraction method and extraction parameters), but will average down likethe square root of N frames/reads. The current NIRCam grism time series mode isespecially affected by 1/f noise because its GRISMR dispersion direction isparallel to the detector fast-read direction, but could be alleviated in theGRISMC direction. Care should be taken to include as many frames as possibleper visit to reduce this 1/f noise source: thus, we recommend the smallestdetector subarray sizes one can tolerate, 4 output channels and readout modesthat minimize the number of skipped frames (RAPID or BRIGHT2). We also describea covariance weighting scheme that can significantly lower the contributionsfrom 1/f noise as compared to sum extraction. We evaluate the noise introducedby pre-amplifier offsets, random telegraph noise, and high dark current RCpixels and find that these are correctable below 10 ppm once backgroundsubtraction and pixel masking are performed. We explore systematic errorsources in a companion paper.[Journal_ref: ]

Poster Presentations

• Schlawin, E. A. (2021, January). The MESCIT Program: Partnering University of Arizona Undergraduate Students with Native American High Schoolers to Improve Math and Teaching Skills. AAS Meeting 237.