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Douglas A Caldwell

Publications and source records attributed to Douglas A Caldwell.

47 records · Page 3

TESS Data Release Notes: Sector 24, DR35

These Data Release Notes provide information on the processing and export of data from the Transiting Exoplanet Survey Satellite (TESS). The data products included in this data release are full frame images (FFIs), target pixel fi les, light curve fi les, collateral pixel fi les, cotrending basis vectors (CBVs), and Data Validation (DV) reports, time series, and associated xml fi les. These data products were generated by the TESS Science Processing Operations Center (SPOC, Jenkins et al., 2016) at NASA Ames Research Center from data collected by the TESS instrument, which is managed by the TESS Payload Operations Center (POC) at Massachusetts Institute of Technology (MIT). The format and content of these data products are documented in the Science Data Products Description Document (SDPDD). The SPOC science algorithms are based heavily on those of the Kepler Mission science pipeline, and are described in the Kepler Data Processing Handbook (Jenkins, 2019).2 The Data Validation algorithms are documented in Twicken et al. (2018) and Li et al. (2019). The TESS Instrument Handbook (Vanderspek et al., 2018) contains more information about the TESS instrument design, detector layout, data properties, and mission operations. The TESS Mission is funded by NASA's Science Mission Directorate.

TESS↗

Kepler Instrument Performance: An In-Flight Update

The Kepler Mission is designed to detect the 80 parts per million (ppm) signal from an Earth-Sun equivalent transit. Such precision requires superb instrument stability on time scales up to 2 days and systematic error removal to better than 20 ppm. The sole scientic instrument is the Photometer, a 0.95 m aperture Schmidt telescope that feeds the 94.6 million pixel CCD detector array, which contains both Science and Fine Guidance Sensor (FGS) CCDs. Since Kepler's launch in March 2009, we have been using the commissioning and science operations data to characterize the instrument and monitor its performance. We find that the in-flight detector properties of the focal plane, including bias levels, read noise, gain, linearity, saturation, FGS to Science crosstalk,and video crosstalk between Science CCDs, are essentially unchanged from their pre-launch values. Kepler'sunprecedented sensitivity and stability in space have allowed us to measure both short- and long- term effects from cosmic rays, see interactions of previously known image artifacts with starlight, and uncover several unexpected systematics that affect photometric precision. Based on these results, we expect to attain Kepler's planned photometric precision over 90% of the field of view.

CCD↗

Pixel-Level Calibration in the Kepler Science Operations Center Pipeline

We present an overview of the pixel-level calibration of flight data from the Kepler Mission performed within the Kepler Science Operations Center Science Processing Pipeline. This article describes the calibration (CAL) module, which operates on original spacecraft data to remove instrument effects and other artifacts that pollute the data. Traditional CCD data reduction is performed (removal of instrument/detector effects such as bias and dark current), in addition to pixel-level calibration (correcting for cosmic rays and variations in pixel sensitivity), Kepler-specific corrections (removing smear signals which result from the lack of a shutter on the photometer and correcting for distortions induced by the readout electronics), and additional operations that are needed due to the complexity and large volume of flight data. CAL operates on long (~30 min) and short (~1 min) sampled data, as well as full-frame images, and produces calibrated pixel flux time series, uncertainties, and other metrics that are used in subsequent Pipeline modules. The raw and calibrated data are also archived in the Multi-mission Archive at Space Telescope at the Space Telescope Science Institute for use by the astronomical community.

Calibration↗

Data Validation in the Kepler Science Operations Center Pipeline

We present an overview of the Data Validation (DV) software component and its context within the Kepler ScienceOperations Center (SOC) pipeline and overall Kepler Science mission. The SOC pipeline performs a transiting planetsearch on the corrected light curves for over 150,000 targets across the focal plane array. We discuss the DV strategy forautomated validation of Threshold Crossing Events (TCEs) generated in the transiting planet search. For each TCE, atransiting planet model is fitted to the target light curve. A multiple planet search is conducted by repeating the transitingplanet search on the residual light curve after the model flux has been removed; if an additional detection occurs, aplanet model is fitted to the new TCE. A suite of automated tests are performed after all planet candidates have beenidentified. We describe a centroid motion test to determine the significance of the motion of the target photocenterduring transit and to estimate the coordinates of the transit source within the photometric aperture; a series of eclipsingbinary discrimination tests on the parameters of the planet model fits to all transits and the sequences of odd and eventransits; and a statistical bootstrap to assess the likelihood that the TCE would have been generated purely by chancegiven the target light curve with all transits removed.

photometry↗

Semi-Weekly Monitoring of the Performance and Attitude of Kepler Using a Sparse Set of Targets

The Kepler spacecraft is in a heliocentric Earth-trailing orbit, continuously observing ~160,000 select stars over ~115 square degrees of sky using its photometer containing 42 highly sensitive CCDs. The science data from these stars, consisting of ~6 million pixels at 29.4-minute intervals, is downlinked only every ~30 days. Additional low-rate Xband communications contacts are conducted with the spacecraft twice a week to downlink a small subset of the science data. This paper describes how we assess and monitor the performance of the photometer and the pointing stability of the spacecraft using such a sparse data set.

Attitude reconstruction↗

Upping the Ante: The TESS Mission Shortens Full Frame Images to 10 Minutes and Introduces a Twenty-Second Data Collection Mode

The Transiting Exoplanet Survey Satellite (TESS) recently completed its initial two-year, near all-sky survey, identifying over 79 exoplanets and over 2000 exoplanet candidates. The mission is well on its way to find at least 50 small, nearby exoplanets for which masses can be ascertained and whose atmospheres can be characterized by ground- and space-based follow-on observations. TESS has unveiled a plethora of exciting non-exoplanet astrophysics results, such as asteroseismology, asteroids, and supernova. In the extended mission, TESS is collecting full frame images (FFIs) at 10-minute intervals rather than at 30-minute intervals, as was the case for the two-year primary mission. TESS is also collecting and providing photometry for up to 1000 20-sec targets in addition to the 20,000 target star postage stamps collected at 2-min intervals. The extended mission will also feature a five-month interval in which the 24°x96° field of view (FOV) will be rotated by 90°from its normal North-South orientation to observe a swath of the ecliptic plane. The FOVs for the remainder of the extended mission will be offset in latitude from those of the prime mission to help fill in the gaps in the full sky coverage. We discuss the performance and behavior of the data products generated by the TESS Science Processing Operations Center (SPOC) at NASA Ames Research Center and highlight the new 20-sec data mode and the 10-min FFIs. The TESS Mission is funded by NASA's Science Mission Directorate as an Astrophysics Explorer Mission.

TESS↗

TESS Science Processing Operations Center Pipeline Status and Updates

The past eighteen months have seen a number of important changes for the TESS Science Processing Operations Center (SPOC) and our archival data products as TESS embarked upon its first extended mission. First, the SPOC developed and deployed a new 20-sec cadence pipeline, promising to unveil exciting new astrophysics at these short timescales for up to 1000 targets per observing sector. We also developed an FFI light curve pipeline that creates light curves and associated data products for up to 160,000 targets in each sector and archive these as High-Level Science Products (HLSP) at the Mikulski Archive for Space Telescopes (MAST). Soon we plan to perform transiting planet searches on these light curves and to release Data Validation reports and associated data products to the MAST. We also present results from the first multi-year transiting planet search of sectors 1 through 36. Finally, we discuss major changes to the SPOC pipeline that motivated the reprocessing of the first year of data, including the application of target-and cadence-specific scattered light flags, and an update to the sky background correction algorithm to mitigate bias in the original algorithm for dim and/or severely crowded stars.

TESS↗

Towards A Better Measurement of eta-Earth and Beyond Via Modernizing the Kepler Pipeline: An Update

The measurement of the occurrence of rocky habitable-zone planets orbiting Sun-like stars (eta-Earth), is a fundamental quantity for guiding our search for habitable exoplanets. Despite being launched 15 years ago, NASA’s Kepler mission remains responsible for finding the majority of all known exoplanet candidates relevant to eta-Earth, ushering in a new era of exoplanet demographics studies and continuing to drive planet occurrence rate calculations. However, the paucity of detections of likely rocky planets in the habitable zones of their host stars remains a limiting factor for estimating eta-Earth. We describe our five-year project for modernizing the Kepler planet detection and vetting pipeline in order to produce a more complete and reliable exoplanet catalog, which will lead to more accurate and precise measurements of eta-Earth. First, we are currently porting the original Kepler pipeline code from MATLAB to Python. We will then describe new stellar catalogs based on Gaia and ground-based imaging data, and ways to improve the pipeline detection and vetting algorithms. We will provide an update on the current state of this work. When completed, we will use this new pipeline and catalog to calculate updated estimates of eta-Earth. The full, updated pipeline code in Python, as well as all our inputs and results, will be made available to the public for detailed exoplanet occurrence-rate and demographics studies.

kepler↗