Kepler Presearch Data Conditioning II - A Bayesian Approach to Systematic Error Correction
Ames Research Center · Search for Extraterrestrial Intelligence · +3 more institutions
Abstract
With the unprecedented photometric precision of the Kepler Spacecraft, significant systematic and stochastic errors on transit signal levels are observable in the Kepler photometric data. These errors, which include discontinuities, outliers, systematic trends and other instrumental signatures, obscure astrophysical signals. The Presearch Data Conditioning (PDC) module of the Kepler data analysis pipeline tries to remove these errors while preserving planet transits and other astrophysically interesting signals. The completely new noise and stellar variability regime observed in Kepler data poses a significant problem to standard cotrending methods such as SYSREM and TFA. Variable stars are often of particular…
Citation impact
- FWCI
- 34.66
- Percentile
- 100%
- References
- 28
Authors
11- JCJeffrey C. SmithCorresponding
Ames Research Center, Search for Extraterrestrial Intelligence
- MCMartin C. Stumpe
Ames Research Center, Search for Extraterrestrial Intelligence
- JEJeffrey E. Van Cleve
Ames Research Center, Search for Extraterrestrial Intelligence
- JMJon M. Jenkins
Ames Research Center, Search for Extraterrestrial Intelligence
- TBThomas Barclay
Ames Research Center, Bay Area Environmental Research Institute
Topics & keywords
- Outlier
- Bayesian probability
- Algorithm
- Physics
- Prior probability
- Range (aeronautics)
- Computer science
- Astrophysics