Kepler Presearch Data Conditioning I – Architecture and Algorithms for Error Correction in Kepler Light Curves
Ames Research Center · Search for Extraterrestrial Intelligence · +3 more institutions
Abstract
Kepler provides light curves of 156,000 stars with unprecedented precision. However, the raw data as they come from the spacecraft contain significant sys-tematic and stochastic errors. These errors, which include discontinuities, sys-tematic trends, and outliers, obscure the astrophysical signals in the light curves. To correct these errors is the task of the Presearch Data Conditioning (PDC) module of the Kepler data analysis pipeline. The original version of PDC in Kepler did not meet the extremely high performance requirements for the de-tection of miniscule planet transits or highly accurate analysis of stellar activity and rotation. One particular deficiency was that astrophysical features were of-ten…
Citation impact
- FWCI
- 19.08
- Percentile
- 100%
- References
- 25
Authors
11- MCMartin C. StumpeCorresponding
Ames Research Center, Search for Extraterrestrial Intelligence
- JCJeffrey C. Smith
Ames Research Center, Search for Extraterrestrial Intelligence
- JEJeffrey E. Van Cleve
Ames Research Center, Search for Extraterrestrial Intelligence
- JDJoseph D. Twicken
Ames Research Center, Search for Extraterrestrial Intelligence
- TBThomas Barclay
Ames Research Center, Bay Area Environmental Research Institute
Topics & keywords
- Kepler
- Light curve
- Astronomy
- Computer science
- Algorithm
- Physics
- Planet