Mathematics – Probability
Scientific paper
Jan 2012
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012aas...21941403b&link_type=abstract
American Astronomical Society, AAS Meeting #219, #414.03
Mathematics
Probability
Scientific paper
The Kepler mission finds exoplanets by detecting planetary transit signals using various centroiding methods that identify false positives due to background eclipsing binaries. One robust, high precision method fits the Kepler PSF to both the out-of-transit target star pixels and the difference between out-of and in-transit pixels. This difference image directly provides the location of the transit signal. The difference between these fits provides a high precision estimate of the offset between the transit signal location and the target star. A large offset implies a BGEB. This method is subject to various biases which complicate its interpretation. These biases change every 3 months because the Kepler spacecraft rolls, placing stars on different pixels. We describe several methods to control these biases through modeling, multi-quarter fitting and robust weighted averaging. These methods achieve uncertainties of less than an arcsec, compared with the prior minimum uncertainty of 2 arcsec (Kepler pixels are 3.98 arcsec on a side). The remaining residual biases are observed to have a nearly Gaussian distribution. These residual biases are combined with modeled observation biases to create observed and expected probability distributions for the transit signal, assuming that the transit is on a particular star. We use these distributions to calculate a relative probability that an observed transit is due to a transit on a specified star. This probability is an important step towards computing an absolute probability that a transit is on the observed target star.
Funding for this mission provided by NASA's Discovery Program Office, SMD.
Bryson Steve
Fressin François
Gilliland Ron L.
Jenkins Jon Michael
Kepler Science Team
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