Open AccessCorrecting systematic effects in a large set of photometric light curves
Author(s) -
Tamuz O.,
Mazeh T.,
Zucker S.
Publication year - 2005
Publication title -
monthly notices of the royal astronomical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.058
H-Index - 383
eISSN - 1365-2966
pISSN - 0035-8711
DOI - 10.1111/j.1365-2966.2004.08585.x
Subject(s) - physics , principal component analysis , detector , set (abstract data type) , extinction (optical mineralogy) , algorithm , point (geometry) , stars , function (biology) , rank (graph theory) , chemometrics , systematic error , astrophysics , statistics , optics , computer science , mathematics , machine learning , combinatorics , geometry , evolutionary biology , biology , programming language
We suggest a new algorithm to remove systematic effects in a large set of light curves obtained by a photometric survey. The algorithm can remove systematic effects, such as those associated with atmospheric extinction, detector efficiency, or point spread function changes over the detector. The algorithm works without any prior knowledge of the effects, as long as they linearly appear in many stars of the sample. The approach, which was originally developed to remove atmospheric extinction effects, is based on a lower rank approximation of matrices, an approach which has already been suggested and used in chemometrics, for example. The proposed algorithm is especially useful in cases where the uncertainties of the measurements are unequal. For equal uncertainties, the algorithm reduces to the Principal Component Analysis (PCA) algorithm. We present a simulation to demonstrate the effectiveness of the proposed algorithm and we point out its potential, in the search for transit candidates in particular.