Poster Abstracts - Kepler - NASA

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POSTER ABSTRACTSP0132. POSTER SESSION IWavelet-Based Band Splitting for Improved Systematic Error Correction and NoiseReduction in Kepler Light CurvesMartin C. Stumpe 1,* , T. Barclay 2 , M. N. Fanelli 2 , J. M. Jenkins 1 , J. Kolodziejczak 3 , R. Morris 1 , Jeffrey C. Smith 1 , J.Twicken 1 , J. Van Cleve 1 . 1 SETI Institute/NASA Ames Research Center, MS 244-30, Moffett Field, CA 94035,USA,2 Bay Area Environmental Research Institute,3 NASA Marshall Space Flight Center.* martin.stumpe@nasa.govKepler photometric data contain significant systematicand stochastic errors as they come from the KeplerSpacecraft. The main cause for the systematic errorsare changes in the focus of the photometer due tointrinsic and extrinsic thermal changes in theinstrument, and also residual spacecraft pointingerrors. It is the main purpose of the Presearch-Data-Conditioning (PDC) module of the Kepler Scienceprocessing pipeline to remove these systematic errorsfrom the light curves. While PDC has recently seen adramatic performance improvement by means of aBayesian approach to systematic error correction (seecompanion poster by J. C. Smith et al.) and improveddiscontinuity correction (see poster by R. L. Morris etal.), there is still room for improvement.effect to removing the trends, co-trending with thesebasis vectors can then also mistakenly introduce thesesmall scale features into the light curves.A solution to this problem is to perform a separation ofscales, such that small scale features and lowfrequency trends are described by different basisvectors. We present our investigation of a waveletbasedband splitting approach to separate small scalefrom large scale features in the light curves. The PDCBayesian co-trending can then be performed on eachband individually, such that low frequency trends andhigh frequency features will be contained inindependent basis vectors (see Figure 2).One problem of the current (Kepler 8.0)implementation of PDC is that injection of highfrequency noise can be observed in a few cases (seeFigure 1). Although this high frequency noise does notnegatively impact the general co-trending, an increasednoise level can make detection of planet transits orother astrophysical signals more difficult.Figure 2: Band splitting of the light curves leads to adecomposition of small scale and large scale features.Aside from eliminating the problems of noise andsmall scale feature injection, this wavelet-based scaledecomposition will also allow an investigation ofcharacteristic scales and amplitudes of systematicerrors, which may lead to further improvements in thesystematic error correction.Figure 1: Injection of high frequency noise into correctedlight curves. While the co-trending itself is very good(upper panel), the MAP fit (red curve) has a higher noiselevel than the Normalized Flux (blue curve).Funding for this work is provided by the NASAScience Mission Directorate.The origin of this noise-injection is that high frequencycomponents of light curves sometimes get includedinto co-trending basis vectors characterizing long termtrends. Similarly, small scale features like edges cansometimes get included in basis vectors whichotherwise describe low frequency trends. As a side1422011 Kepler Science Conference - NASA Ames Research Center
POSTER ABSTRACTSP0133. POSTER SESSION IKepler: An Astrometric Mission to Detect Giant Planets and Brown Dwarfs around Nearby Stars? A. M.Tanner 1 and D. Monet 2 ,1 Mississippi State University, 235 Hilbun Hall, MSU, MS 39762, angelle.tanner@gmail.com,2 USNO, dgm@nofs.navy.mil–12–Introduction: While the primary science goal forthe Kepler mission is the characterization of terrestrialand giant exoplanets through ultra-precise photometry,the telescope is capable of collecting astrometric dataat 0.001 pixel precision or better (see Figure 1). Thesedata have been used to rule out false positives due toblends with eclipsing binaries and could be used toderive trigonometric parallaxes and proper motions, aswell as search for 10-40 Jupiter-mass companionsaround a subset of high priority Kepler targets (seeFigure 2). Alas, precise Kepler astrometry remains anelusive goal. The astrometric accuracy is compromisedby as yet un-modeled "wiggles" (i.e., slow drifts in thestellar positions). Many numerical experiments havebeen devoted to understanding these apparent motions,but a predictive model has yet to be found. These motionsare at the level of 0.01 pixel and preclude Fig. 1.— the Astrometric error as a function of Kp magnitude for stars on Channel 2measurement of proper motion, parallax, and perturba-Figure 1: Plot of initial estimates of the as-tions. The current status of efforts to model Quarter these drifts 1 data collection. trometric errors from 30 minute (LC) obser-will be reviewed as well as the full impact of the sciencethat will be gained from this unique data set.References:[1] Monet, D. et al. (2010) arXiv:1001.0305vations as a function of Kepler magnitude 1 .There is a substantial portion of the Keplercatalog that achieves mili-arcsecond precisionor better sufficient to detect browndwarf and low mass companions to manyKepler targets and Jupiter-mass companionfor the closest members.1000800Number60040020000 1 2 3 4Astrometric Amplitude - masFig. 2.— Astrometric residuals from a blended variable (top) and a non-variable sttom) taken from a solution for a single channel. Red symbols are from the columns aFigure 2: Histogram of the astrometric amplitudesymbols are from the rows.of 10 M J (dashed) and 40 M J (solid) companionsin a 3.5 year orbit around the ~1000 Kepler targetswith planetary transit candidates (Borucki etal. 2011). Also plotted (dash-dot) is the 0.2 masastrometric detection limit that results from assuminga S/N of 5, single measurement precisionof 4 mas and 22k observations over the lifetime ofthe mission.2011 Kepler Science Conference - NASA Ames Research Center 143
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Poster Abstracts - Kepler - NASA

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