OverSampling Mode

1. OverSampling Mode C. Quentin, R. Cautain, C. Surace, R. Savalle, J-C. Meunier CSC 05/04/2006

2. Scientific interest for oversampling • To better reconstruct the shape of the transits: • Limb darkening (atmospheres) • Asymmetry of the transit shape (rings, moons, …) • To help identify secondary transits (eclipsing binaries) • To get a better estimate of the phase and the timing of the transits (systems of planets) • By products: • Weaker instrumental noises (no piling up on board) • Additional possibilities of data corrections (« glitches », etc..) CSC 05/04/2006

3. OSM – General Overview 12000 Light Curves N1 data (8.5mn) Initial list of targets Priority Management Conf(i), Likelihood(i), Scien(i), tend(i) Detection, Estimation and Sorting Procedures List of new candidates Conf(i) Sorted List of targets Scientific Oversamp. Staff Discrimination (Planet/EB) Likelihood(i) Oversampling List CMC

4. The main objectives - To identify transit events with a high confidence level or/and a confirmed periodicity. - To discriminate, in the case of periodic events, possible planetary transits from eclipsing binaries. - To sorttransit candidates as a function of the confidence level and the likelihood index. - To checkthe scientific interest of the sorting, in the case of peculiar events (Scientific Oversampling Staff). - To draw up the list of the targets to be oversampled (CoRoTID). The frequency of all these operations is once a week. (short delay to process ~12000 LCs) CSC 05/04/2006

5. The various steps of the OSM • Preprocessing • To filter residuals of the SAA • To remove disturbing low frequencies of Stellar Variability • To filter (possible) orbital perturbations • Detection of transit candidates • Two complementary algorithms running in parallel • Estimate of a confidence level for each detection • Discrimination • Use of simple procedures to identify most striking ambiguities • Estimate of a likelihood index • Sorting and list management CSC 05/04/2006

6. 1. Preprocessing Goals : (a) To reduce the level of instrumental noise (b) To remove the most disturbing frequencies (at low frequency) Possible Methods: • Based on individual target • Based on collective analysis (multiplex approach  PCA, SysRem, …) Developed Procedures (individual targets): • Moving Box • Low Filter (fft) • Filtering_saa (?) • Gauging Filter CSC 05/04/2006

7. 2. Detection Goal : To identify transit like events in the Light-curves and to estimate a confidence level. Methods: • Based on the search of individual shape (transit like event) • Based on the search of periodic features Developed algorithms : • MID (Morph. Individual Detector) + EPF (Event Periodicity Finder) • BLS (Box fitting Least Square) Other algorithms: • … … CSC 05/04/2006

8. Simulated Light-Curves • Blindtest1: 1000 Light-Curves in white color with 20 planetary transits + 16 other astronomical signals (sampling 512s). Used to test the complete chain and the list sorting. • ABAC: 850 Light-Curves for a G type star of magnitude 14, with 3 level of stellar activity. Used to calibrate the detection algorithms. • Blindtest2: 236 colored Light-curves with periodic signals (either planetary transits or eclipsing binaries). Used to test the discrimination capacities. (transits simulated by C. Moutou) CSC 05/04/2006

9. 3. Discrimination Goal : To identify in the list of candidates the most striking ambiguities and estimate a likelihood index. Possible Methods: • Identification of secondary transits at ½ period (EBs) • Events are incompatible in the three « colors » • To reconstruct the transit shape • To use the knowledge of Exodat Developed procedure (the simplest one): • BinTest: identification of secondary transits  EBs To fold the signal after a phase shift of a ½ period and compare with the folding without shift. CSC 05/04/2006

10. 4. Sorting and list management Goal : To draw up a list of targets that merit to be oversampled. The list must be sorted following: • a confidence level in the detections • a likelihood index that the candidate be a planet • a number of scientific priorities … Procedure to be developed : • Management of the lists issued from the previous steps. CSC 05/04/2006

11. Sketch of the OSM procedures 1. Preprocessing Corot_ID, Raw_lightcurve Moving Box Norbit=10 Low Filter Tcut=1.5 jd Gauging Filter Nech=6, dff=5E-3 Corot_ID, Filter_lightcurve Corot_ID List{TransitEvent} [date, duration, deltaF, surface], SNRE 2. Detection MID (maille)  SNRE BLS (Nharm,Pmin,Pmax,DT)  SDE BD Alarm Corot_ID, WinID… Corot_ID, List{ObjetPeriodique}[Objet_periodique, type, Liste{ObjetTransit}, VR EPF , WPDM  VR Corot_ID Objet_Periodique[period, phase, deltaF, duration],SDE 3. Discrimination Bin-Test  type List{Corot_ID} SDE > (SDE)o 4. Sorting List{Corot_ID} SNRE > (SRE)o Merging (SDE)o, (SNRE)o, (VR)o List{Corot_ID} VR > (VR)o CSC 05/04/2006

12. Current status and prospect The proposed methods: • Are ready to be implemented in an operational chain • MID + PEF is well suited for weak transit numbers • Standard BLS is well suited for large transit numbers Oversampling data base: • Constructed to store and manage the versions of the various software, lists of candidates and targets Possible Improvements during the preprocessing stage: • Filtering likely will change when using true data. • Removal of instrumental noise will possibly benefit of using collective information as for example with PCA or SysRem. CSC 05/04/2006