Oversampling mode

1
Oversampling mode
Roi Alonso , Pierre-Yves Chabaud Christian
Surace, Raphael Cautain, P. Barge
2
Planned procedures

• Inputs
• N1 data from the LESIA pipeline
• Scientific criteria
• Additional programs
• Specific algorithms in various steps
• Output
• List of targets (XML files) ? SEF/CMC

3
The various steps

• Preprocessing of the data
• To filter residuals of the SAA and orbital
  perturbations
• To remove disturbing low frequencies of Stellar
  Variability
• (moving box, Fourier wavelets,
  multiplex-PCA)
• Detection of possible transits
• Two complementary algorithms running in parallel
• MID (Morphological Detector) EPF (Periodicity
  Finder)
• BLS (Box fitting Least Square)
• Estimate of a confidence level for each detected
  event
• Discrimination/priority
• Building a common list of detected events
• Use simple tools to remove ambiguities (SOS)
• Management of the lists
• EXOP/AP

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Merging of the detection lists
Filtered LCs
MID
BLS
MIDEPF
List with P and E of best detections
List with P and E of best detections
List with Epoch of best detections
Trapezoidal fitting of the phase-folded
LC Period P and Epoch E
Single list of outputs Sorting - no repetitions
Input for the discrimination tools
5
Priority removing ambiguites

• To discriminate planetary transits from
• Eclipsing Binaries, variable stars, false
  detections (noisy features)
• Identification of EB ligth curve
• Search for secondary transits in the signal
  folded at 1xPeriod around epoch 0.5
• Looking at differences (depth position) between
  even and odd eclipses in the signal folded at
  2xPeriod around epoch
• Search for out of eclipse modulations (peak in
  the spectrum)
• Use of colours (trapezoidal fitting in each
  channel)
• ? Reduced list of candidates
• (sorted by increasing order of the sum of 4
  significances)
• ? Exoplanet candidates for oversampling
• (ordered in priority after visual
  inspection - SOS)

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Exo - Transit Detection
Exo - Detection list
Tools Discrimination/Priority
EXODAT
Exo - Sorted list
Visual Inspection - SOS
Combine lists
Exo - Candidate list (core)
Exo - Initial list (core)
Exo-CCD list
AP-targets list
Exo-CCD - XML file
AP - Variability analysis
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How things are presently working

• Inputs
• Raw N0 data instead of N1
• (N1 only available since 1 month)
• Raw data are put in the N1 format
• Algorithms
• Automated procedures not at work
• LC analysis made using visual inspection
• Management of the oversampling lists
• Variability analysis by the AP at work
• Output
• List of targets (XML files) ? SEF/CMC (OK)

8
Results from the alarm mode

• Two alarm candidates during IRa01
• One confirmed planet
• No alarm candidates during SRc01 (no available
  data)
• 19 alarm candidates during LRc01
• Intense Follow Up effort during the summer
• 2 confirmed planets
• 5 eclipsing binaries
• FU observations are still going on
• Only the most obvious candidates were detected
• The alarm pipeline must be improved !

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Information released for FU operations

• The lists of  alarms  are accessible to the
  Science Team only for the purpose of Follow Up
  operations
• (periods, depths and durations of the events
  the contaminating background stars)
• The coordinates of the targets are accessible
  only to the members of the FU coordination group
• (leaders of the FU working groups some
  experts)

10
Encountered difficulties

• Due to the production of the N1 data
• Long delay in the data delivery (up to 1 month)
• Some gaps introduced in the N1 products
• Non homogeneous level of the corrections
• Pipeline corrections introduced in the data
• Reversed or negative  hot  pixels
• Some additional discontinuities
• Hot pixels
• Detection and modeling (L. Jorda R. Cautain) -gt
  corrections
• Filtering using wavelet transform (R. Alonso)

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Incomplete corrections and mirroring of hot
pixels
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Discontinuities introduced in the N1 data
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Necessary evolution

• ? To be effective the alarm software needs
• Regular delivery of data all along the run
• Data corrected in an homogenous way (continuity
  of the corrections)
• A possibility is to produce data specifically
  processed for the alarm mode
• (only simple corrections performed on the raw
  data in a regular and continuous way)
• This possibility is under
  study