Speaker
Description
We outline the current status of the systems we are designing to detect and characterise exoplanet candidates with PLATO lightcurve data in the early stages of processing (transitPipe). The results of transitPipe comprise a list of vetted and graded exoplanet candidates which will be shared with the community, and passed on to analysis at the next stage (planetPipe). Our process includes robust strategies for filtering stellar variability, and a new fast detection algorithm for the transit signals. The new detection code (CETRA: Cambridge Exoplanet Transit Recovery Algorithm) separates the task into a linear transit search followed by a phase-folding of the former into a periodic signal search, using a physically motivated transit model to improve detection sensitivity. Implemented with NVIDIA’s CUDA platform (for GPUs), it outperforms traditional methods like Box Least Squares and Transit Least Squares in both sensitivity and speed. We also summarise the vetting and grading processes to be applied to all candidates, and show how the PLATO multi-camera data gives us extra leverage for the identification of false positive signals for blended systems.
| Affiliation of the submitter | Institute of Astronomy, University of Cambridge |
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| Attendance | in-person |
