Matched filtering with non-Gaussian noise for planet transit detections

Abstract

We develop a method for planet detection in transit data, which is based on the Matched Filter technique, combined with the Gaussianization of the noise outliers. The method is based on Fourier transforms and is as fast as the existing methods for planet searches. The Gaussinized Matched Filter (GMF) method significantly outperforms the standard baseline methods in terms of the false positive rate, enabling planet detections at up to 30 % lower transit amplitudes. Moreover, the method extracts all the main planet transit parameters, amplitude, period, phase, and duration. By comparison to the state of the art Gaussian Process methods on both simulations and real data we show that all the transit parameters are determined with an optimal accuracy (no bias and minimum variance), meaning that the GMF method can be used both for the initial planet detection and the follow-up planet parameter analysis.

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Cited by in corpus (5)

• fBLS -- a fast-folding BLS algorithm
• Self-Calibrating the Look-Elsewhere Effect: Fast Evaluation of the Statistical Significance Using Peak Heights
• Statistical significance testing for mixed priors: a combined Bayesian and frequentist analysis
• An Independent Search for Small Long-period Planets in Kepler Data I: Detection Pipeline
• Exoplanet transit search at the detection limit: detection and false alarm vetting pipeline