Extracting Periodic Transit Signals from Noisy Light Curves using Fourier Series
Samsing et al
We present a simple and powerful method for extracting a transit signal from noisy light curves. Assuming the signal is periodic, we illustrate that systematic noise can be removed in Fourier space at all frequencies, by only using data from inside a time window which is matched to the main planet transits. This results in a reconstruction of the signal which on average is unbiased, despite that no prior knowledge of either the noise or the transit signal itself is used in the analysis. The method has therefore clear advantages over standard phase folding, which normally requires external input such as nearby stars or noise models for removing systematic components. In addition, we extract the full 360 degree transit signal simultaneously, and Kepler like data can be analyzed in just a few seconds. We illustrate the performance of our method by applying it to a dataset composed of light curves from Kepler with a fake injected signal emulating a planet with rings. For extracting periodic transit signals, our presented method is in general the optimal and least biased estimator and could therefore lead the way towards the first detections of, e.g., planet rings and exo-trojan asteroids.