Searching for transits in the Wide Field Camera Transit Survey with difference-imaging light curves

The Wide Field Camera Transit Survey is a pioneer program aiming at for searching extra-solar planets in the near-infrared. The images from the survey are processed by a data reduction pipeline, which uses aperture photometry to construct the light curves. We produce an alternative set of light curves using the difference-imaging method for the most complete field in the survey and carry out a quantitative comparison between the photometric precision achieved with both methods. The results show that difference-photometry light curves present an important improvement for stars with J > 16. We report an implementation on the box-fitting transit detection algorithm, which performs a trapezoid-fit to the folded light curve, providing more accurate results than the box-fitting model. We describe and optimize a set of selection criteria to search for transit candidates, including the V-shape parameter calculated by our detection algorithm. The optimized selection criteria are applied to the aperture photometry and difference-imaging light curves, resulting in the automatic detection of the best 200 transit candidates from a sample of ~475 000 sources. We carry out a detailed analysis in the 18 best detections and classify them as transiting planet and eclipsing binary candidates. We present one planet candidate orbiting a late G-type star. No planet candidate around M-stars has been found, confirming the null detection hypothesis and upper limits on the occurrence rate of short-period giant planets around M-dwarfs presented in a prior study. We extend the search for transiting planets to stars with J ≤ 18, which enables us to set a stricter upper limit of 1.1%. Furthermore, we present the detection of five faint extremely-short period eclipsing binaries and three M-dwarf/M-dwarf binary candidates. The detections demonstrate the benefits of using the difference-imaging light curves, especially when going to fainter magnitudes.