One of the obstacles in the search for exoplanets via transits is the large number of candidates that must be followed up, few of which ultimately prove to be exoplanets. Any method that could make this process more efficient by somehow identifying the best candidates and eliminating the worst would therefore be very useful. Seager and Mallen-Ornelas (2003) demonstrated that it was possible to discern between blends and exoplanets using only the photometric characteristics of the transits. However, these techniques are critically dependent on the shape of the transit, characterization of which requires very high precision photometry of a sort that is atypical for candidates identified from transit searches. We present a method relying only on transit duration, depth, and period, which require much less precise photometry to determine accurately. The numerical tool we derive, the exoplanet diagnostic eta, is intended to identify the subset of candidates from a transit search that is most likely to contain exoplanets, and thus most worthy of subsequent follow-up studies. The effectiveness of the diagnostic is demonstrated with its success in separating modeled exoplanetary transits and interlopers, and by applying it to actual OGLE transit candidates.
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