Presentation #102.247 in the session Poster Session.
Algorithmic planet validation using the transit signal has revolutionized the field of exoplanet detection in the past decade, leading to the confirmation of thousands of new exoplanets. Several open source packages exist to rapidly differentiate between true exoplanet signals and sources of false positive signals, such as stellar variability and nearby eclipsing binaries. We are now entering an era in which we have many hundreds of planets with transit timing variation (TTV) signals. While much effort has been put into disentangling a TTV signal assuming the cause is a multi-planet system, there is a need for methods to distinguish between perturbing planet, moon, and stellar variability caused TTV signals. Here, we show the first results of our work that will investigate how TTV properties like amplitude, frequency, and high order harmonics can be used to statistically rank competing physical TTV models. In particular, we present new results applying these methods to two high significance Kepler candidates that fall into a frequency range typically expected for exomoons. This work is part of a broader goal to ultimately create an open source package that goes beyond TTV parameter estimation to TTV model differentiation.