Assessing the Impact of High-resolution Imaging on Statistical Validation of TESS Planet Candidates

High-resolution imaging is widely used to constrain false positive scenarios in exoplanet validation, but it is a finite follow-up resource that reaches only a subset of candidates, and its population-level impact on validation outcomes has not been quantified through controlled removal experiments. Using an automated pipeline built on TRICERATOPS, we compute the false positive probability (FPP) of 443 TESS planet candidates. For the 264 planet candidates with high-resolution imaging observations, we compute FPP with and without the corresponding contrast curves, allowing us to quantify the impact of the additional data. We find that 72% of 68 contrast-curve-bearing validated planets would fail validation without their adopted contrast curves. The fraction requiring imaging decreases with increasing planet size, from 100% below 1.7 R⊕ to 33% above 4 R⊕: within our sample and TRICERATOPS-based analysis, the availability of high-resolution imaging directly limits the yield of small-planet validation and the supply of validated targets for atmospheric characterization. Our analysis statistically validates 64 new TESS planets with sizes spanning 0.94 to 7.83 R⊕ across hosts of spectral types: M through F. Four of these are highly amenable to JWST observations based on the transmission and emission spectroscopy metrics, and each achieves validation only with its imaging constraint.