Nathan Findlay, Seshadri Nadathur

We present VERSUS, a publicly available, fast void-finding algorithm designed to identify spherical underdensities in the density field that can be accurately described by excursion set predictions of the void size function. We validate the algorithm against both a synthetic distribution of particles designed to trace a known input void population, and mock galaxy sample built from a $(2\ h^{-1}\text{Gpc})^3$ AbacusSummit simulation populated with a realistic galaxy-halo connection, including systematic effects designed to mimic real survey data. In all cases, VERSUS demonstrates excellent performance, achieving strong agreement with theoretical predictions for the void size function across the range $25 < R \,[\ h^{-1}\text{Mpc}] < 61$ without requiring any post-processing of the void catalogue. The code is user-friendly, modular, and readily applicable to observational survey data. Its computational efficiency further enables the use of simulation-based modelling approaches, facilitating robust and consistent cosmic void analyses with Stage-IV surveys.