The Back-in-time Void Finder: Dynamical identification of cosmic voids through optimal transport reconstruction

Abstract

Cosmic voids have increasingly emerged as a powerful cosmological probe. However, their large spatial extent and intrinsically underdense environments make their identification highly sensitive to shot noise, redshift-space distortions (RSDs), and observational systematics, particularly for topological and density-based void definitions. We introduce the ( ), a novel dynamical and physically motivated algorithm that identifies cosmic voids as regions of negative divergence of the Lagrangian displacement field reconstructed from the present-day tracer distribution. The reconstruction relies on an optimized discrete optimal transport algorithm that recovers the backward-in-time dynamics of tracers, naturally accounting for tracer bias without relying on cosmological assumptions. Using high-resolution N-body simulations, we validated against the widely used topological void finder . We show that it produces void catalogs with smoother and more physically motivated density profiles as well as abundances that are more stable under tracer subsampling and shot noise. We further applied to realistic DESI-like mock light-cone galaxy catalogs, demonstrating that it intrinsically mitigates redshift-space systematic effects and preserves real-space void size functions more faithfully than topological methods. Modeling RSD, the reconstruction can be combined with a fiducial cosmology and an assumed tracer bias within a bias-corrected Kaiser framework, yielding reconstructed-space void catalogs consistent with real-space statistics across redshifts. Its performance is characterized as a function of the main internal parameters, showing an optimal balance between accuracy, computational efficiency, and applicability to stage IV galaxy surveys. will be publicly released within the . Back-In-Time Void Finder BitVF BitVF REVOLVER BitVF BitVF CosmoBolognaLib