Extracting asteroid physical properties from Vera C. Rubin Observatory science validation survey data: Rotational periods, colors, and taxonomies

Carruba V.; Greenstreet S.; Mastropietro M.; Aljbaae S.; Caritá G.; Domingos R.C.; Huaman M.; Bala M.M.; Pedroso R.D.Z.; Delfino E.M.D.S. · Planetary and Space Science (2026) · DOI: 10.1016/j.pss.2026.106350

Resumen

The Vera C. Rubin Observatory will enable large-scale characterization of minor bodies through high-cadence, multi-band photometry. Early Science Validation (SV) observations from 2025–2026 provide one of the first extensive datasets for Solar System studies, but typically with sparser and more heterogeneous coverage than the Rubin First Look data, where hundreds of observations were available for well-characterized objects.In this work, we build on the methodology developed for the Rubin First Look data to extract asteroid rotation periods, amplitudes, colors, and taxonomic classifications from early Rubin SV data using multi-band ((Formula presented) ) photometry. Rotation periods are determined through a combination of high-order Fourier light-curve fitting and multi-band Lomb–Scargle analysis. A unified light-curve model is then used to derive rotation-corrected colors, which are converted into taxonomic classes using calibrated color indices and spectral slopes.We validate the method on objects with sufficient observational coverage and show that preliminary physical properties can be estimated from sparse and irregular datasets, while robust determinations require improved temporal coverage. By simulating sparsely observed data, we identify the observational conditions required for period determinations. The inclusion of z[jls-end-space/]-band photometry extends traditional color-based taxonomy and improves compositional discrimination relative to (Formula presented) -only analyses.The proposed framework combines automated period-search procedures with expert visual quality assessment of candidate solutions and is designed for application to future Rubin data releases, providing a baseline for the systematic extraction of asteroid physical properties, while validation at full survey scale will require larger and more diverse datasets.

Instituciones: Universidad Tecnológica del Perú