Datasets and scripts from the paper "Hide and Seek with Gaia. Detectability of Predicted Thin-Disc Metal-Rich RR Lyrae Binaries in Gaia DR3 and DR4."

This repository contains the scripts, data, and figures needed to reproduce the results and plots of Iorio et al. (2026), "Hide and Seek with Gaia: Detectability of Predicted Thin-Disc Metal-Rich RR Lyrae Binaries in Gaia DR3 and DR4". It includes: input data including binary formation model samples from Bobrick & Iorio et a.. (2024), RR Lyrae catalogues, and cross-matches with the Gaia DR3 non-single-star solutions; (data.zip) a modified version of the gaiamock package extended to handle variable stars, including heteroskedastic astrometric errors, variability-induced mover (VIM) effects, and chromatic astrometric shifts; (gaiamock_750ccd5.zip) mock Gaia astrometric simulations for assessing the detectability of of RR Lyrae stars assuming they are in binaries following the models in Bobrick & Iorio et al. (2024) (detectability.zip) a Bayesian Gaussian Process analysis inferring the binary fraction as a function of metallicity ([Fe/H]) from Gaia DR3 detection statistics (bayesian_analysis.zip) Jupyter notebooks reproducing all paper figures (plot.zip) A full computational environment is provided via a Pixi environment file for reproducibility (pixi.toml and environment.sh) Additional details are reported in the README.md and if the additional README.md included in the folders and sub-folders Disclaimer Data and scripts are only partially documented, in the READMEs and in the scripts themselves. If you have any questions, comments, or doubts about using or adapting the scripts, feel free to contact me at [e-mail] You are free to use or adapt the scripts for your own scientific work. Likewise, the figures may be used or adapted for presentations, dissemination, and manuscripts. If you make use of any of them, even in adapted form, we kindly ask you to cite this repository and the associated paper. Although all scripts and data have been carefully tested and are identical to those used to produce the results and figures in the paper, they are provided without warranty of any kind. We decline any responsibility for the possible presence of bugs or unintended behaviour.