A Calibrated Bayesian Search for Potential Chemical Technosignatures in Polluted White Dwarf

We present a meteorite-calibrated Bayesian framework for searching archival abundance records for chemical technosignatures–operationally, compositional patterns better explained by an idealised “processed” template (endmember) than by the empirical distribution of natural rocks. We fit a multi-modal natural-composition reference using 3,493 whole-rock meteorite analyses, and for each of 697 star-paper abundance sets–spanning at least 397 distinct objects once Gaia-designated repeats are consolidated–we compare the Bayesian evidence for (i) natural material and (ii) a mixture of natural material with a fixed siderophile-enriched template, parameterised by a Ca-normalized mixing fraction alpha. Strong support for the processed template is uncommon: in the photospheric compilation (atm) 8/697 records have BF > 10 (4/697 have BF > 100), and in the diffusion-adjusted steady-state subset (acc ss; 148 records spanning at least 94 objects) 6/148 have BF > 10. We report the highest-evidence candidate records and infer the fraction of records detectably favoring the mixture model, with posterior medians pi-tilde = 0.011 (atm) and pi-tilde = 0.041 (acc ss). We calibrate the analysis with end-to-end injection-recovery experiments matched to each record’s coverage and censoring. The calibration shows that discrimination is driven mainly by chemical information, typically requires greater-than-or-similar-to 5 detected elements for decisive support, and–for the siderophile template–is strongest for exact five-element panels that include Fe, Mg, Cr, and Ti together with Ni, Si, or Na. These results constrain the detectable incidence of the tested processed-composition class in current data and set observational requirements for future multi-element surveys and expanded template families.