^1,2Bo-Lun Huang, ³Zhen-Zhao Tao, ^1,2Tong-Jie Zhang
The Astrophysical Journal, 1006, 9
Open Access Link to Article [DOI: 10.3847/1538-4357/ae742c]
¹Institute for Frontiers in Astronomy and Astrophysics, Beijing Normal University, Beijing 102206, People’s Republic of China
²School of Physics and Astronomy, Beijing Normal University, Beijing 100875, People’s Republic of China
³College of Computer and Information Engineering, Dezhou University, Dezhou 253023, People’s Republic of China

We present a meteorite-calibrated Bayesian framework for searching archival abundance records for chemical technosignatures—operationally, compositional patterns better explained by an idealized “processed” template (endmember) than by the empirical distribution of natural rocks. We fit a multimodal natural-composition reference using 3493 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, parameterized by a Ca-normalized mixing fraction α. Strong support for the processed template is uncommon: in the atmospheric 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 π̃ = 0.011 (atm) and π̃ = 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 ≳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 multielement surveys and expanded template families.