A Data-Driven Model for $r$-Process Production Patterns

Abstract

Using the elemental abundances in 68 metal-poor (MP) stars, we present a data-driven model for $r$-process production patterns covering Sr to U. We show that essentially all the $r$-process patterns in those and other test stars can be adequately explained as mixtures of Patterns 1 and 2, which provides theoretical insights into the empirical categories of limited-$r$, $r$-I, and $r$-II stars. We carry out an extensive survey of the yield templates produced by parametric $r$-process calculations. We propose that Pattern 2 may be dominated by a single template and points to regularity in $r$-process production by a subset of neutron star mergers (NSMs), while Pattern 1 is the average superposition of multiple templates and reflects production by other NSMs and perhaps also some magneto-rotational supernovae. We raise possible systematic issues with abundance ratios for elements measured in different ionization states, and highlight the need for examining the Os, Ir, and Pt measurements for HD~122563, which is dominated by Pattern 1 with a prominent Pt peak in our model. If this result is confirmed, the meaning of the limited-$r$ category requires drastic revision. Further measurements of a wider range of $r$-process elements in a larger sample of MP stars are critical to test and improve our model.