The Lanthanide Fraction Distribution in r-process Metal-Poor Stars by Alexander Ji

Nov
08
2019

Event Location
Online seminar via zoom

Event Audience
Graduate Students
Postdocs
Scientists
Undergraduate Students

Event Hosted By
JINA-CEE

Seminar Recording

Seminar Recording

https://youtu.be/0oz3zWboVEc


Event Contact

Alexander Ji. Carnegie Science Observatories

The lanthanide fraction distribution in r-process metal-poor stars

 

Abstract:

Multimessenger observations of the neutron star merger GW170817 and its kilonova proved that neutron star mergers can synthesize large quantities of r-process elements. If neutron star mergers in fact dominate all r-process element production, then the distribution of kilonova ejecta compositions should match the distribution of r-process abundance patterns observed in stars. The lanthanide fraction (XLa) is a measurable quantity in both kilonovae and metal-poor stars, but it has not previously been explicitly calculated for stars.  Here, we compute the lanthanide fraction distribution of metal-poor stars ([Fe/H] < -2.5) to enable comparison to current and future kilonovae. The full distribution peaks at log XLa ~ -1.8, but r-process-enhanced stars ([Eu/Fe] > 0.7) have distinctly higher lanthanide fractions; log XLa > -1.5. We review observations of GW170817 and find general consensus that the total log XLa = -2.2 +/- 0.5, somewhat lower than the typical metal-poor star and inconsistent with the most highly r-enhanced stars. For neutron star mergers to remain viable as the dominant r-process site, future kilonova observations should be preferentially lanthanide-rich (including a population of ~10% with log XLa > -1.5). These high-XLa kilonovae may be fainter and more rapidly evolving than GW170817, posing a challenge for discovery and follow-up observations. Both optical and (mid-)infrared observations will be required to robustly constrain kilonova lanthanide fractions.  If such high-XLa kilonovae are not found in the next few years, that likely implies that the stars with the highest r-process enhancements have a different origin for their r-process elements.

 

https://ui.adsabs.harvard.edu/abs/2019ApJ...882...40J/abstract