Ground and excited states Gamow-Teller strength distributions of iron isotopes and associated capture rates for core-collapse simulations
Jameel-Un Nabi

TL;DR
This paper presents detailed microscopic calculations of Gamow-Teller strength distributions and electron/positron capture rates for iron isotopes, crucial for modeling core-collapse supernovae, using an advanced pn-QRPA approach that incorporates experimental deformation data.
Contribution
It introduces a comprehensive pn-QRPA-based method for calculating stellar capture rates of iron isotopes, including nuclear deformation effects, improving reliability over previous models.
Findings
Calculated electron capture rates align well with shell model results.
Electron capture rates on $^{54}$Fe are about three times higher than shell model estimates.
Positron capture rates are significantly suppressed, by two to five orders of magnitude.
Abstract
This paper reports on the microscopic calculation of ground and excited states Gamow-Teller (GT) strength distributions, both in the electron capture and electron decay direction, for Fe. The associated electron and positron capture rates for these isotopes of iron are also calculated in stellar matter. These calculations were recently introduced and this paper is a follow-up which discusses in detail the GT strength distributions and stellar capture rates of key iron isotopes. The calculations are performed within the framework of the proton-neutron quasiparticle random phase approximation (pn-QRPA) theory. The pn-QRPA theory allows a microscopic \textit{state-by-state} calculation of GT strength functions and stellar capture rates which greatly increases the reliability of the results. For the first time experimental deformation of nuclei are taken into account. In the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
