Half-Lives for R-Process Nucleosynthesis Using the ANN Statistical Global Model

Costiris, N.J. 1, Mavrommatis, E. 1, Gernoth, K.A. 2, Clark, J.W. 3
Institutes:
[1] University of Athens, Physics Department, Section of Nuclear & Particle Physics, 15771, Athens
[2] School of Physics & Astronomy, Schuster Building, The University of Manchester, M13 9PL, Manchester
[3] McDonnell Center for the Space Sciences & Department of Physics, Washington University, 63130, St. Louis, Missouri

Abstract

There still remain significant uncertainties in the nuclear physics input to the modeling of astrophysical nucleosynthesis via the r-process, notably involving the beta-decay half-lives of neutron-rich nuclei. Since the vast majority of the nuclides which lie on the r-process path will not be experimentally accessible in the foreseeable future, it is important to provide accurate beta-decay half-lives predictions by reliable models. In this work we apply our recently developed multilayered feed-forward Artificial Neural Network (ANN) statistical global model [1] of the beta-decay half-life systematics to nuclei that are relevant to r-process. We present results for nuclides situated on the r-ladders N=50, 82 and 126 where abundances peak, as well as for others that affect abundances between peaks. We also give the values of half-lives of interesting neutron-rich nuclides that have been recently measured or will be measured at developing rare-isotope experimental facilities. Comparison of our results with those available from conventional models and from experiment is very promising.

References
[1] N. J. Costiris, E. Mavrommatis, K. A. Gernoth, and J. W. Clark, Phys. Rev. C 80 (2009) 044332

Keywords:
r-process, nucleosynthesis, half-lives, beta-decay, statistical model

Submitted: 26 April 2010