62,63,68,69Zn γ-Decay Probabilities for Surrogate Constraint of Neutron Capture Cross Sections

ORAL

Abstract

The surrogate method is an indirect technique used to constrain cross sections of nuclear reactions inaccessible for direct measurement. This method uses an alternate reaction channel to populate a nucleus of interest, combining resulting experimental data with theory to constrain the (n,γ) cross section. Hauser-Feshbach calculations use statistical nuclear models of the desired and surrogate reactions to predict cross sections from nuclear level densities, optical model potentials, and γ-strength functions (γSF). Individual γ-decay probabilities are experimentally extracted and used to constrain γSF models and therefore the resulting n-capture cross sections. The surrogate and n-capture reaction channels each populate the excited nucleus with a different spin-parity distribution, necessitating sampling a variety of spin states to correct for this difference.

This work presents γ-decay probabilities around the relevant neutron separation energies for four Zn isotopes. Reactions measured are 64,70Zn(p,d) and 64,70Zn(p,t) as surrogates for 61,62,67,68Zn(n,γ). Experimental data was collected in 2021 at Texas A&M University with a 27-MeV proton beam and Hyperion, a particle-γ coincidence array utilizing in-beam γ-ray spectroscopy. This presentation will examine notable features of the extracted γ-decays and discuss possible implications for the neutron capture cross sections.

Presenters

  • Jes Koros

    University of Notre Dame

Authors

  • Jes Koros

    University of Notre Dame

  • Anna Simon

    University of Notre Dame

  • Philip Adsley

    Texas A&M University College Station, Texas A&M University, Cyclotron Institute at Texas A&M, Cyclotron Institute, Texas A&M

  • Orlando J Gomez

    University of Notre Dame

  • Jason T Harke

    Lawrence Livermore Natl Lab

  • Richard O Hughes

    Lawrence Livermore Natl Lab

  • Brett H Isselhardt

    Lawrence Livermore Natl Lab

  • Brenden Longfellow

    Lawrence Livermore Natl Lab, Lawrence Livermore National Laboratory

  • Miriam Matney

    University of Notre Dame

  • Lauren McIntosh

    Texas A&M University

  • Craig S Reingold

    Lawrence Livermore Natl Lab

  • Antti Saastamoinen

    Texas A&M University

  • Aaron Sun Tamashiro

    Lawrence Livermore Natl Lab

  • Barbara S Alan

    Lawrence Livermore Natl Lab, Lawrence Livermore National Laboratory