Speaker: Filomena Nunes (Michigan State University)

Abstract:

Nuclear reactions are an essential probe for studying isotope structure and nuclear astrophysics. It is from nuclear reactions that we learn about where nuclei come from and how they are produced. Also, reaction experiments provide critical knowledge on how neutrons and protons organize themselves to form matter as we know it and matter at the limits of stability.

However until recently, models for nuclear reactions included no uncertainty quantification. In this presentation, I will review the Bayesian analysis efforts developed over the last 6 years in reaction theory, including not only uncertainty quantification but also steps toward experimental design. This presentation assumes no prior knowledge on Bayesian Statistics.

Some relevant references:
[1] C. Hebborn et al., J. Phys. G 50, 050601 (arXiv:2210.07293)

[2] G.B. King et al., Phys. Rev. Lett. 122, 232502 (2019)

[3] A. Lovell et al., J. Phys. G 48, 014001 (2020)

[4] M. Catacora-Rios et al., Phys. Rev. C 100, 064615 (2019)

[5] T. Whitehead et al., Phys. Rev. C 105, 054611 (2022)

[6] M. Catacora-Rios et al., Phys. Rev. C 108, 024601 (2023) (arXiv:2212.10698)

[7] M. Catacora-Rios et al., Phys. Rev. C 104, 064611 (2021)