Developing Nucleon Self-Energies to Generate the Ingredients for the Description of Nuclear Reactions (eBook)

Mack C. Atkinson (Autor)

eBook Download: PDF

2020 | 1st ed. 2020
XI, 143 Seiten
Springer International Publishing (Verlag)
978-3-030-53114-0 (ISBN)

Infos

This thesis develops the dispersive optical model into a tool that allows for the assessment of the validity of nuclear reaction models, thereby generating unambiguous removal probabilities of nucleons from valence orbits using the electron-induced proton knockout reaction. These removal probabilities document the substantial quantitative degree in which nuclei deviate from the independent-particle model description. Another outcome reported within is the prediction for the neutron distribution of Ca-40, Ca-48, and Pb-208. The neutron radii of these nuclei have direct relevance for the understanding of neutron stars and are currently the subject of delicate experiments. Unlike other approaches, the current method is consistent with all other relevant data and describes nuclei beyond the independent-particle model. Finally, a new interpretation of the saturation probabilities of infinite nuclear matter is proposed suggesting that the semi-empirical mass formula must be supplemented with a better extrapolation from nuclei to infinite matter.

Mack Atkinson is a postdoctoral researcher at TRIUMF, Canada. He received his PhD from Washington University in St. Louis in 2019.

Produkt-Details

• Erscheint lt. Verlag: 10.9.2020
• Reihe/Serie: Springer Theses
• Reihe/Serie: Springer Theses
• Zusatzinfo: XI, 143 p. 54 illus., 49 illus. in color.
• Sprache: englisch
• Themenwelt: Naturwissenschaften ► Physik / Astronomie ► Astronomie / Astrophysik
• Themenwelt: Naturwissenschaften ► Physik / Astronomie ► Atom- / Kern- / Molekularphysik
• Schlagworte: dispersive optical model • DOM binding energy • momentum distribution • neutron skin thickness • Nucleon-nucleus scattering • nucleon self-energy • removal probability
• ISBN-10: 3-030-53114-7 / 3030531147
• ISBN-13: 978-3-030-53114-0 / 9783030531140