Online Dissertation Defense: Paul Fanto, Yale University, “Statistical properties of nuclei: beyond the mean-field approximation”

Event time: 
Friday, May 21, 2021 - 1:00pm to 2:00pm
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Event description: 

The statistical model of compound-nucleus reactions has important applications in fundamental nuclear science, nuclear astrophysics, and nuclear technology. This model relies on two theoretical areas: (i) statistical reaction theory, which describes the compound nucleus with the Gaussian orthogonal ensemble (GOE) of random-matrix theory; and (ii) statistical properties of nuclei, i.e., nuclear structure observables that determine statistical-model predictions of reaction rates.
The GOE statistical theory predicts that the partial widths of compound-nucleus resonances follow the Porter-Thomas distribution (PTD) and that total $\gamma$-decay widths have a narrow distribution. However, recent experiments measured width distributions that were broader than statistical-model predictions. We study these results with resonance-reaction models based on the GOE.
Nuclear level densities are important statistical properties of nuclei and inputs to the statistical model. Mean-field methods are widely used to calculate level densities microscopically but neglect important correlations. We introduce two novel methods for symmetry projection after variation in the finite-temperature mean-field approximation and calculate nuclear state densities with exact particle-number projection. Moreover, we calculate state densities in the configuration-interaction shell model framework using the static-path plus random-phase approximation (SPA+RPA). The SPA+RPA includes static fluctuations and small-amplitude time-dependent quantal fluctuations beyond the mean field.
We find that the SPA+RPA state densities agree with exact shell model Monte Carlo (SMMC) state densities and improve significantly over mean-field state densities in heavy lanthanide nuclei.
Thesis advisor: Yoram Alhassid (