# Shell Model Calculations for Proton-rich Zn Isotopes via New Generated Effective Interaction by Artificial Neural Networks

## TL;DR

This paper introduces a novel neural network-based method to generate effective interactions for shell model calculations, improving the accuracy of predictions for proton-rich Zn isotopes.

## Contribution

The study presents a new neural network approach to generate two-body matrix elements, enhancing shell model predictions for proton-rich nuclei.

## Key findings

- Generated interactions yield results close to original jj44b.
- New interactions sometimes align better with experimental data.
- Neural network approach improves shell model calculations.

## Abstract

In this study, the artificial neural network method has been employed for the generation of the new two-body matrix elements which is used for pfg shell nuclei. For this purpose, jj44b interaction Hamiltonian has been considered as a source. After the generation of the new Hamiltonian, both, original and new generated, are tested on proton-rich Zn isotopes. According to the results, the calculated values are close to the each other. As well the results from new interaction (jj44b_nn) are closer to the available experimental values in some cases.

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Source: https://tomesphere.com/paper/1907.03015