α-decay half-life calculations of superheavy nuclei using artificial neural networks

Tuncay Bayram,S Okan Kara,Serkan Akkoyun

doi:10.1088/1742-6596/490/1/012105

Abstract

Investigations of superheavy elements (SHE) have received much attention in the last two decades, due to the successful syntheses of SHE. In particular, α-decay of SHEs has a great importance because most synthesized SHE have a-decay and the experimentalists have evaluated the theoretical predictions of the a-decay half-life during the experimental design. Because of this, the correct prediction of α-decay half-life is important to investigate superheavy nuclei as well as heavy nuclei. In this work, artificial neural networks (ANN) have been employed on experimental a-decay half-lives of superheavy nuclei. Statistical modeling of a-decay half-life of superheavy nuclei have been found as to be successful.

Highlights

In this work, feed-forward artificial neural networks (ANN) have been used in order to obtain α-decay half-lives of superheavy nuclei
One of the hottest research subjects in nuclear physics is superheavy nuclei beyond Fermium (Z = 100)
These values except those of Bh (Z = 107) nuclei have been used as output of artificial neural networks (ANN) in units of second while related proton Z, neutron N and mass A numbers have been used as inputs

Summary

Introduction

In this work, feed-forward ANN have been used in order to obtain α-decay half-lives of superheavy nuclei. The main purpose of the present study is to show success of ANN in describing of the unknown α-decay half-lives of superheavy nuclei.

Objectives

Results

Conclusion