Abstract
A novel experimental analysis method has been developed, making use of the continuous wavelet transform and machine learning to rapidly identify alpha -clustering in nuclei in regions of high nuclear state density. This technique was applied to resonant scattering measurements of the ^text {4}He(^text {40,44,48}Ca,alpha ) resonant reactions, allowing the alpha -cluster structure of ^text {44,48,52}Ti to be investigated. Fragmented alpha -clustering was identified in ^text {44}Ti and ^text {52}Ti, while the results for ^text {48}Ti were less conclusive, but suggest no such clustering.
Highlights
Surements, and often it is these uninteresting questions which dominate the efforts of researchers in their fields
In this article we present a novel technique which uses machine learning [1] to bypass the difficult and uninteresting parts of the analysis, and address the fundamental questions directly
The fundamental question we wish to address is: given an experimental energy spectrum produced by the resonant scattering of a nucleus with 4He, is α-clustering observed in the structure of the compound nucleus formed in this reaction? Alpha-clustering is the phenomenon whereby protons and neutrons form sub-structures within the nucleus, and it can usually be ascribed to specific nuclear energy levels, known as α-clustered states
Summary
Alpha-clustering is the phenomenon whereby protons and neutrons form sub-structures within the nucleus, and it can usually be ascribed to specific nuclear energy levels, known as α-clustered states This has been shown to play a pivotal role in dictating the properties and interactions of light nuclei [6,7], yet it has not been observed to the same extent in heavy nuclei. Analyses of α-transfer reactions have indicated that the degree of α-clustering in titanium isotopes decreases with increasing nuclear mass, both in the ground state [13,14] and in excited states [11], a measurement of 48Ca(α,α) elastic scattering shows significant resonant structure [15]. This allows the degree of α-clustering above the α-decay threshold to be compared consistently between the three isotopes, and is an ideal testing ground for a novel machine learning technique as 44Ti can be used to test the reliability of the procedure, as it is already well understood, before the technique is applied to the neutron rich isotopes
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
