AGATA: Precision Spectroscopy of Exotic Nuclei

Lead Research Organisation: University of Liverpool
Department Name: Physics

Abstract

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Planned Impact

The impact of the UK project will derive from the signal processing and technological advances delivered to the next phase of the AGATA spectrometer. This impact will be enabled through the partnerships with industrial collaborators, major outreach projects, and will impact on other scientific disciplines outside nuclear physics. The innovative gamma-ray imaging technology developed will continue to lead to many collaborative projects for nuclear physics in the medical, security, decommissioning and environmental monitoring areas. The groups have a strong track record of industrial collaboration with partners including AWE, Kromek, the Defence Academy of the United Kingdom, Mirion Technologies (Canberra), Ametek (Ortec), John Caunt Scientific, National Nuclear Laboratory and Rapiscan. There have been many collaborative projects (for example NuPNET, DEPICT, GRi+, ProSPECTus, PorGamRays, PGRIS and GammaKeV), a number of which directly derive from earlier work pioneered within the AGATA collaboration. STFC has helped to leverage funds from these partners with support provided through the STFC CLASP, STFC mini-IPS, STFC follow-on, STFC IPS and STFC CASE schemes.

The technologies and techniques developed through the AGATA project have had and will continue to influence other disciplines. Examples include
The Pulse Shape Analysis and characterisation methods for HPGe signals are crucial for the success of background rejection in two large scale neutrinoless double-beta decay experiments, GERDA and MAJORANA which have recently merged to form the LEGEND collaboration. Moreover, realistic electric field calculations and signal generation algorithms are essential for an effective pulse-shape analysis and offer significant linkages between the AGATA project and these experiments.
Gamma-ray tracking algorithms are also used in Compton gamma cameras, which find applications in nuclear astrophysics, nuclear security, nuclear decontamination and decommissioning, and medical imaging.
The need for highly-segmented, position sensitive HPGe crystals imposed by the AGATA and GRETA arrays has enabled the vendor and industrial partner (Mirion Technologies) to develop the necessary detector technology to high standards.
In each of these areas there are significant opportunities to exploit the advances that will be enabled by the UK AGATA project. For the LEGEND collaboration, Liverpool are the UK lead for the next generation "inverted coax" detector characterisation programme which with output from the AGATA project grant will enable a new level of background reduction to be achieved. The gamma-ray tracking Compton Camera systems rely on high performance signal decomposition and tracking algorithms. The realisation of an automated approach to optimising these algorithms would open a huge range of opportunities. Finally pushing detector manufacturers industrialise high-segmented gamma-ray detector systems will in time lead to such systems being available for wider commercial application.

We will build on our excellent track record in public engagement and outreach to fulfil the important role of educating the public in nuclear radiation and its wider aspects. York have pioneered the 'binding blocks' nuclear-physics outreach project, with support from STFC. This allows members of the public and schools to build a 9m long 3D nuclear chart of all isotopes made completely out of Lego. We will continue this engagement, highlighting the areas of the chart that will be explored using AGATA. The groups engage widely with school pupils and teachers via several events, such as the year-12 nuclear-physics masterclasses, which have been hosted already by three of the institutions on this project. Events such as these will be used to highlight the innovation and scientific exploitation of the AGATA programme.
 
Title Machine Learning approach to Pulse Shape Analysis 
Description A novel approach to analysing signal shapes from an AGATA detector module has been developed using machine learning approaches. 
Type Of Material Data analysis technique 
Year Produced 2022 
Provided To Others? Yes  
Impact Improvement in the performance of the Pulse Shape Analysis approach to identifying the location of the interaction of gamma-rays in large volumes semiconductor detectors.