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AGATA Collaboration(Clement, E. et al), Domingo-Pardo, C., Gadea, A., Perez-Vidal, R. M., & Civera, J. V. (2017). Conceptual design of the AGATA 1 pi array at GANIL. Nucl. Instrum. Methods Phys. Res. A, 855, 1–12.
Abstract: The Advanced GAmma Tracking Array (AGATA) has been installed at the GANIL facility, Caen-France. This setup exploits the stable and radioactive heavy-ions beams delivered by the cyclotron accelerator complex of GANIL. Additionally, it benefits from a large palette of ancillary detectors and spectrometers to address in-beam gamma-ray spectroscopy of exotic nuclei. The set-up has been designed to couple AGATA with a magnetic spectrometer, charged-particle and neutron detectors, scintillators for the detection of high-energy gamma rays and other devices such as a plunger to measure nuclear lifetimes. In this paper, the design and the mechanical characteristics of the set-up are described. Based on simulations, expected performances of the AGATA l pi array are presented.
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AGATA Collaboration(Crespi, F. C. L. et al), & Gadea, A. (2013). Response of AGATA segmented HPGe detectors to gamma rays up to 15.1 MeV. Nucl. Instrum. Methods Phys. Res. A, 705, 47–54.
Abstract: The response of AGATA segmented HPGe detectors to gamma rays in the energy range 2-15 MeV was measured. The 15.1 MeV gamma rays were produced using the reaction d(B-11,n gamma)C-12 at E-beam=19.1 MeV, while gamma rays between 2 and 9 MeV were produced using an Am-Be-Fe radioactive source. The energy resolution and linearity were studied and the energy-to-pulse-height conversion resulted to be linear within 0.05%.Experimental interaction multiplicity distributions are discussed and compared with the results of Geant4 simulations. It is shown that the application of gamma-ray tracking allows a suppression of background radiation caused by n-capture in Ge nuclei. Finally the Doppler correction for the 15.1 MeV gamma line, performed using the position information extracted with Pulse-shape analysis is discussed.
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AGATA Collaboration, Domingo-Pardo, C., Bazzacco, D., Doornenbal, P., Farnea, E., Gadea, A., et al. (2012). Conceptual design and performance study for the first implementation of AGATA at the in-flight RIB facility of GSI. Nucl. Instrum. Methods Phys. Res. A, 694, 297–312.
Abstract: The main objective of the Advanced GAmma Tracking Array (AGATA) is the investigation of the structure of exotic nuclei at the new generation of RIB facilities. As part of the preparatory phase for FAIR-NUSTAR, AGATA is going to be installed at the FRS fragmentation facility of the GSI centre for an experimental campaign to be performed in 2012 and 2013. Owing to its gamma-ray tracking capabilities and the envisaged enhancement in resolving power, a series of in-flight gamma-ray spectroscopy experiments are being planned. The present work describes the conceptual design of this first implementation of AGATA at GSI-FRS, and provides information about the expected performance figures. According to the characteristics of each particular experiment, it is foreseen that the target-array distance is adjusted in order to achieve the optimum compromise between detection efficiency and energy resolution, or to cover an specific angular range of the emitted electromagnetic radiation. Thus, a comprehensive Monte Carlo study of the detection sensitivity in terms of photopeak efficiency, resolution and peak-to-total ratio, as a function of the target-array distance is presented. Several configurations have been investigated, and MC-calculations indicate that a remarkable enhancement in resolving power can be achieved when double-cluster AGATA detectors are developed and implemented. Several experimental effects are also investigated. This concerns the impact of passive materials between the target and the array, the angular distribution of the detection efficiency and the influence of target thickness effects and transition lifetimes in the attainable detection sensitivity. A short overview on half-life measurements via lineshape effects utilizing AGATA is also presented. (C) 2012 Elsevier B.V. All rights reserved.
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AGATA Collaboration, Farnea, E., Recchia, F., Bazzacco, D., Kroll, T., Podolyak, Z., et al. (2010). Conceptual design and Monte Carlo simulations of the AGATA array. Nucl. Instrum. Methods Phys. Res. A, 621(1-3), 331–343.
Abstract: The aim of the Advanced GAmma Tracking Array (AGATA) project is the construction of an array based on the novel concepts of pulse shape analysis and gamma-ray tracking with highly segmented Ge semiconductor detectors. The conceptual design of AGATA and its performance evaluation under different experimental conditions has required the development of a suitable Monte Carlo code. In this article, the description of the code as well as simulation results relevant for AGATA, are presented.
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Gammaldi, V., Zaldivar, B., Sanchez-Conde, M. A., & Coronado-Blazquez, J. (2023). A search for dark matter among Fermi-LAT unidentified sources with systematic features in machine learning. Mon. Not. Roy. Astron. Soc., 520(1), 1348–1361.
Abstract: Around one-third of the point-like sources in the Fermi-LAT catalogues remain as unidentified sources (unIDs) today. Indeed, these unIDs lack a clear, univocal association with a known astrophysical source. If dark matter (DM) is composed of weakly interacting massive particles (WIMPs), there is the exciting possibility that some of these unIDs may actually be DM sources, emitting gamma-rays from WIMPs annihilation. We propose a new approach to solve the standard, machine learning (ML) binary classification problem of disentangling prospective DM sources (simulated data) from astrophysical sources (observed data) among the unIDs of the 4FGL Fermi-LAT catalogue. We artificially build two systematic features for the DM data which are originally inherent to observed data: the detection significance and the uncertainty on the spectral curvature. We do it by sampling from the observed population of unIDs, assuming that the DM distributions would, if any, follow the latter. We consider different ML models: Logistic Regression, Neural Network (NN), Naive Bayes, and Gaussian Process, out of which the best, in terms of classification accuracy, is the NN, achieving around 93 . 3 per cent +/- 0 . 7 per cent performance. Other ML evaluation parameters, such as the True Ne gativ e and True Positive rates, are discussed in our work. Applying the NN to the unIDs sample, we find that the de generac y between some astrophysical and DM sources can be partially solved within this methodology. None the less, we conclude that there are no DM source candidates among the pool of 4FGL Fermi-LAT unIDs.
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