PANDA Collaboration(Singh, B. et al), & Diaz, J. (2019). Technical design report for the (P)over-barANDA Barrel DIRC detector. J. Phys. G, 46(4), 045001–155pp.
Abstract: The (P) over bar ANDA (anti-Proton ANnihiliation at DArmstadt) experiment will be one of the four flagship experiments at the new international accelerator complex FAIR (Facility for Antiproton and Ion Research) in Darmstadt, Germany. (P) over bar ANDA will address fundamental questions of hadron physics and quantum chromodynamics using high-intensity cooled antiproton beams with momenta between 1.5 and 15 GeV/c and a design luminosity of up to 2 x 10(32) cm(-2) S-1. Excellent particle identification (PID) is crucial to the success of the (P) over bar ANDA physics program. Hadronic PID in the barrel region of the target spectrometer will be performed by a fast and compact Cherenkov counter using the detection of internally reflected Cherenkov light (DIRC) technology. It is designed to cover the polar angle range from 22 degrees to 140 degrees and will provide at least 3 standard deviations (s.d.) pi/K separation up to 3.5 GeV/c, matching the expected upper limit of the final state kaon momentum distribution from simulation. This documents describes the technical design and the expected performance of the (P) over bar ANDA Barrel DIRC detector. The design is based on the successful BaBar DIRC with several key improvements. The performance and system cost were optimized in detailed detector simulations and validated with full system prototypes using particle beams at GSI and CERN. The final design meets or exceeds the PID goal of clean pi/K separation with at least 3 s.d. over the entire phase space of charged kaons in the Barrel DIRC.
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Magan, D. L. P., Caballero, L., Domingo-Pardo, C., Agramunt-Ros, J., Albiol, F., Casanovas, A., et al. (2016). First tests of the applicability of gamma-ray imaging for background discrimination in time-of-flight neutron capture measurements. Nucl. Instrum. Methods Phys. Res. A, 823, 107–119.
Abstract: In this work we explore for the first time the applicability of using gamma-ray imaging in neutron capture measurements to identify and suppress spatially localized background. For this aim, a pinhole gamma camera is assembled, tested and characterized in terms of energy and spatial performance. It consists of a monolithic CeBr3 scintillating crystal coupled to a position-sensitive photomultiplier and readout through an integrated circuit AMIC2GR. The pinhole collimator is a massive carven block of lead. A series of dedicated measurements with calibrated sources and with a neutron beam incident on a Au-197 sample have been carried out at n_TOF, achieving an enhancement of a factor of two in the signal-to-background ratio when selecting only those events coming from the direction of the sample.
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Etxebeste, A., Dauvergne, D., Fontana, M., Letang, J. M., Llosa, G., Muñoz, E., et al. (2020). CCMod: a GATE module for Compton camera imaging simulation. Phys. Med. Biol., 65(5), 055004–17pp.
Abstract: Compton cameras are gamma-ray imaging systems which have been proposed for a wide variety of applications such as medical imaging, nuclear decommissioning or homeland security. In the design and optimization of such a system Monte Carlo simulations play an essential role. In this work, we propose a generic module to perform Monte Carlo simulations and analyses of Compton Camera imaging which is included in the open-source GATE/Geant4 platform. Several digitization stages have been implemented within the module to mimic the performance of the most commonly employed detectors (e.g. monolithic blocks, pixelated scintillator crystals, strip detectors...). Time coincidence sorter and sequence coincidence reconstruction are also available in order to aim at providing modules to facilitate the comparison and reproduction of the data taken with different prototypes. All processing steps may be performed during the simulation (on-the-fly mode) or as a post-process of the output files (offline mode). The predictions of the module have been compared with experimental data in terms of energy spectra, angular resolution, efficiency and back-projection image reconstruction. Consistent results within a 3-sigma interval were obtained for the energy spectra except for low energies where small differences arise. The angular resolution measure for incident photons of 1275 keV was also in good agreement between both data sets with a value close to 13 degrees. Moreover, with the aim of demonstrating the versatility of such a tool the performance of two different Compton camera designs was evaluated and compared.
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Stoppa, F., Bhattacharyya, S., Ruiz de Austri, R., Vreeswijk, P., Caron, S., Zaharijas, G., et al. (2023). AutoSourceID-Classifier Star-galaxy classification using a convolutional neural network with spatial information. Astron. Astrophys., 680, A109–16pp.
Abstract: Aims. Traditional star-galaxy classification techniques often rely on feature estimation from catalogs, a process susceptible to introducing inaccuracies, thereby potentially jeopardizing the classification's reliability. Certain galaxies, especially those not manifesting as extended sources, can be misclassified when their shape parameters and flux solely drive the inference. We aim to create a robust and accurate classification network for identifying stars and galaxies directly from astronomical images.Methods. The AutoSourceID-Classifier (ASID-C) algorithm developed for this work uses 32x32 pixel single filter band source cutouts generated by the previously developed AutoSourceID-Light (ASID-L) code. By leveraging convolutional neural networks (CNN) and additional information about the source position within the full-field image, ASID-C aims to accurately classify all stars and galaxies within a survey. Subsequently, we employed a modified Platt scaling calibration for the output of the CNN, ensuring that the derived probabilities were effectively calibrated, delivering precise and reliable results.Results. We show that ASID-C, trained on MeerLICHT telescope images and using the Dark Energy Camera Legacy Survey (DECaLS) morphological classification, is a robust classifier and outperforms similar codes such as SourceExtractor. To facilitate a rigorous comparison, we also trained an eXtreme Gradient Boosting (XGBoost) model on tabular features extracted by SourceExtractor. While this XGBoost model approaches ASID-C in performance metrics, it does not offer the computational efficiency and reduced error propagation inherent in ASID-C's direct image-based classification approach. ASID-C excels in low signal-to-noise ratio and crowded scenarios, potentially aiding in transient host identification and advancing deep-sky astronomy.
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Llosa, G., Barrio, J., Cabello, J., Crespo, A., Lacasta, C., Rafecas, M., et al. (2012). Detector characterization and first coincidence tests of a Compton telescope based on LaBr3 crystals and SiPMs. Nucl. Instrum. Methods Phys. Res. A, 695, 105–108.
Abstract: A Compton telescope for dose monitoring in hadron therapy consisting of several layers of continuous LaBr3 crystals coupled to silicon photomultiplier (SiPM) arrays is under development within the ENVISION project. In order to test the possibility of employing such detectors for the telescope, a detector head consisting of a continuous 16 mm x 18 mm x 5 mm LaBr3 crystal coupled to a SiPM array has been assembled and characterized, employing the SPIROC1 ASIC as readout electronics. The best energy resolution obtained at 511 key is 6.5% FWHM and the timing resolution is 3.1 ns FWHM. A position determination method for continuous crystals is being tested, with promising results. In addition, the detector has been operated in time coincidence with a second detector layer, to determine the coincidence capabilities of the system. The first tests are satisfactory, and encourage the development of larger detectors that will compose the telescope prototype.
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