Torres-Sanchez, P., Lerendegui-Marco, J., Balibrea-Correa, J., Babiano-Suarez, V., Gameiro, B., Ladarescu, I., et al. (2025). The potential of the i-TED Compton camera array for real-time boron imaging and determination during treatments in Boron Neutron Capture Therapy. Appl. Radiat. Isot., 217, 111649–9pp.
Abstract: This paper explores the adaptation and application of i-TED Compton imagers for real-time dosimetry in Boron Neutron Capture Therapy (BNCT). The i-TED array, previously utilized in nuclear astrophysics experiments at CERN, is being optimized for detecting and imaging 478 keV gamma-rays, critical for accurate BNCT dosimetry. Detailed Monte Carlo simulations were used to optimize the i-TED detector configuration and enhance its performance in the challenging radiation environment typical of BNCT. Additionally, advanced 3D image reconstruction algorithms, including a combination of back-projection and List-Mode Maximum Likelihood Expectation Maximization (LM-MLEM), are implemented and validated through simulations. Preliminary experimental tests at the Institut Laue-Langevin (ILL) demonstrate the potential of i-TED in simplified conditions, with ongoing experiments focusing on testing imaging capabilities in realistic BNCT conditions.
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Lerendegui-Marco, J., Hallam, J., Cisterna, G., Sanchis-Molto, A., Balibrea-Correa, J., Babiano-Suarez, V., et al. (2025). First experimental results and optimization study of the portable neutron-gamma imager GN-Vision. Appl. Radiat. Isot., 224, 111826–13pp.
Abstract: GN-Vision is a compact, dual-modality imaging device designed to simultaneously localize the spatial origin of y-ray and slow neutron sources, with potential applications in nuclear safety, security, and hadron therapy. The system utilizes two position-sensitive detection planes, combining Compton imaging techniques for yray visualization with passive collimation for imaging slow and thermal neutrons (energies below 100 eV). This paper presents the first experimental outcomes from the initial GN-Vision prototype, focused on the development of its neutron imaging capabilities. Following this experimental assessment, we explore the device's performance potential and discuss several Monte Carlo simulation-based optimizations aimed at refining the neutron collimation system. These optimizations seek to improve real-time imaging efficiency and cost-effectiveness, enhancing GN-Vision's applicability for future practical deployments.
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Real, D., Sanchez Losa, A., Diaz, A., Salesa Greus, F., & Calvo, D. (2023). The Neutrino Mediterranean Observatory Laser Beacon: Design and Qualification. Appl. Sci.-Basel, 13(17), 9935–16pp.
Abstract: This paper encapsulates details of the NEMO laser beacon's design, offering a profound contribution to the field of the time calibration of underwater neutrino telescopes. The mechanical design of the laser beacon, which operates at a depth of 3500 m, is presented, together with the design of the antibiofouling system employed to endure the operational pressure and optimize the operational range, enhancing its functionality and enabling time calibration among multiple towers. A noteworthy innovation central to this development lies in the battery system. This configuration enhances the device's portability, a crucial aspect in underwater operations. The comprehensive design of the laser beacon, encompassing the container housing, the requisite battery system for operation, electronics, and an effective antibiofouling system, is described in this paper. Additionally, this paper presents the findings of the laser beacon's qualification process.
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Panes, B., Eckner, C., Hendriks, L., Caron, S., Dijkstra, K., Johannesson, G., et al. (2021). Identification of point sources in gamma rays using U-shaped convolutional neural networks and a data challenge. Astron. Astrophys., 656, A62–18pp.
Abstract: Context. At GeV energies, the sky is dominated by the interstellar emission from the Galaxy. With limited statistics and spatial resolution, accurately separating point sources is therefore challenging. Aims. Here we present the first application of deep learning based algorithms to automatically detect and classify point sources from gamma-ray data. For concreteness we refer to this approach as AutoSourceID. Methods. To detect point sources, we utilized U-shaped convolutional networks for image segmentation and k-means for source clustering and localization. We also explored the Centroid-Net algorithm, which is designed to find and count objects. Using two algorithms allows for a cross check of the results, while a combination of their results can be used to improve performance. The training data are based on 9.5 years of exposure from The Fermi Large Area Telescope (Fermi-LAT) and we used source properties of active galactic nuclei (AGNs) and pulsars (PSRs) from the fourth Fermi-LAT source catalog in addition to several models of background interstellar emission. The results of the localization algorithm are fed into a classification neural network that is trained to separate the three general source classes (AGNs, PSRs, and FAKE sources). Results. We compared our localization algorithms qualitatively with traditional methods and find them to have similar detection thresholds. We also demonstrate the robustness of our source localization algorithms to modifications in the interstellar emission models, which presents a clear advantage over traditional methods. The classification network is able to discriminate between the three classes with typical accuracy of similar to 70%, as long as balanced data sets are used in classification training. We published online our training data sets and analysis scripts and invite the community to join the data challenge aimed to improve the localization and classification of gamma-ray point sources.
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Sanchis-Lozano, M. A., Melia, F., Lopez-Corredoira, M., & Sanchis-Gual, N. (2022). Missing large-angle correlations versus even-odd point-parity imbalance in the cosmic microwave background. Astron. Astrophys., 660, A121–10pp.
Abstract: Context. The existence of a maximum correlation angle (theta(max) & 60 greater than or similar to degrees) in the two-point angular temperature correlations of cosmic microwave background (CMB) radiation, measured by WMAP and Planck, stands in sharp contrast to the prediction of standard inflationary cosmology, in which the correlations should extend across the full sky (i.e., 180 degrees). The introduction of a hard lower cuto ff (k(min)) in the primordial power spectrum, however, leads naturally to the existence of theta(max). Among other cosmological anomalies detected in these data, an apparent dominance of odd-over-even parity multipoles has been seen in the angular power spectrum of the CMB. This feature, however, may simply be due to observational contamination in certain regions of the sky. Aims. In attempting to provide a more detailed assessment of whether this odd-over-even asymmetry is intrinsic to the CMB, we therefore proceed in this paper, first, to examine whether this odd-even parity imbalance also manifests itself in the angular correlation function and, second, to examine in detail the interplay between the presence of theta(max) and this observed anomaly. Methods. We employed several parity statistics and recalculated the angular correlation function for di fferent values of the cuto ff kmin in order to optimize the fit to the di fferent Planck 2018 data. Results. We find a phenomenological connection between these features in the data, concluding that both must be considered together in order to optimize the theoretical fit to the Planck 2018 data. Conclusions. This outcome is independent of whether the parity imbalance is intrinsic to the CMB, but if it is, the odd-over-even asymmetry would clearly point to the emergence of new physics.
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