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ATLAS Collaboration(Abat, E. et al), Bernabeu Verdu, J., Castillo Gimenez, V., Costa, M. J., Escobar, C., Ferrer, A., et al. (2011). A layer correlation technique for pion energy calibration at the 2004 ATLAS Combined Beam Test. J. Instrum., 6, P06001–35pp.
Abstract: A new method for calibrating the hadron response of a segmented calorimeter is developed and successfully applied to beam test data. It is based on a principal component analysis of energy deposits in the calorimeter layers, exploiting longitudinal shower development information to improve the measured energy resolution. Corrections for invisible hadronic energy and energy lost in dead material in front of and between the calorimeters of the ATLAS experiment were calculated with simulated Geant4 Monte Carlo events and used to reconstruct the energy of pions impinging on the calorimeters during the 2004 Barrel Combined Beam Test at the CERN H8 area. For pion beams with energies between 20 GeV and 180 GeV, the particle energy is reconstructed within 3% and the energy resolution is improved by between 11% and 25% compared to the resolution at the electromagnetic scale.
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Peppa, V., Thomson, R. M., Enger, S. A., Fonseca, G. P., Lee, C. N., Lucero, J. N. E., et al. (2023). A MC-based anthropomorphic test case for commissioning model-based dose calculation in interstitial breast 192-Ir HDR brachytherapy. Med. Phys., 50(7), 4675–4687.
Abstract: PurposeTo provide the first clinical test case for commissioning of Ir-192 brachytherapy model-based dose calculation algorithms (MBDCAs) according to the AAPM TG-186 report workflow. Acquisition and Validation MethodsA computational patient phantom model was generated from a clinical multi-catheter Ir-192 HDR breast brachytherapy case. Regions of interest (ROIs) were contoured and digitized on the patient CT images and the model was written to a series of DICOM CT images using MATLAB. The model was imported into two commercial treatment planning systems (TPSs) currently incorporating an MBDCA. Identical treatment plans were prepared using a generic Ir-192 HDR source and the TG-43-based algorithm of each TPS. This was followed by dose to medium in medium calculations using the MBDCA option of each TPS. Monte Carlo (MC) simulation was performed in the model using three different codes and information parsed from the treatment plan exported in DICOM radiation therapy (RT) format. Results were found to agree within statistical uncertainty and the dataset with the lowest uncertainty was assigned as the reference MC dose distribution. Data Format and Usage NotesThe dataset is available online at ,. Files include the treatment plan for each TPS in DICOM RT format, reference MC dose data in RT Dose format, as well as a guide for database users and all files necessary to repeat the MC simulations. Potential ApplicationsThe dataset facilitates the commissioning of brachytherapy MBDCAs using TPS embedded tools and establishes a methodology for the development of future clinical test cases. It is also useful to non-MBDCA adopters for intercomparing MBDCAs and exploring their benefits and limitations, as well as to brachytherapy researchers in need of a dosimetric and/or a DICOM RT information parsing benchmark. Limitations include specificity in terms of radionuclide, source model, clinical scenario, and MBDCA version used for its preparation.
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Arganda, E., Marcano, X., Martin Lozano, V., Medina, A. D., Perez, A. D., Szewc, M., et al. (2022). A method for approximating optimal statistical significances with machine-learned likelihoods. Eur. Phys. J. C, 82(11), 993–14pp.
Abstract: Machine-learning techniques have become fundamental in high-energy physics and, for new physics searches, it is crucial to know their performance in terms of experimental sensitivity, understood as the statistical significance of the signal-plus-background hypothesis over the background-only one. We present here a simple method that combines the power of current machine-learning techniques to face high-dimensional data with the likelihood-based inference tests used in traditional analyses, which allows us to estimate the sensitivity for both discovery and exclusion limits through a single parameter of interest, the signal strength. Based on supervised learning techniques, it can perform well also with high-dimensional data, when traditional techniques cannot. We apply the method to a toy model first, so we can explore its potential, and then to a LHC study of new physics particles in dijet final states. Considering as the optimal statistical significance the one we would obtain if the true generative functions were known, we show that our method provides a better approximation than the usual naive counting experimental results.
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ANTARES Collaboration(Aguilar, J. A. et al), Bigongiari, C., Dornic, D., Emanuele, U., Gomez-Gonzalez, J. P., Hernandez-Rey, J. J., et al. (2012). A method for detection of muon induced electromagnetic showers with the ANTARES detector. Nucl. Instrum. Methods Phys. Res. A, 675, 56–62.
Abstract: The primary aim of ANTARES is neutrino astronomy with upward going muons created in charged current muon neutrino interactions in the detector and its surroundings. Downward going muons are background for neutrino searches. These muons are the decay products of cosmic-ray collisions in the Earth's atmosphere far above the detector. This paper presents a method to identify and count electromagnetic showers induced along atmospheric muon tracks with the ANTARES detector. The method is applied to both cosmic muon data and simulations and its applicability to the reconstruction of muon event energies is demonstrated.
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Contreras, T., Martins, A., Stanford, C., Escobar, C. O., Guenette, R., Stancari, M., et al. (2023). A method to characterize metalenses for light collection applications. J. Instrum., 18(9), T09004–11pp.
Abstract: Metalenses and metasurfaces are promising emerging technologies that could improve light collection in light collection detectors, concentrating light on small area photodetectors such as silicon photomultipliers. Here we present a detailed method to characterize metalenses to assess their efficiency at concentrating monochromatic light coming from a wide range of incidence angles, not taking into account their imaging quality.
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