Bouhova-Thacker, E., Kostyukhin, V., Koffas, T., Liebig, W., Limper, M., Piacquadio, G. N., et al. (2010). Expected Performance of Vertex Reconstruction in the ATLAS Experiment at the LHC. IEEE Trans. Nucl. Sci., 57(2), 760–767.
Abstract: In the harsh environment of the Large Hadron Collider at CERN (design luminosity of 10(34) cm(-2) s(-1)) efficient reconstruction of vertices is crucial for many physics analyses. Described in this paper is the expected performance of the vertex reconstruction used in the ATLAS experiment. The algorithms for the reconstruction of primary and secondary vertices as well as for finding photon conversions and vertex reconstruction in jets are described. The implementation of vertex algorithms which follows a very modular design based on object-oriented C++ is presented. A user-friendly concept allows event reconstruction and physics analyses to compare and optimize their choice among different vertex reconstruction strategies. The performance of implemented algorithms has been studied on a variety of Monte Carlo samples and results are presented.
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HAWC Collaboration(Alfaro, R. et al), & Salesa Greus, F. (2022). Gamma/hadron separation with the HAWC observatory. Nucl. Instrum. Methods Phys. Res. A, 1039, 166984–13pp.
Abstract: The High Altitude Water Cherenkov (HAWC) gamma-ray observatory observes atmospheric showers produced by incident gamma rays and cosmic rays with energy from 300 GeV to more than 100 TeV. A crucial phase in analyzing gamma-ray sources using ground-based gamma-ray detectors like HAWC is to identify the showers produced by gamma rays or hadrons. The HAWC observatory records roughly 25,000 events per second, with hadrons representing the vast majority (> 99.9%) of these events. The standard gamma/hadron separation technique in HAWC uses a simple rectangular cut involving only two parameters. This work describes the implementation of more sophisticated gamma/hadron separation techniques, via machine learning methods (boosted decision trees and neural networks), and summarizes the resulting improvements in gamma/hadron separation obtained in HAWC.
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Perez-Calatayud, J., Ballester, F., Tedgren, C., DeWerd, L. A., Papagiannis, P., Rivard, M. J., et al. (2022). GEC-ESTRO ACROP recommendations on calibration and traceability of HE HDR-PDR photon-emitting brachytherapy sources at the hospital level. Radiother. Oncol., 176, 108–117.
Abstract: The vast majority of radiotherapy departments in Europe using brachytherapy (BT) perform temporary implants of high-or pulsed-dose rate (HDR-PDR) sources with photon energies higher than 50 keV. Such techniques are successfully applied to diverse pathologies and clinical scenarios. These recommen-dations are the result of Working Package 21 (WP-21) initiated within the BRAchytherapy PHYsics Quality Assurance System (BRAPHYQS) GEC-ESTRO working group with a focus on HDR-PDR source cal-ibration. They provide guidance on the calibration of such sources, including practical aspects and issues not specifically accounted for in well-accepted societal recommendations, complementing the BRAPHYQS WP-18 Report dedicated to low energy BT photon emitting sources (seeds). The aim of this report is to provide a European-wide standard in HDR-PDR BT source calibration at the hospital level to maintain high quality patient treatments.
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KM3NeT Collaboration(Aiello, S. et al), Alves Garre, S., Calvo, D., Carretero, V., Colomer, M., Corredoira, I., et al. (2020). gSeaGen: The KM3NeT GENIE-based code for neutrino telescopes. Comput. Phys. Commun., 256, 107477–15pp.
Abstract: The gSeaGen code is a GENIE-based application developed to efficiently generate high statistics samples of events, induced by neutrino interactions, detectable in a neutrino telescope. The gSeaGen code is able to generate events induced by all neutrino flavours, considering topological differences between tracktype and shower-like events. Neutrino interactions are simulated taking into account the density and the composition of the media surrounding the detector. The main features of gSeaGen are presented together with some examples of its application within the KM3NeT project. Program summary Program Title: gSeaGen CPC Library link to program files: http://dx.doi.org/10.17632/ymgxvy2br4.1 Licensing provisions: GPLv3 Programming language: C++ External routines/libraries: GENIE [1] and its external dependencies. Linkable to MUSIC [2] and PROPOSAL [3]. Nature of problem: Development of a code to generate detectable events in neutrino telescopes, using modern and maintained neutrino interaction simulation libraries which include the state-of-the-art physics models. The default application is the simulation of neutrino interactions within KM3NeT [4]. Solution method: Neutrino interactions are simulated using GENIE, a modern framework for Monte Carlo event generators. The GENIE framework, used by nearly all modern neutrino experiments, is considered as a reference code within the neutrino community. Additional comments including restrictions and unusual features: The code was tested with GENIE version 2.12.10 and it is linkable with release series 3. Presently valid up to 5 TeV. This limitation is not intrinsic to the code but due to the present GENIE valid energy range. References: [1] C. Andreopoulos at al., Nucl. Instrum. Meth. A614 (2010) 87. [2] P. Antonioli et al., Astropart. Phys. 7 (1997) 357. [3] J. H. Koehne et al., Comput. Phys. Commun. 184 (2013) 2070. [4] S. Adrian-Martinez et al., J. Phys. G: Nucl. Part. Phys. 43 (2016) 084001.
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LHCb Collaboration(Aaij, R. et al), Martinez-Vidal, F., Oyanguren, A., Ruiz Valls, P., & Sanchez Mayordomo, C. (2015). Identification of beauty and charm quark jets at LHCb. J. Instrum., 10, P06013–29pp.
Abstract: Identification of jets originating from beauty and charm quarks is important for measuring Standard Model processes and for searching for new physics. The performance of algorithms developed to select b- and c-quark jets is measured using data recorded by LHCb from proton-proton collisions at root s = 7TeV in 2011 and at root s = 8TeV in 2012. The efficiency for identifying a b (c) jet is about 65%(25%) with a probability for misidentifying a light-parton jet of 0.3% for jets with transverse momentum pT > 20GeV and pseudorapidity 2 : 2 < eta < 4.2. The dependence of the performance on the pT and eta of the jet is also measured.
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