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Aiola, S., Amhis, Y., Billoir, P., Jashal, B. K., Henry, L., Oyanguren, A., et al. (2021). Hybrid seeding: A standalone track reconstruction algorithm for scintillating fibre tracker at LHCb. Comput. Phys. Commun., 260, 107713–5pp.
Abstract: We describe the Hybrid seeding, a stand-alone pattern recognition algorithm aiming at finding charged particle trajectories for the LHCb upgrade. A significant improvement to the charged particle reconstruction efficiency is accomplished by exploiting the knowledge of the LHCb magnetic field and the position of energy deposits in the scintillating fibre tracker detector. Moreover, we achieve a low fake rate and a small contribution to the overall timing budget of the LHCb real-time data processing.
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NEXT Collaboration(Simon, A. et al), Gomez-Cadenas, J. J., Alvarez, V., Benlloch-Rodriguez, J. M., Botas, A., Carcel, S., et al. (2017). Application and performance of an ML-EM algorithm in NEXT. J. Instrum., 12, P08009–22pp.
Abstract: The goal of the NEXT experiment is the observation of neutrinoless double beta decay in Xe-136 using a gaseous xenon TPC with electroluminescent amplification and specialized photodetector arrays for calorimetry and tracking. The NEXT Collaboration is exploring a number of reconstruction algorithms to exploit the full potential of the detector. This paper describes one of them: the Maximum Likelihood Expectation Maximization (ML-EM) method, a generic iterative algorithm to find maximum-likelihood estimates of parameters that has been applied to solve many different types of complex inverse problems. In particular, we discuss a bi-dimensional version of the method in which the photosensor signals integrated over time are used to reconstruct a transverse projection of the event. First results show that, when applied to detector simulation data, the algorithm achieves nearly optimal energy resolution (better than 0.5% FWHM at the Q value of 136Xe) for events distributed over the full active volume of the TPC.
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Boronat, M., Fuster, J., Garcia, I., Ros, E., & Vos, M. (2015). A robust jet reconstruction algorithm for high-energy lepton colliders. Phys. Lett. B, 750, 95–99.
Abstract: We propose a new sequential jet reconstruction algorithm for future lepton colliders at the energy frontier. The Valencia algorithm combines the natural distance criterion for lepton colliders with the greater robustness against backgrounds of algorithms adapted to hadron colliders. Results on a detailed Monte Carlo simulation of t (t) over tilde and ZZ production at future linear e(+)e(-) colliders (ILC and CLIC) with a realistic level of background overlaid, show that it achieves better performance in the presence of background than the classical algorithms used at previous e(+)e(-) colliders.
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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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ANTARES Collaboration(Aguilar, J. A. et al), Bigongiari, C., Dornic, D., Emanuele, U., Gomez-Gonzalez, J. P., Hernandez-Rey, J. J., et al. (2011). A fast algorithm for muon track reconstruction and its application to the ANTARES neutrino telescope. Astropart Phys., 34(9), 652–662.
Abstract: An algorithm is presented, that provides a fast and robust reconstruction of neutrino induced upward-going muons and a discrimination of these events from downward-going atmospheric muon background in data collected by the ANTARES neutrino telescope. The algorithm consists of a hit merging and hit selection procedure followed by fitting steps for a track hypothesis and a point-like light source. It is particularly well-suited for real time applications such as online monitoring and fast triggering of optical follow-up observations for multi-messenger studies. The performance of the algorithm is evaluated with Monte Carlo simulations and various distributions are compared with that obtained in ANTARES data.
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