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ATLAS Collaboration(Aad, G. et al), Cabrera Urban, S., Castillo Gimenez, V., Costa, M. J., Ferrer, A., Fiorini, L., et al. (2014). A neural network clustering algorithm for the ATLAS silicon pixel detector. J. Instrum., 9, P09009–34pp.
Abstract: A novel technique to identify and split clusters created by multiple charged particles in the ATLAS pixel detector using a set of artificial neural networks is presented. Such merged clusters are a common feature of tracks originating from highly energetic objects, such as jets. Neural networks are trained using Monte Carlo samples produced with a detailed detector simulation. This technique replaces the former clustering approach based on a connected component analysis and charge interpolation. The performance of the neural network splitting technique is quantified using data from proton-proton collisions at the LHC collected by the ATLAS detector in 2011 and from Monte Carlo simulations. This technique reduces the number of clusters shared between tracks in highly energetic jets by up to a factor of three. It also provides more precise position and error estimates of the clusters in both the transverse and longitudinal impact parameter resolution.
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Stuhl, L., Krasznahorkay, A., Csatlos, M., Algora, A., Gulyas, J., Kalinka, G., et al. (2014). A neutron spectrometer for studying giant resonances with (p,n) reactions in inverse kinematics. Nucl. Instrum. Methods Phys. Res. A, 736, 1–9.
Abstract: A neutron spectrometer, the European Low-Energy Neutron Spectrometer (ELENS), has been constructed to study exotic nuclei in inverse-kinematics experiments. The spectrometer, which consists of plastic scintillator bars, can be operated in the neutron energy range of 100 keV-10 MeV. The neutron energy is determined using the time-of-flight technique, while the position of the neutron detection is deduced from the time-difference information from photomultipliers attached to both ends of each bar. A novel wrapping method has been developed for the plastic scintillators. The array has a larger than 25% detection efficiency for neutrons of approximately 500 keV in kinetic energy and an angular resolution of less than 1 degrees. Details of the design, construction and experimental tests of the spectrometer will be presented.
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LHCb Collaboration(Aaij, R. et al), Martinez-Vidal, F., Oyanguren, A., Ruiz Valls, P., & Sanchez Mayordomo, C. (2016). A new algorithm for identifying the flavour of B-s(0) mesons at LHCb. J. Instrum., 11, P05010–23pp.
Abstract: A new algorithm for the determination of the initial flavour of B-s(0) mesons is presented. The algorithm is based on two neural networks and exploits the b hadron production mechanism at a hadron collider. The first network is trained to select charged kaons produced in association with the B-s(0) meson. The second network combines the kaon charges to assign the B-s(0) flavour and estimates the probability of a wrong assignment. The algorithm is calibrated using data corresponding to an integrated luminosity of 3 fb(-1) collected by the LHCb experiment in proton-proton collisions at 7 and 8 TeV centre-of-mass energies. The calibration is performed in two ways: by resolving the B-s(0)-B-s(0) flavour oscillations in B-s(0) -> D-s(-)pi(+) decays, and by analysing flavour-specific B-s2*(5840)(0) -> B+K- decays. The tagging power measured in B-s(0) -> D-s(-)pi(+) decays is found to be (1.80 +/- 0.19 ( stat) +/- 0.18 (syst))%, which is an improvement of about 50% compared to a similar algorithm previously used in the LHCb experiment.
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Hernandez, P., Pena, C., Ramos, A., & Gomez-Cadenas, J. J. (2021). A new formulation of compartmental epidemic modelling for arbitrary distributions of incubation and removal times. PLoS One, 16(2), e0244107–22pp.
Abstract: The paradigm for compartment models in epidemiology assumes exponentially distributed incubation and removal times, which is not realistic in actual populations. Commonly used variations with multiple exponentially distributed variables are more flexible, yet do not allow for arbitrary distributions. We present a new formulation, focussing on the SEIR concept that allows to include general distributions of incubation and removal times. We compare the solution to two types of agent-based model simulations, a spatially homogeneous one where infection occurs by proximity, and a model on a scale-free network with varying clustering properties, where the infection between any two agents occurs via their link if it exists. We find good agreement in both cases. Furthermore a family of asymptotic solutions of the equations is found in terms of a logistic curve, which after a non-universal time shift, fits extremely well all the microdynamical simulations. The formulation allows for a simple numerical approach; software in Julia and Python is provided.
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Egea Canet, F. J. et al, Gadea, A., & Huyuk, T. (2015). A New Front-End High-Resolution Sampling Board for the New-Generation Electronics of EXOGAM2 and NEDA Detectors. IEEE Trans. Nucl. Sci., 62(3), 1056–1062.
Abstract: This paper presents the final design and results of the FADC Mezzanine for the EXOGAM (EXOtic GAMma array spectrometer) and NEDA (Neutron Detector Array) detectors. The measurements performed include those of studying the effective number of bits, the energy resolution using HP-Ge detectors, as well as timing histograms and discrimination performance. Finally, the conclusion shows how a common digitizing device has been integrated in the experimental environment of two very different detectors which combine both low-noise acquisition and fast sampling rates. Not only the integration fulfilled the expected specifications on both systems, but it also showed how a study of synergy between detectors could lead to the reduction of resources and time by applying a common strategy.
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