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CALICE Collaboration(Lai, S. et al), & Irles, A. (2024). Software compensation for highly granular calorimeters using machine learning. J. Instrum., 19(4), P04037–28pp.
Abstract: A neural network for software compensation was developed for the highly granular CALICE Analogue Hadronic Calorimeter (AHCAL). The neural network uses spatial and temporal event information from the AHCAL and energy information, which is expected to improve sensitivity to shower development and the neutron fraction of the hadron shower. The neural network method produced a depth-dependent energy weighting and a time-dependent threshold for enhancing energy deposits consistent with the timescale of evaporation neutrons. Additionally, it was observed to learn an energy-weighting indicative of longitudinal leakage correction. In addition, the method produced a linear detector response and outperformed a published control method regarding resolution for every particle energy studied.
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Cervera-Villanueva, A., Laing, A., Martin-Albo, J., & Soler, F. J. P. (2010). Performance of the MIND detector at a Neutrino Factory using realistic muon reconstruction. Nucl. Instrum. Methods Phys. Res. A, 624(3), 601–614.
Abstract: A Neutrino Factory producing an intense beam composed of v(e)((v) over bar (e)) and (v) over bar (mu)(v(mu)) from muon decays has been shown to have the greatest sensitivity to the two currently unmeasured neutrino mixing parameters theta(13) and delta(CP) Using the wrong-sign muon signal to measure v(e)-> v(mu)((v) over bar (e) ->(v) over bar (mu)) oscillations in a 50kt Magnetised Iron Neutrino Detector (MIND) sensitivity to delta(CP) could be maintained down to small values of theta(13) However the detector efficiencies used in these previous studies were calculated assuming perfect pattern recognition In this paper MIND is reassessed taking into account for the first time a realistic pattern recognition for the muon candidate Reoptimisation of the analysis utilises a combination of methods including a multivariate analysis similar to the one used in MINOS to maintain high efficiency while suppressing backgrounds ensuring that the signal selection efficiency and the background levels are comparable or better than the ones in previous analyses As a result MIND remains the most sensitive future facility for the discovery of CP violation from neutrino oscillations.
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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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LHCb Collaboration(Aaij, R. et al), Garcia Martin, L. M., Henry, L., Jashal, B. K., Martinez-Vidal, F., Oyanguren, A., et al. (2020). Observation of a new baryon state in the Lambda(0)(b)pi(+)pi(-) mass spectrum. J. High Energy Phys., 06(6), 136–26pp.
Abstract: A new baryon state is observed in the Lambda(0)(b)pi(+)pi(-) mass spectrum with high significance using a data sample of pp collisions, collected with the LHCb detector at centre-of-mass energies root s = 7, 8 and 13 TeV, corresponding to an integrated luminosity of 9 fb(-1). The mass and natural width of the new state are measured to be m = 6072.3 +/- 2.9 +/- 0.6 +/- 0.2 MeV, Gamma = 72 +/- 11 +/- 2 MeV, where the first uncertainty is statistical and the second systematic. The third uncertainty for the mass is due to imprecise knowledge of the Lambda(0)(b) baryon mass. The new state is consistent with the first radial excitation of the Lambda(0)(b) baryon, the Lambda(b)(2S)(0) resonance. Updated measurements of the masses and the upper limits on the natural widths of the previously observed Lambda(b)(5912)(0) and Lambda(b)(5920)(0) states are also reported.
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