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Belver, D., Blanco, A., Cabanelas, P., Diaz, J., Fonte, P., Garzon, J. A., et al. (2012). Analysis of the space-time microstructure of cosmic ray air showers using the HADES RPC TOF wall. J. Instrum., 7, P10007–9pp.
Abstract: Cosmic rays have been studied, since they were discovered one century ago, with a very broad spectrum of detectors and techniques. However, never the properties of the extended air showers (EAS) induced by high energy primary cosmic rays had been analysed at the Earth surface with a high granularity detector and a time resolution at the 0.1 ns scale. The commissioning of the timing RPC (Resistive Plate Chambers) time of flight wall of the HADES spectrometer with cosmic rays, at the GSI (Darmstadt, Germany), opened up that opportunity. During the last months of 2009, more than 500 millions of cosmic ray events were recorded by a stack of two RPC modules, of about 1.25 m(2) each, able to measure swarms of up to similar to 100 particles with a time resolution better than 100 ps. In this document it is demonstrated how such a relative small two-plane, high-granularity timing RPC setup may provide significant information about the properties of the shower and hence about the primary cosmic ray properties.
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NEXT Collaboration(Serra, L. et al), Sorel, M., Alvarez, V., Carcel, S., Cervera-Villanueva, A., Diaz, J., et al. (2015). An improved measurement of electron-ion recombination in high-pressure xenon gas. J. Instrum., 10, P03025–21pp.
Abstract: We report on results obtained with the NEXT-DEMO prototype of the NEXT-100 high-pressure xenon gas time projection chamber (TPC), filled with pure xenon gas at 10 bar pressure and exposed to an alpha decay calibration source. Compared to our previous measurements with alpha particles, an upgraded detector and improved analysis techniques have been used. We measure event-by-event correlated fluctuations between ionization and scintillation due to electronion recombination in the gas, with correlation coefficients between -0.80 and -0.56 depending on the drift field conditions. By combining the two signals, we obtain a 2.8% FWHM energy resolution for 5.49 MeV alpha particles and a measurement of the optical gain of the electroluminescent TPC. The improved energy resolution also allows us to measure the specific activity of the radon in the gas due to natural impurities. Finally, we measure the average ratio of excited to ionized atoms produced in the xenon gas by alpha particles to be 0.561 +/- 0.045, translating into an average energy to produce a primary scintillation photon of W-ex = (39.2 +/- 3.2) eV.
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ATLAS Collaboration(Aad, G. et al), Amoros, G., Cabrera Urban, S., Castillo Gimenez, V., Costa, M. J., Ferrer, A., et al. (2012). A study of the material in the ATLAS inner detector using secondary hadronic interactions. J. Instrum., 7, P01013–40pp.
Abstract: The ATLAS inner detector is used to reconstruct secondary vertices due to hadronic interactions of primary collision products, so probing the location and amount of material in the inner region of ATLAS. Data collected in 7 TeV pp collisions at the LHC, with a minimum bias trigger, are used for comparisons with simulated events. The reconstructed secondary vertices have spatial resolutions ranging from similar to 200 μm to 1 mm. The overall material description in the simulation is validated to within an experimental uncertainty of about 7%. This will lead to a better understanding of the reconstruction of various objects such as tracks, leptons, jets, and missing transverse momentum.
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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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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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