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LHCb Collaboration(Aaij, R. et al), Garcia Martin, L. M., Martinez-Vidal, F., Oyanguren, A., Remon Alepuz, C., Ruiz Valls, P., et al. (2017). Observation of B+ -> J/psi 3 pi(+)2 pi(-) and B+ -> psi (2S)pi(+)pi(+)pi(-) decays. Eur. Phys. J. C, 77(2), 72–12pp.
Abstract: The decays B+-> J/psi 3 pi(+)2 pi(-) and B+ -> psi(2S)pi(+)pi(+)pi(-) are observed for the first time using a data sample corresponding to an integrated luminosity of 3.0 fb(-1), collected by the LHCb experiment in proton- proton collisions at the centre-of-mass energies of 7 and 8 TeV. The branching fractions relative to that of B+ -> psi(2S)K+ are measured to be B(B+-> J/psi 3 pi(+)2 pi(-))/B(B+ -> psi (2S)K+) = (1.88 +/- 0.17 +/- 0.09)x10(-2). B(B+ -> psi(2S)pi(+)pi(+)pi(-))/B(B+ -> psi (2S)K+) = (3.04 +/- 0.50 +/- 0.26)X10(-2) where the first uncertainties are statistical and the second are systematic.
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ATLAS Collaboration(Aaboud, M. et al), Alvarez Piqueras, D., Barranco Navarro, L., Cabrera Urban, S., Castillo Gimenez, V., Cerda Alberich, L., et al. (2017). Search for heavy resonances decaying to a Z boson and a photon in pp collisions at root s=13 TeV with the ATLAS detector. Phys. Lett. B, 764, 11–30.
Abstract: This Letter presents a search for new resonances with mass larger than 250 GeV, decaying to a Z boson and a photon. The dataset consists of an integrated luminosity of 3.2 fb(-1) of pp collisions collected at root s = 13 TeV with the ATLAS detector at the Large Hadron Collider. The Z bosons are identified through their decays either to charged, light, lepton pairs (e(+) e(-), mu(+) mu(-)) or to hadrons. The data are found to be consistent with the expected background in the whole mass range investigated and upper limits are set on the production cross section times decay branching ratio to Z gamma of a narrow scalar boson with mass between 250 GeV and 2.75 TeV.
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LHCb Collaboration(Aaij, R. et al), Garcia Martin, L. M., Martinez-Vidal, F., Oyanguren, A., Remon Alepuz, C., Ruiz Valls, P., et al. (2017). Search for the CP-violating strong decays eta -> pi(+)pi(-) and eta ' (958) -> pi(+)pi(-). Phys. Lett. B, 764, 233–240.
Abstract: A search for the CP-violating strong decays eta -> pi(+)pi(-) and eta ' (958) -> pi(+)pi(-) has been performed using approximately 2.5 x 10(7) events of each of the decays D+ -> pi(+)pi(+)pi(-) and D-s(+) -> pi(+)pi(+)pi(-), recorded by the LHCb experiment. The data set corresponds to an integrated luminosity of 3.0 fb(-1) of pp collision data recorded during LHC Run 1 and 0.3fb(-1) recorded in Run 2. No evidence is seen for D-(s)(+) -> pi(+)eta((')) with eta((')) -> pi(+)pi(-), and upper limits at 90% confidence level are set on the branching fractions, B(eta -> pi(+)pi(-)) < 1.6 x 10(-5) and B(eta' -> pi(+)pi(-)) < 1.8 x 10(-5). The limit for the eta decay is comparable with the existing one, while that for the eta' is a factor of three smaller than the previous limit.
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Vento, V. (2017). Skyrmions at high density. Int. J. Mod. Phys. E, 26(1-2), 1740029–15pp.
Abstract: The phase diagram of quantum chromodynamics is conjectured to have a rich structure containing at least three forms of matter: hadronic nuclear matter, quarkyonic matter and quark-gluon plasma. We justify the origin of the quarkyonic phase transition in a chiral-quark model and describe its formulation in terms of Skyrme crystals.
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NEXT Collaboration(Renner, J. et al), Benlloch-Rodriguez, J., Botas, A., Ferrario, P., Gomez-Cadenas, J. J., Alvarez, V., et al. (2017). Background rejection in NEXT using deep neural networks. J. Instrum., 12, T01004–21pp.
Abstract: We investigate the potential of using deep learning techniques to reject background events in searches for neutrinoless double beta decay with high pressure xenon time projection chambers capable of detailed track reconstruction. The differences in the topological signatures of background and signal events can be learned by deep neural networks via training over many thousands of events. These networks can then be used to classify further events as signal or background, providing an additional background rejection factor at an acceptable loss of efficiency. The networks trained in this study performed better than previous methods developed based on the use of the same topological signatures by a factor of 1.2 to 1.6, and there is potential for further improvement.
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