Search for CP violation through an amplitude analysis of D0 → K+K−π+π− decays
A search for CP violation in the Cabibbo-suppressed D0 → K+K−π+π− decay mode is performed using an amplitude analysis. The measurement uses a sample of pp collisions recorded by the LHCb experiment during 2011 and 2012, corresponding to an integrated luminosity of 3.0 fb−1. The D0 mesons are reconstructed from semileptonic b-hadron decays into D0μ−X final states. The selected sample contains more than 160 000 signal decays, allowing the most precise amplitude modelling of this D0 decay to date. The obtained amplitude model is used to perform the search for CP violation. The result is compatible with CP symmetry, with a sensitivity ranging from 1% to 15% depending on the amplitude considered.
We present a model for freight train time prediction based on station network analysis and specific feature engineering. We discuss the first pipeline to improve the freight flight duration prediction in Russia. While every freight company use only reference book made by RZD (Russian Railways) based on railroad distances with accuracy measured in days, we argue that one could predict the flight duration with error less than twenty hours while decreasing error to twelve hours for certain type of freight trains.
The cross-sections of 𝜓(2𝑆) meson production in proton-proton collisions at 𝑠√=13 TeV are measured with a data sample collected by the LHCb detector corresponding to an integrated luminosity of 275 pb−1. The production cross-sections for prompt 𝜓(2𝑆) mesons and those for 𝜓(2𝑆) mesons from b-hadron decays (𝜓(2𝑆)-from- 𝑏) are determined as functions of the transverse momentum, 𝑝T, and the rapidity, y, of the 𝜓(2𝑆) meson in the kinematic range 2<𝑝T<20 GeV/𝑐 and 2.0<𝑦<4.5
. The production cross-sections integrated over this kinematic region are
𝜎( prompt 𝜓(2𝑆),13 TeV)=1.430±0.005 (stat)±0.099 (syst)μb,𝜎(𝜓(2𝑆)-from- 𝑏,13 TeV)=0.426±0.002 (stat)±0.030 (syst)μb.
A new measurement of 𝜓(2𝑆)
production cross-sections in pp collisions at 𝑠√=7 TeV is also performed using data collected in 2011, corresponding to an integrated luminosity of 614 pb−1. The integrated production cross-sections in the kinematic range 3.5<𝑝T<14 GeV/𝑐 and 2.0<𝑦<4.5
𝜎( prompt 𝜓(2𝑆),7 TeV)=0.471±0.001 (stat)±0.025 (syst)μb,𝜎(𝜓(2𝑆)-from- 𝑏,7 TeV)=0.126±0.001 (stat)±0.008 (syst)μb.
All results show reasonable agreement with theoretical calculations.
One of the most challenging data analysis tasks of modern High Energy Physics experiments is the identification of particles. In this proceedings we review the new approaches used for particle identification at the LHCb experiment. Machine-Learning based techniques are used to identify the species of charged and neutral particles using several observables obtained by the LHCb sub-detectors. We show the performances of various solutions based on Neural Network and Boosted Decision Tree models.
The production of W and Z bosons in association with jets is studied in the forward region of proton-proton collisions collected at a centre-of-mass energy of 8 TeV by the LHCb experiment, corresponding to an integrated luminosity of 1.98 ± 0.02 fb−1 . The W boson is identified using its decay to a muon and a neutrino, while the Z boson is identified through its decay to a muon pair. Total cross-sections are measured and combined into charge ratios, asymmetries, and ratios of W+jet and Z+jet production cross-sections. Differential measurements are also performed as a function of both boson and jet kinematic variables. All results are in agreement with Standard Model predictions.
The law of accelerating returns can be viewed as a concept that describes acceleration of technological progress. The idea is that tools are used for developing more advanced tools that are applied for creating even more advanced tools etc. A similar idea has been implemented in algorithms for advancing artificial intelligence. In this paper, the results of applying these algorithms in games are discussed. Nevertheless, real life tasks seem more complicated. The game theoretic approach can be applied for transition from theoretical and unrealistic games to more complex and practical tasks. Applications of the game theoretic approach to advance artificial intelligence in solving tasks in the credit industry are proposed.
Proceedings of Machine Learning Research: Volume 97: International Conference on Machine Learning, 9-15 June 2019, Long Beach, California, USA
A full amplitude analysis of Λ 0 b → J/ψ pπ− decays is performed with a data sample acquired with the LHCb detector from 7 and 8 TeV pp collisions, corresponding to an integrated luminosity of 3 fb−1 . A significantly better description of the data is achieved when, in addition to the previously observed nucleon excitations N → pπ−, either the Pc(4380)+ and Pc(4450)+ → J/ψ p states, previously observed in Λ 0 b → J/ψ pK− decays, or the Zc(4200)− → J/ψ π− state, previously reported in B0 → J/ψ K+π − decays, or all three, are included in the amplitude models. The data support a model containing all three exotic states, with a significance of more than three standard deviations. Within uncertainties, the data are consistent with the Pc(4380)+ and Pc(4450)+ production rates expected from their previous observation taking account of Cabibbo suppression.