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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). Fiducial, total and differential cross-section measurements of t-channel single top-quark production in pp collisions at 8 TeV using data collected by the ATLAS detector. Eur. Phys. J. C, 77(8), 531–46pp.
Abstract: Detailed measurements of t-channel single top-quark production are presented. They use 20.2 fb(-1) of data collected by the ATLAS experiment in proton-proton collisions at a centre-of-mass energy of 8 TeV at the LHC. Total, fiducial and differential cross-sections are measured for both top-quark and top-antiquark production. The fiducial cross-section is measured with a precision of 5.8% (top quark) and 7.8% (top antiquark), respectively. The total cross-sections are measured to be stot(tq) = 56.7(-3.8)(+4.3) pb for top-quark production and sigma(tot)((t) over barq) = 32.9(-2.7)(+3.0) pb for top-antiquark production, in agreement with the Standard Model prediction. In addition, the ratio of top-quark to top-antiquark production cross-sections is determined to be R-t = 1.72 +/- 0.09. The differential cross-sections as a function of the transverse momentum and rapidity of both the top quark and the top antiquark are measured at both the parton and particle levels. The transverse momentum and rapidity differential cross-sections of the accompanying jet from the t-channel scattering are measured at particle level. All measurements are compared to various Monte Carlo predictions as well as to fixed-order QCD calculations where available.
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ATLAS Collaboration(Aad, G. et al), Cabrera Urban, S., Castillo Gimenez, V., Costa, M. J., Fassi, F., Ferrer, A., et al. (2014). Flavor tagged time-dependent angular analysis of the B-s(0) -> J/psi phi decay and extraction of Delta Gamma(s) and the weak phase phi(s) in ATLAS. Phys. Rev. D, 90(5), 052007–26pp.
Abstract: A measurement of the B-s(0) -> J/psi phi decay parameters, updated to include flavor tagging is reported using 4.9 fb(-1) of integrated luminosity collected by the ATLAS detector from root s = 7 TeV pp collisions recorded in 2011 at the LHC. The values measured for the physical parameters are phi(s) = 0.12 +/- 0.25(stat) +/- 0.05(syst) rad Delta Gamma(s) = 0.053 +/- 0.021(stat) +/- 0.010(syst) ps(-1) Gamma(s) = 0.677 +/- 0.007(stat) +/- 0.004(syst) ps(-1) vertical bar A(parallel to)(0)vertical bar(2) = 0.220 +/- 0.008(stat) +/- 0.009(syst) vertical bar A(0)(0)vertical bar(2) = 0.529 +/- 0.006(stat) +/- 0.012(syst) delta(perpendicular to) = 3.89 +/- 0.47(stat) +/- 0.11(syst) rad where the parameter Delta Gamma(s) is constrained to be positive. The S-wave contribution was measured and found to be compatible with zero. Results for phi(s) and Delta Gamma(s) are also presented as 68% and 95% likelihood contours, which show agreement with the Standard Model expectations.
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ATLAS Collaboration(Aaboud, M. et al), Alvarez Piqueras, D., Aparisi Pozo, J. A., Bailey, A. J., Barranco Navarro, L., Cabrera Urban, S., et al. (2020). Fluctuations of anisotropic flow in Pb plus Pb collisions at root s(NN)=5.02 TeV with the ATLAS detector. J. High Energy Phys., 01(1), 051–59pp.
Abstract: Multi-particle azimuthal cumulants are measured as a function of centrality and transverse momentum using 470 μb(-1) of Pb+Pb collisions at root s(NN) = 5.02TeV with the ATLAS detector at the LHC. These cumulants provide information on the event-by-event fluctuations of harmonic flow coefficients v(n) and correlated fluctuations between two harmonics v(n) and v(m). For the first time, a non-zero four-particle cumulant is observed for dipolar flow, v(1). The four-particle cumulants for elliptic flow, v(2), and triangular flow, v(3), exhibit a strong centrality dependence and change sign in ultra-central collisions. This sign change is consistent with significant non-Gaussian fluctuations in v(2) and v(3). The four-particle cumulant for quadrangular flow, v(4), is found to change sign in mid-central collisions. Correlations between two harmonics are studied with three- and four-particle mixed-harmonic cumulants, which indicate an anti-correlation between v(2) and v(3), and a positive correlation between v(2) and v(4). These correlations decrease in strength towards central collisions and either approach zero or change sign in ultra-central collisions. To investigate the possible flow fluctuations arising from intrinsic centrality or volume fluctuations, the results are compared between two different event classes used for centrality definitions. In peripheral and mid-central collisions where the cumulant signals are large, only small differences are observed. In ultra-central collisions, the differences are much larger and transverse momentum dependent. These results provide new information to disentangle flow fluctuations from the initial and final states, as well as new insights on the influence of centrality fluctuations.
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Conde, D., Castillo, F. L., Escobar, C., García, C., Garcia Navarro, J. E., Sanz, V., et al. (2023). Forecasting Geomagnetic Storm Disturbances and Their Uncertainties Using Deep Learning. Space Weather, 21(11), e2023SW003474–27pp.
Abstract: Severe space weather produced by disturbed conditions on the Sun results in harmful effects both for humans in space and in high-latitude flights, and for technological systems such as spacecraft or communications. Also, geomagnetically induced currents (GICs) flowing on long ground-based conductors, such as power networks, potentially threaten critical infrastructures on Earth. The first step in developing an alarm system against GICs is to forecast them. This is a challenging task given the highly non-linear dependencies of the response of the magnetosphere to these perturbations. In the last few years, modern machine-learning models have shown to be very good at predicting magnetic activity indices. However, such complex models are on the one hand difficult to tune, and on the other hand they are known to bring along potentially large prediction uncertainties which are generally difficult to estimate. In this work we aim at predicting the SYM-H index characterizing geomagnetic storms multiple-hour ahead, using public interplanetary magnetic field (IMF) data from the Sun-Earth L1 Lagrange point and SYM-H data. We implement a type of machine-learning model called long short-term memory (LSTM) network. Our scope is to estimate the prediction uncertainties coming from a deep-learning model in the context of forecasting the SYM-H index. These uncertainties will be essential to set reliable alarm thresholds. The resulting uncertainties turn out to be sizable at the critical stages of the geomagnetic storms. Our methodology includes as well an efficient optimization of important hyper-parameters of the LSTM network and robustness tests.
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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). Forward-backward correlations and charged-particle azimuthal distributions in pp interactions using the ATLAS detector. J. High Energy Phys., 07(7), 019–46pp.
Abstract: Using inelastic proton-proton interactions at root s = 900 GeV and 7 TeV, recorded by the ATLAS detector at the LHC, measurements have been made of the correlations between forward and backward charged-particle multiplicities and, for the first time, between forward and backward charged-particle summed transverse momentum. In addition, jet-like structure in the events is studied by means of azimuthal distributions of charged particles relative to the charged particle with highest transverse momentum in a, selected kinematic region of the event. The results are compared with predictions from tunes of the PYTHIA and HERWIG++ Monte Carlo generators, which in most cases are found to provide a reasonable description of the data.
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