|
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.
|
|
|
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.
|
|
|
ATLAS Collaboration(Aad, G. et al), Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Castillo, F. L., Castillo Gimenez, V., et al. (2020). Higgs boson production cross-section measurements and their EFT interpretation in the 4l decay channel at root s=13 TeV with the ATLAS detector. Eur. Phys. J. C, 80(10), 957–54pp.
Abstract: Higgs boson properties are studied in the fourlepton decay channel (where lepton = e, mu) using 139 fb(-1) of proton-proton collision data recorded at v s =13 TeV by the ATLAS experiment at the Large Hadron Collider. The inclusive cross-section times branching ratio for H -> ZZ * decay is measured to be 1.34 +/- 0.12 pb for a Higgs boson with absolute rapidity below 2.5, in good agreement with the Standard Model prediction of 1.33 +/- 0.08 pb. Crosssections times branching ratio are measured for the main Higgs boson production modes in several exclusive phasespace regions. The measurements are interpreted in terms of coupling modifiers and of the tensor structure of Higgs boson interactions using an effective field theory approach. Exclusion limits are set on the CP-even and CP-odd beyond the Standard Model couplings of the Higgs boson to vector bosons, gluons and top quarks.
|
|
|
ATLAS Collaboration(Aad, G. et al), Alvarez Piqueras, D., Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Castillo, F. L., et al. (2019). Identification of boosted Higgs bosons decaying into b-quark pairs with the ATLAS detector at 13 TeV. Eur. Phys. J. C, 79(10), 836–38pp.
Abstract: This paper describes a study of techniques for identifying Higgs bosons at high transverse momenta decaying into bottom-quark pairs, H -> b (b) over bar, for proton-proton collision data collected by the ATLAS detector at the Large Hadron Collider at a centre-of-mass energy root s = 13 TeV. These decays are reconstructed from calorimeter jets found with the anti-k(t) R = 1.0 jet algorithm. To tag Higgs bosons, a combination of requirements is used: b-tagging of R = 0.2 track-jets matched to the large-R calorimeter jet, and requirements on the jet mass and other jet substructure variables. The Higgs boson tagging efficiency and corresponding multijet and hadronic top-quark background rejections are evaluated using Monte Carlo simulation. Several benchmark tagging selections are defined for different signal efficiency targets. The modelling of the relevant input distributions used to tag Higgs bosons is studied in 36 fb(-1) of data collected in 2015 and 2016 using g -> b (b) over bar and Z(-> b (b) over bar)gamma event selections in data. Both processes are found to be well modelled within the statistical and systematic uncertainties.
|
|
|
ATLAS Collaboration(Aad, G. et al), Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Castillo, F. L., Castillo Gimenez, V., et al. (2021). Jet energy scale and resolution measured in proton-proton collisions at root s = 13 TeV with the ATLAS detector. Eur. Phys. J. C, 81(8), 689–49pp.
Abstract: Jet energy scale and resolution measurements with their associated uncertainties are reported for jets using 36-81 fb-1 of proton-proton collision data with a centre-of-mass energy of root s=13 TeV collected by the ATLAS detector at the LHC. Jets are reconstructed using two different input types: topo-clusters formed from energy deposits in calorimeter cells, as well as an algorithmic combination of charged-particle tracks with those topo-clusters, referred to as the ATLAS particle-flow reconstruction method. The anti-kt jet algorithm with radius parameter R=0.4 is the primary jet definition used for both jet types. This result presents new jet energy scale and resolution measurements in the high pile-up conditions of late LHC Run 2 as well as a full calibration of particle-flow jets in ATLAS. Jets are initially calibrated using a sequence of simulation-based corrections. Next, several in situ techniques are employed to correct for differences between data and simulation and to measure the resolution of jets. The systematic uncertainties in the jet energy scale for central jets (|eta|<1.2) vary from 1% for a wide range of high-pT jets (250<pT<2000 GeV), to 5% at very low pT (20 GeV) and 3.5% at very high pT (>2.5 TeV). The relative jet energy resolution is measured and ranges from (24 +/- 1.5)% at 20 GeV to (6 +/- 0.5)% at 300 GeV.
|
|