Jet Physics in the ATLAS Experiment At
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Jet Physics in the ATLAS experiment at LHC Vincenzo Cavasinni on behalf of the ATLAS Collaboration Dipartimento di fisica `E.Fermi' and INFN Pisa, ITALY E-mail: [email protected] Jet physics represents a powerful tool to investigate the properties of quark and gluon interactions. With the advent of LHC, these studies have been possible at an energy never investigated before. In this proceedings we review the main char- acteristics of jets measured by the ATLAS experiment in proton-proton collisions at center-of-mass energies of 7 and 8 TeV. The experimental results are compared with the predictions of the Quantum Chromodymamics, QCD, the standard theory of quark-gluon interactions. A good agreement is found between data and QCD predictions. The jet mesurements provide also a clue in the search for new physics: a few examples of searches for excited quarks and supersymmetric particles are presented. 1 Introduction The proton-proton collider LHC started operations at at center-of-mass energy of 7 TeV in 2010. ATLAS, one of the two multipurpose experiments, has collected an integrated luminosity of ≈ 40pb−1 in 2010 and ≈ 5fb−1 in 2011 . Jet production, consequence of the fragmentation of quarks and gluons in hadronic collisions, is the high-pT process with the highest cross section. Their measurement allows a direct access to the elementary interactions between the constituents of the incoming protons. The emergence of jets in hadron collisions has been proved by the UA2 experiment at ATL-PHYS-PROC-2012-152 30 August 2012 the CERN pp¯ Collider in 1983 [1]. Since then, many measurements at different collider energies have been performed: Fig. 1 summarizes schematically the inclusive jet cross sections investigated in a larger and larger pT range in the last 30 years. 1 2 Vincenzo Cavasinni HSQCD 2012 Figure 1: Inclusive jet cross sections as a function of the jet pT at various colliders. Also the theory of quark-gluon interactions, QCD, has been developed and verified with better and better accuracy, first at the CERN pp¯ Collider and, afterwards, at the Tevatron Collider (for a review see [2]). As a consequence, the QCD predictions ( at LO, NLO, NNLO) have become more and more stringent. The start-up of LHC has opened a new window of energy and the operation of powerful detectors, such as ATLAS, allows precise measurements of jets produced in pp collision in an energy region (TeV) never explored before. A precise knowledge of jet production is also fundamental as it is an important background for many new physics searches (including Higgs searches). The success of QCD made even more interesting the search of deviations from it. These deviations could indicate new physics: quark compositness, excited quarks, su- persymmetric particle production,... In almost all these new phenomena, the final state would be fully or partially made of jets which, therefore, constitute a powerful tool for new physics investigation. The counterpart of using jets, instead of single particles such as electrons, photons, muons, is that the jet definition relies strongly on the algorithm used to identify and measure it. This algorithm should ensure robustness, it should be insensitive to the infrared production, i.e. to low energy partons radiated by the leading parton, and collinear safe, i.e. insensitive to the decay of a parton into a parton-pair 3 almost collinear with it. The performances of jet identification and measurement depend on the quality of the calorimeter hardware: granularity, hermeticity, resolution, but also on the procedure to extract the correct jet energy scale (JES). The jet reconstruction performances are addressed in Sections 3 and 4 of this proceedings. The other parts will present a selection of physics results on inclusive jet and dijet production cross sections . The data are compared with QCD predictions using a variety of parton density functions (PDF) parametrizations. The agreement between data and theory is good in the full pT and dijet mass ranges. Finally, two examples of the use of jets to explore new physics are given in Section 71: the search for dijet resonances which could be generated by the decay of excited quarks and the search of superymmetric particles: gluinos and squarks, produced in a decay chain containing only jets and missing transverse momentum. 2 The ATLAS detector The ATLAS detector is shown in Fig. 2 [3]. Jet measurements are mainly performed by the electromagnetic andOverview hadronic of the ATLAS detector calorimeters with the contribution, for some appli- The ATLAS Detector cations, for example the jet energy calibration, of the inner detector. The calorimeters For the measurements described in this talk: inner detector, calorimeter system Figure 2: General view of the ATLAS detector. C. Doglioni - 29/05/2012 - CERN PH/LPCC Seminar 4 / 43 N cover jηj < 4:9 with 200000 read-out channels. The signal shape read-out allows the evaluation of the in-time and out-of-time pile-up events contributions. The tracking sys- tem is composed by pixel and strip semiconductor detectors near the interaction region 1For more details on search of new physics in ATLAS, see the Valerio Rossetti's talk at this Conference. Jet finding from calorimeter energy deposits to jets, to particles, to partons Calorimeter deposits : local 3D noise suppressed clusters (topoclusters) Standard jet reconstruction algorithm: anti-KT: 4 Vincenzo• CavasinniInfrared and collinear safe; HSQCD 2012 Calorimeter component of jet energyRegular, scale cone uncertainty-like shape in calorimeters; CalibrationHit concept in simulation: assign true• energy depositions in calorimeter to true particles in an event •Distance parameters: 0.6,0.4. Jets are selected requiring an isolation of ∆R > 2.0 to any other jet with pT (EM scale) > 7 GeV. The jet energy is decomposed into the energy of the constituent particles of the jet. The uncertainty on the JES is determined by propagating the uncertainties of the single particle measurements (see prev. slide) to the particles of the jet Pavel Starovoitov (DESY) JES uncertainty QCD LHC 5 / 12 6 Figure 3: Schematic view of the mechanism of jet production (left) and lego-plot of an event with jets reconstructed with the anti-kT algorithm [4] (right). and a transition radiation detector with a total number of 87 million read-out channels immersed in a 2 T axial magnetic field and covering jηj < 2:5. 3 Jet finding and reconstruction Ideally the jet finding algorithm should, starting from the energy depositions in the calorimeter, identify the particles which produced those energy-clusters and, from there, measure the 4-momenta of the parent partons, as schematically shown in Fig. 3 (left plot). Several algorithms have been developed to find jets. In ATLAS the preferred jet- finding algorithm is the anti-kT [4] based on local three-dimensional noise-suppressed clusters (topoclusters). This algorithm is infrared and collinear safe and produces regular cone-like shapes in the calorimeter (see Fig. 3, right plot). In our applications we used two typical radius parameters: R = 0:4 and R = 0:6. 4 Jet energy assessment The jet energy is first calibrated at the electromagnetic scale. This is done using test beam data with electrons, as well as in situ measurements using Z-decays into electron- pairs. The hadronic scale of the jet energy is extracted by means of constants obtained by a Monte Carlo calculation as a function of the jet eta and energy. The Monte Carlo Jet energy assessment • Electromagnetic energy scale from in situ measurement: Z→e- e+ ,test beam, muon MIP from the electromagnetic to the jet energy scale: EM+JES calibration •Pile up subtraction: in-time and out-of-time •MC provides constants to restore the JES as a function of η,pT 5 JES uncertainty determined with: •Isolated hadrons (in situ and test beam)) •MC samples varying parameters •Pile-up effect added as f(NPV) arXiv:1112.6426, submitted to EPJC 8 Figure 4: Contributions to jet energy scale uncertainty as a function of the jet pT obtained with the Monte Carlo (left), and its validation with several physics processes measured in situ (right). calculation includes the calorimeter response to single hadrons, the correction for pile-up and dead material effects. Fig. 4, left, shows the jet energy scale sistematic uncertainties coming from several contributions for the data collected in 2010 [5]. The uncertainty is limited to 2:5% for central jets and pT = 100 GeV up to 9(14)% for endcap (forward) jets. The JES calibration obtained with the Monte Carlo has been verified using several in situ measured processes: pT-balance of a photon and a jet, either directly, or imposing null transverse energy along the direction of the photon (γ−jet MPF, Missing Projection Fraction). Other in situ calibrations exploit the comparison between jet energy using tracks and calorimeters and, to higher jet pT, the multijet balancing. The result of this validation is shown in Fig. 4 (right): the agreement between MC-calibrated jets and the in situ calibration is good in the full pT interval. The increase of LHC luminosity of about a factor 15 in 2011, made it necessary to reevaluate the JES calibration constants; moreover the increased statistics allowed the use also of the Z-jet balancing as in situ validation channel [6]. As a result of the new calibrations, together with the multijet calibration, the JES is known to less than 3 % in the interval 30 GeV≤pT≤ 1300GeV: The jet energy resolution is important because it introduces systematic effects when 6 Vincenzo Cavasinni HSQCD 2012 Figure 5: On the left, inclusive jet cross section as a function of pT for several jet-rapidity intervals. On the right, the ratio of inclusive jet double-differential cross section to the theoretical prediction obtained using NLOJET++ with the CT10 PDF set.