ATL-PHYS-PROC-2012-152 30 August 2012 n21.ALS n ftetomliups xeiet,hscletda integrated an collected has experiments, multipurpose TeV two 7 the of of of energy luminosity one center-of-mass ATLAS, at at 2010. operations in started LHC collider -proton The Introduction 1 nrishv enpromd i.1smaie ceaial h nlsv e cross inclusive p the larger schematically and summarizes larger a 1 in Fig. investigated sections performed: been have energies elementary the CERN to the access . direct incoming a the of allows constituents measurement the Their between interactions section. cross highest the h rgetto fqak n losi arnccliin,i h high-p the is collisions, hadronic in gluons and quarks of fragmentation the h mrec fjt nhdo olsoshsbe rvdb h A xeietat experiment UA2 the by proved been has collisions in jets of emergence The e xmlso erhsfrectdqak n uesmercprilsare particles supersymmetric and quarks excited physics: new for QCD for searches search and the of presented. data in examples between clue a found few also is a provide mesurements agreement jet good The theory A compared predictions. standard are the interactions. results QCD, quark-gluon Chromodymamics, experimental Quantum of The the TeV. collisions of 8 proton-proton predictions and the char- in 7 with main experiment of ATLAS the at energies review the possible center-of-mass we by been at proceedings measured have and this jets studies quark In of these of acteristics before. LHC, investigated properties of never the advent energy investigate the an to With tool interactions. powerful gluon a represents physics Jet p p ¯ ≈ oldri 93[] ic hn aymaueet tdffrn collider different at measurements many then, Since [1]. 1983 in Collider 40 e hsc nteALSeprmn tLHC at experiment ATLAS the in Physics Jet pb − 1 iatmnod sc EFri n INFN and ‘E.Fermi’ fisica di Dipartimento n21 and 2010 in -al [email protected] E-mail: nbhl fteALSCollaboration ATLAS the of behalf on icnoCavasinni Vincenzo ≈ ia ITALY Pisa, 5 fb − 1 T 1 n21 e rdcin osqec of consequence production, Jet . 2011 in ag ntels 0years. 30 last the in range T rcs with process 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, , 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 |η| < 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 |η| < 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, 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 (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. The ratios of POWHEG predictions showered using either Pythia or Hervig to the NLOJET++ predictions corrected for non-perturbative effects are also shown.

the unfolding procedure is applied to get the jet-pT cross section. The resolution is about 12% at a jet pT of 100 GeV and it decreases to about 7% at 1 TeV. If the JES calibration procedure is applied to individual energy clusters the resolution improves of 30% for high-pT jets.

5 Inclusive jet cross sections

Fig. 5 (left) shows the measured inclusive jet cross section as a function of the jet pT for several rapidity intervals [7]. For a pT range between 20 and 1200 GeV, the jet cross sections vary 10 orders of magnitude. A comparison is made with the predictions of NLOJET++ [8] with non-perturbative corrections and CT10 PDF, with factorization max and fragmentation scales µ = pT . Fig. 5 ( right) shows the ratio between the data and the NLOJET++ predictions. The ratio of the predictions of POWHEG interfaced with Pythia and Hervig, to NLO- JET++ are also shown in Fig. 5 (right). We find a good agreement between POWHEG and NLOJET++ at fixed order; a significant difference (up to 30%) is observed when POWHEG is interfaced to a parton shower of Pythia and Herwig, both at low and high pT. 7

The systematic uncertainty of the inclusive jet cross section is largely dominated by the JES uncertainty in the full pT interval and it ranges between 10 and 25% in the central rapidity region.

Figure 6: Ratios of inclusive jet double-differential cross section to the theoretical pre- diction obtained using NLOJET++ with the CT10 PDF set. The ratios are shown as a function of jet pT in different rapidity regions . The theoretical error bands obtained by using NLOJET++ with different PDF sets (CT10, MSTW 2008, NNPDF 2.1 and HERAPDF 1.5) are shown.

A comparison with NLOJET++ predictions using different PDF sets is shown in Fig. 6. The data show a marginally smaller cross section than the predictions from each of the PDF sets.

6 Dijet cross sections

Fig. 7 shows the dijet invariant mass, m12, differential cross section, for different intervals ∗ |y1−y2| of y = 2 where y1 and y2 are the rapidity of the leading and subleading jets for 2010 data on the left [7] and for 2011 data on the right [9]. The dijet invariant mass varies between 0.26 TeV and 4.6 TeV and no deviation from the NLOJET++ predictions is observed as shown in Fig. 8 which presents the ratio between data and the NLOJET++ and, similarly to Fig. 5 (right), the ratio of POWHEG predictions to those of NLOJET++. 8 Vincenzo Cavasinni HSQCD 2012

Figure 7: Dijet double differential cross section as a function of the dijet invariant mass for different intervals of the rapidity y∗ for 2010 (left) and 2011 data (right).The data are compared to the NLOJET++ predictions.

Figure 8: Ratios of the measured dijet cross section to the theoretical predictions obtained ∗ using NLOJET++ with the CT10 PDF set shown as a function of m12 , in bins of y . A comparison is also made with the POWHEG predictions in various configurations. 9

7 Search for new physics with jets

Many new physics effects predict final state with only jets, for instance dijet resonances from excited quark decays and supersymmetric particles production yielding jets and missing pT. The dijet invariant mass studies (jet-spectroscopy) have been pioneered by the UA2 experiment searching for W/Z decaying into quark pairs [10]. Fig. 9 (right) shows the result of the UA2 invariant dijet mass distribution after the subtraction of a continuum background: the W/Z signal is visible at the level of 4 standard deviations. Of course the better mass resolution (i.e. the jet-momentum resolution) the better will be the signal-to-background ratio, as schematically illustrated in the left plot of Fig. 9.

Figure 9: Cartoon illustrating a dijet mass resonance signal over a continuum background (left). The W/Z decays into jet pairs as measured by the UA2 experiment, after the continuum background subtraction, is shown in the right plot.

The ATLAS dijet invariant mass distribution is shown in Fig. 10 (left) [11]. There is no evidence of resonances: this allows to set a limit, excluding excited quarks with masses below 3.66 TeV at 95% C.L as shown in Fig. 10 (right). Supersymmetric (SUSY) partners of quarks (squarks) and gluons (gluinos) can decay in cascade with only jets and missing transverse energy in the final state. The effective mass (scalar sum of all transverse energies in the event) together with the missing trans- verse energy, is a powerful discriminant between signals and standard model background as shown in Fig. 11 [12]. A comparison is made with a simplified 0 SUSY model with a null neutralino (˜χ1) mass; the considered masses are those of the 10 Vincenzo Cavasinni HSQCD 2012

Figure 10: On the left, dijet invariant mass distribution compared to a continuum parametrization. On the right, limits on a resonance cross section times the experi- mental acceptance as a function of the dijet mass and comparison to an excited quark model.

Figure 11: Effective mass distribution in events with 2 or 5 jets. A comparison to the predictions of a model of supersymmetric particle production is shown. octet gluinos and of the first 2 generations squarks. The effective mass distributions are in agreement with the standard model expectations. This result can be presented as limits in the squark-gluino mass plane or in the MSUGRA/CMSSM m0 and m1/2 parameter plane as shown in Fig. 12. Limits at 95% C.L. are obtained for mgluino > 940 11

Figure 12: On the left, 95% limits in the squark-gluino masses plane. On the right, 95% limits in the MSUGRA/CMSSM m0 and m1/2 parameter plane.

GeV, msquark > 1380 GeV and m1/2 > 300 GeV (high m0), m1/2 > 680 GeV (low m0).

8 Conclusions

QCD accounts for jets physics in an excellent way. Search for new physics has been performed at (multi) TeV scale: no new phenomena, quantum black holes, excited quarks, quark compositness, supersymmetry have been discovered yet. The 2012 run at 8 TeV already collected ≈ 8fb−1 (25-30 fb−1 are expected by the end of the year). Jet-physics sensitivity (in jet pT , dijet mass) will increase quite significantly.

9 Acknowledgements

I wish to thank the organizers of HSQCD 2012, in particular Victor Kim, for their kind hospitality.

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