1 / 27

Prospectives of the Hadron Program in ATLAS

Prospectives of the Hadron Program in ATLAS. Regina Kwee CERN / Humboldt-Universität zu Berlin on behalf of the ATLAS- Collaboration. 5th International Conference on Quark and Nuclear Physics Beijing, 21.-26. September 2009. Outline. Introduction

linus
Download Presentation

Prospectives of the Hadron Program in ATLAS

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Prospectives of the Hadron Program in ATLAS Regina Kwee CERN / Humboldt-Universität zu Berlin on behalf of the ATLAS-Collaboration 5th International Conference on Quark andNuclearPhysics Beijing, 21.-26. September 2009

  2. Outline • Introduction • From soft tohardhadronPhysics in ATLAS • Minimum Bias Physics • Motivation for soft hadronphysics • Minimum Bias Trigger • Track reconstructionperformance • Resultsofthestudies • Underlying Event studies • Definition andimpactof UE tohigh-pTstudies • Analysis Plan with Early Data • Summaryand Outlook QNP 2009, IHEP Beijing

  3. Introduction ATLAShas ca. 25 m diameter, is 46 m long andweighs ~7000 t. InnerTrackersystem: Ø = 2.1 m, 6.2 m length, consistsof siliconpixel, siliconstripdetector (SCT),transitionradiationdetector (TRT) in a 2 T solenoidhomgenious magneticfield • ATLAS isoneofthe 4 majorexperimentsatthe Large HadronCollider (LHC) at CERN • Itcovers a widephysicsprogramandispreparedfor • Higgsdiscoveryat different masses • measurementsofdeviationsfromthe Standard Model • unknownsignatures • Goodunderstandingof soft hadronphysicsis also neccessaryforanyhigh-pTanalysis → First measurements will analysepropertiesofinelastic pp-collisions • Will beabletomeasurequantitieswhichareonlyknownwith large uncertaintiesat LHC energies, evenatinitialenergiesof√s = 7 and 10 TeV QNP 2009, IHEP Beijing

  4. Motivation for Soft Hadron Analyses • soft interactionsat LHC • canimproveknowledgeabout • inelasticscatteringprocesses • multi-partoninteractions • → ultimategoal: fundamental • descriptionof soft physics in QCD • representdetectoroccupancies • QCD-background in high-pTanalyses • influence • jetenergy-/missing ET-scale • leptonisolation • vertexdetermination • Higgs-searches in VBF Analysesof soft interactionscanpin-down inelasticcross-sectionsandarethebaseforanyhigh-pT-physicsanalysis • Thereare 2 mainhadronstudiesfor soft interactions • Minimum Bias (MB) • Underlying Event (UE) • Whyis soft physics relevant for LHC? With design parameters LHC runsat • √s = 14 TeV • bunchcrossing rate at 25 ns • luminosity L = 10³⁴/cm²s → highinteraction rate 10⁹ pp-interactions/second → expectpile-up ~ 25 pp-collisionsoverlapping in onebunch-crossing → highgluondensity gives rise to any QCD-cross-section QNP 2009, IHEP Beijing

  5. Multiple Parton Interactions • Cannotapplyperturbative QCD forlow Q² as • severalmodelsexsisttodescribe MPI • dual parton model • geometrical model • stochasticmodels • models in QCD framework • →measurements will improveunderstanding, • tune MC • The conceptof multiple partoninteractions (MPI) was introducedtodescribethatσint(parton-parton) exceededσtot(proton-proton) • UA5 datawere well fittedtomodelsbased on MPI, MPI hasbeendirectlymeasuredat CDF • UE and KNO-scaling variables arevery sensitive to MPI, typically • meanpTormeansumpTvs#particles • probabilitydistributionsfor multiple particleproductionas a functionof z = n/<n>, n=#particles QNP 2009, IHEP Beijing

  6. Definition of Minimum Bias • Minimum Bias eventscomprisecontributionsfrominelasticinteractions, hereshownfor √s = 14 TeVfor Pythia6.4 20 (Phojet1.12) : • In previousstudiesminimumbiaseventsareassociatedto ND and DD events (NSD, non-singlediffractive e.g. asat CDF) • Exactdefinitionisdefinedbythetriggersystem • At ATLAS wehave non- andboth-diffractiveevents, but • → ND eventsstronglydominate • Will also study NSD distributionsat ATLAS tocomparewithpreviousresults σndiff≈ 55 (68) mb σsdiff≈ 14 (11) mb σddiff≈ 10 (4) mb σcdiff≈ -/- (1) mb non-diffractive (ND) single-diffractivedissociation (SD) double-diffractivedissociation (DD) central-diffractive dissociation (CD) QNP 2009, IHEP Beijing

  7. Predictions for Soft Hadron Activities η = -ln(tan(θ/2)) CERN-OPEN-2008-020 14 TeV ND pythia ND phojet SD/DD phojet but will bestudiedat LHC/ATLAS SD/DD pythia pseudorapidityspectrum At LHC energiesthepropertiesofinelasticinteractionsarehighlyuncertain. • Predictionsfrom different modelshave large variations, e.g. in Pythia 6.420 (+ATLAS mc08 tune) andPhojet 1.12 on • inclusivecross-sections • chargedparticledensities • variations in √s from 10 TeVto 14 TeVis not very large QNP 2009, IHEP Beijing

  8. Predictions for Soft Hadron Activities CERN-OPEN-2008-020 14 TeV ND pythia ND phojet SD/DD pythia but will bestudiedat LHC/ATLAS SD/DD phojet transversmomentumspectrum At LHC energiesthepropertiesofinelasticinteractionsarehighlyuncertain. • Predictionsfrom different modelshave large variations, e.g. in Pythia 6.420 (+ATLAS mc08 tune) andPhojet 1.12 on • inclusivecross-sections • chargedparticledensities • variations in √s from 10 TeVto 14 TeVis not very large QNP 2009, IHEP Beijing

  9. Minimum Bias Physics • Strategyat ATLAS • Investigate pp-collisionsatthebeginningofdata-taking • → have a clean signalof a single pp-collision • pp-interaction rate is still verysmall in theinitialphase • L = 10²⁸/cm²s • 43 bunches • 2021 nsbunchspacing • expect in 10% ofthebunch-crossings a pp-collision • → Minimum-Bias Trigger • athigher pp-interaction rate → usepure randomtrigger • Minimum Bias Observables • chargedparticledensities • → pT-spectrum • → η-spectrum • KNO-variables ; multiplicityscaledvariables • <pT> vschargedparticlemultplicity • Analysis Requirements • introduceaslittletriggerbiasaspossible • performefficientlytrackreconstructionforlow –pTparticles (standardtrackingstartsat 500 MeV) QNP 2009, IHEP Beijing

  10. Minimum Bias Triggers MBTS InnerDetector ATLAS 2008-09-10 22:42:34 CEST run:87863 event:3939 Atlantis Event Display • Atinitiallow pp-interaction rate ATLAS uses 2 main Minimum Bias Triggers: • Minimum Bias Trigger Scintillators (MBTS) • consistof 16 counters per side • 32 read-out channels • covers 2.1 < |η| < 3.8 • Inner Tracking Detector (ID) based Minimum Bias Trigger • Level 1 Trigger(L1): randomtrigger • Level 2/Level 3 Trigger (L2/EF): use hits/tacksfromsilicondetector ( ~ 86 millionread-out channels) • covers ID-region: |η| < 2.5 • Additional supporttriggersareavailable eg. Zero-Degree-Calorimeter: triggeringonly on neutralsat +-140 m awayfrominteractionpoint (goodfordiffractiveevents) QNP 2009, IHEP Beijing

  11. MBTS Trigger Efficiency L1 Multiplicity mode:MBTS_2 L1 Coincidence mode:MBTS_1_1 verygoodefficiencyfor ND events ND ND DD highsuppressionofnoiseevents SD beamgas DD CERN-OPEN-2008-020 SD beamgas highsuppressionofnoiseevents CERN-OPEN-2008-020 • Trigger efficienciesfor different configurationsof MBTS • bothconfigurationhighlysuppress all emptybunch-brossingeventsandareveryefficientfor ND • MBTS_2: 2-hit-multiplicity triggerperformsoverallbetter QNP 2009, IHEP Beijing

  12. ID MinBias Trigger Efficiency L2 SpacePointCounter EF TrackCounter ND ND very good efficiency for ND events DD DD highsuppressionofnoiseevents SD SD CERN-OPEN-2008-020 CERN-OPEN-2008-020 beamgas beamgas • EF requires a certainnumberoftracksclosetothe IP • # trackswith |z0| < 200 mm • pTmin= 200 MeV • L2 requires a certainnumberofdetectorhits (SpacePoints) • formsspacepoints in pixeland SCT detector • operates just abovenoiselevel QNP 2009, IHEP Beijing

  13. Trigger Bias L2 SpacePointCounter + EF TrackCounter L1 MBTS_2 ND ND SD ID ID SD DD PoS(2008LHC)117 PoS(2008LHC)117 DD • Definetriggerbias a changeingenerateddistribution, introducedbythetriggerconditions • → bias = ratioof(hereshownforη) • generateddistributionwithtriggerconditions • plaingenerateddistribution • nobias in the relevant region (ID coverage) in ηexpectedfor MBTS_2 and ID Minbias Trigger • strong biasfordiffractivefor MBTS_1_1 expected (won‘tuseasphysicstrigger) QNP 2009, IHEP Beijing

  14. Track Reconstruction Efficiency trackingefficiencyasfunctionofpT • Standard-trackreconstructionimprovedforlow-pTtracks • → pTmin = 100 MeV (default: 500 MeV) • low-pTtrackreconstruction in 2 steps: • trackingefficiency = • numberofmatchedrec. primarytracks/ • numberofgeneratedprimarytracks CERN-OPEN-2008-020 pTmin= 100 MeV CERN-OPEN-2008-020 trackingefficiencyasfunctionofη QNP 2009, IHEP Beijing

  15. Event Selection and Corrections Track-To-Particlecorrection in η smallcorrections needed in centralregion (dependenceof Nch not shown) CERN-OPEN-2008-020 Track-to-Particlecorrection in pT needcorrections in lowpT-region (dependenceof Nch not shown) CERN-OPEN-2008-020 • Offline-selectioncriterium • eventcontainsoneprimaryreconstructedvertex • Correctionsfor • trigger (bias, efficiencies) • primaryvertexreconstruction • trackreconstruction → correctionsarefunctionsofprimarychargedparticlemultiplicity, pTandη • Estimateof total uncertaintiesis ~ 8% includingmainlycontributionsfrom[seeCERN-OPEN-2008-020] : • misalignment • diffractivecross-section (NSD sample) QNP 2009, IHEP Beijing

  16. Results for Minimum Bias CERN-OPEN-2008-020 CERN-OPEN-2008-020 14 TeV 14 TeV • Show NSD distributionswithpT >= 150 MeVfor√s = 14 TeV • Reconstructedandgenerateddistributions (pythia 6.420+ATLAS tune mc08) are in goodagreement → consistency check fortheanalysismethod QNP 2009, IHEP Beijing

  17. Underlying Event Topologial cut for UE studies • UE in hadron-hadroninteractionsisdefinedtoall particlesproduced accompanying the hard scattering component of the collision • Experimentially such separation is impossible → define regions sensitive to the UE • divide transverse plane into 3 regions based on the leading jet or leading track • Contributions to particle production in UE • convolution of initial and final state radiation • beam remnants and their interactions • multiple parton scattering • Predictions highly uncertain → Measurements will probe the sum of these effects and are needed to improve soft models and for tuning Monte Carlo models QNP 2009, IHEP Beijing

  18. Underlying Event Analysis Goals ATLAS-PUB-2005-015 • Underlying Event Observables • typicallyquantities in transverseregion: • chargedparticledensity • pT, <pT >, <ΣpT> oftracksandjets Measurement of UE helps distinguishing different physics models • Measure UE at different energies, • √s = 7 TeV, 10 TeV (14 TeV in ~ 4-5 yrs) → 1< Ldt< 10 pb-1alreadyusefulfor UE studies, but needto understand thesystematicsfirst QNP 2009, IHEP Beijing

  19. from Minimum Bias Analysis walkthrough, 8th September 2009 Analysis Plan with Early Data 1 day 7 TeV (100k evt) dN/dη, dN/dpT Few days at 7 TeV (1 M evt) KNO scaling,<pT> vs N, UE 1 day 900 GeV (50k evt) dN/dη, dN/dpT time pT> 500 MeV barrel only low-pt tracking endcap region understand material improve systematics • Should collect enough tracks very quickly, depending on beam and detector stability. • Limitation is not set by statistics but by systematics • Tracking and trigger perfomance need to be understood • Day 1 data : • focus on pT >500 MeV and barrel region: • lose events •  gain confidence on systematics • Prepare for low-pT tracking at 7 TeV QNP 2009, IHEP Beijing

  20. Summaryand Outlook • Base for a successful ATLAS phyicsprogrammeisto understand asgoodaspossible soft QCD physics in LHC enviroment • Minimum Bias studies→ particlesdenisities, originof KNO-scalingviolations, inelasticcross-sections, pile-updescription • Underlying eventsstudies→ determineconstituentsof UE, reducesystematicuncertainties(jetenergy, missing ETandleptonisolation,…) → bothstudiesvaluabletoimprovetheoryand MC models • ATLAS provides a detailedstrategyfortriggerandearlydataanalyses • analysismethodis in goodshape • toolshavebeenmuchimprovedsince 14 TeVstudies • MB and UE studiesare just thebeginningof an excitingphysicsprogram! Formore on earlyhadronphysicsanalyses, see talk byK.Hara QNP 2009, IHEP Beijing

  21. backup QNP 2009, IHEP Beijing

  22. Plan for LHC Scenarios from http://lhccwg.web.cern.ch/lhccwg/ LHC-Betriebs-Szenarien QNP 2009, IHEP Beijing

  23. Impact of UE toPhyicsAnalyses • Determination of JES forhigh PT Jets • Method: Jet-balancing, e.g.: • → take 1-jet eventsasΣ ET = 0: • 1 jet + Z → 2μ : Z massisvery well known • balancejet ET /jet PT • determine JES for • 10 GeV< PT < ca. 200 GeV • 1 jet + γfor • ca. 100 GeV < PT < ca. 200 GeV • uncertainties [arXiv.0901.0512] from JES for • PT < 100 GeV: ~ 10 % • PT > 100 -500 GeV: ~ 1-2 % • statisticalerror[arXiv.0901.0512] on JES for 100pb-1is 1-2 % • The uncertaintyofthejetenergyscale (JES) is a principaluncertaintyto all analyseswithjet ET-measurements, e.g. • top quarkmass • Higgsproduction in VBF • leptonisolation • moresignificantimpactof UE forlow-PTjets QNP 2009, IHEP Beijing

  24. Analysis Sketch Monte-Carlo-models e.g. Pythia, Phojet Trigger providesinelastic pp-collisions σndiff, σsdiff, σddiff withsystematicuncertainties Offline-Software Offline-Software compareto MC improveMC+detectorsimulation (alignment, material) reconstruct tracksandvertices study: biasandeffizienies reconstruct: tracksandvertices dNch/dη dNch/dpT Measurement withdata Analysis with MC QNP 2009, IHEP Beijing

  25. Acta Phys. Polonica, No.5, Vol. B19(1988), Ina Sarcenic MPI Models • stochasticmodel • scalingrelatestogeneralstatisticalanddynamicalpropertiesof MPI • describeprobabilitydistribution e.g. with negative binominal model (Fourier-Transform ofPoissonian) → fits well UA5 data • or • use Fokker-Planck eq. todescribe MPI as a stochastic-dissipative process • models in QCD • → MPI havecontributionsfromquarkandgluonbremsstrahlung • (parton-branching) • dual parton model • assumehadronseperates after collisioninto 2 coloredsystems: quarkand di-quark • gluons mediate interaction, producequark-antiquarkpairs → increasere-scatteringcomponent → MPI • geometrical model • probabilitydistribution (in KNO-scaling) is a superpositionofmanyPoisson-distributions, characterisedbyimpactparameter b. → thehighertheenergy, themoreforward-backwardmultiplicity QNP 2009, IHEP Beijing

  26. QNP 2009, IHEP Beijing

  27. L1 MBTS_1_1 PoS(2008LHC)117 • strong biasfordiffractivefor MBTS_1_1 expected (won‘tuseasphysicstrigger) Trigger biasfor L1 MBTS_1_1 QNP 2009, IHEP Beijing

More Related