Physics at Hadron Colliders Part II

Transcription

1 Physics at Hadron Colliders Part II Marina Cobal Università di Udine 1

2 The structure of an event One incoming parton from each of the protons enters the hard process, where then a number of outgoing particles are produced. It is the nature of this process that determines the main characteristics of the event. Hard subprocess: described by matrix elements 2

3 An event: resonances The hard process may produce a set of short-lived resonances, like the Z0/W± gauge bosons. 3

4 In this range the momentum scale is known at the permill level. it is a cross-check of the detector performance in particular for the lepton energy measurements Resonances 4

5 The structure of an event: ISR One shower initiator parton from each beam may start off a sequence of branchings, such as q qg, which build up an initial-state shower. Initial state radiation: spacelike parton shower 5

6 The structure of an event: FSR The outgoing partons may branch, just like the incoming did, to build up final-state showers. Final state radiation: timelike parton showers 6

7 An event: Underlying events Proton remnants ( in most cases coloured! ) interact: Underlying event,consist of low p T objects. There are events without a hard collision ( dependent on p T cutoff)

8 An event: Underlying events Underlying event: Multi-parton interaction Beam-beam remnants Initial/final state radiation

9 Underlying Event Studying underlying event is crucial for understanding high p T SM events at LHC. - = 3 Leading Charged-Particle Jet = 0 Toward Region = 3 ingredient for many analyses. In fact they affect: the jet reconstructions and lepton isolation, jet tagging etc.. = -2 3 Transverse Region Away Region Transverse Region = 2 3 One can look at charged track multiplicities N ch in transverse regions which are little affected by the high p T objects. > [GeV] T <p R=0.2 Transverse region Reasonably described by models ATLAS 1.2 MC/DATA jet p [GeV] T 9

10 The structure of an event: Pile up In addition to the hard process considered above, further semi-hard interactions may occur between the partons of two other incoming hadrons. Pile-up is distinct from underlying events in that it describes events coming from additional proton-proton interactions, rather than additional interactions originating from the same proton collision.

11 Pile up 2012 ATLAS event; Z in µµ with 25 primary vertices Z in µµ event with 25 vertices 11

12 Multiple interactions between partons in other protons in the same bunch crossing Consequence of high rate (luminosity) and high proton-proton total cross-section (~75 mb) Pile up without pile-up E t ~ 58 GeV E t ~ 81 GeV Statistically independent of hard scattering Similar models used for soft physics as in underlying event Prog.Part.Nucl.Phys. 60: ,2008

13 Multiple interactions between partons in other protons in the same bunch crossing Consequence of high rate (luminosity) and high proton-proton total cross-section (~75 mb) Pile up with design luminosity pile-up E t ~ 58 GeV E t ~ 81 GeV Statistically independent of hard scattering Similar models used for soft physics as in underlying event Prog.Part.Nucl.Phys. 60: ,2008

14 Challenge Pile up: example E T miss Important for quantities, affected by soft hadrons, for example; E T miss = - Σ pt without PU suppression with PU suppression Use data! Requirements on track vertexing Number of reconstructed vertices proportional to the pile-up Measure pile-up density event by event: Use it to subtract from the jets energy a pile-up term. do the same with isolation cones. 14

15 Minimum bias events Inelastic hadron-hadron events selected with an experiment s minimum bias trigger. Usually associated with inelastic non-single-diffractive events (e.g. UA5, E735, CDF ATLAS?) The underlying event The soft part associated with hard scatters σ tot = σ EL +σ SD +σ DD +σ ND Need minimum bias data if want to: 1) Study general characteristics of proton-proton interactions 2) Investigate multi-parton interactions and the structure of the proton etc. 3) Understand the underlying event: impact on physics analyses? In parton-parton scattering, the UE is usually defined to be everything except the two outgoing hard scattered jets: Beam-beam remnants. 1) Additional parton-parton interactions. 2) ISR + FSR Can we use minimum bias data to model the underlying event? Ø At least for the beam-beam remnant and multiple interactions?

16 Minimum bias Non head-on collisions, with only low p T objects. Those are the majority of the events in which there is a small momentum transfer p ~ h/ x Distributed uniformly in η: dn/dη = 6 On average the charged particles in the final state have a p T ~500 MeV Not well described by models! Shape is sort of OK Normalisation is off 16

17 Minimum bias It is interesting by its own to study such events. Also an ingredient for many analyses you will see. A necessary first step for precision measurements (such as top-quark mass) A key ingredient to modelling pile-up As can be seen most of the events do have quite low pt Anyhow those events constitute a noise of few GeV per bunch crossing 17

18 Monte Carlo Simulations Attempt to simulate all physics and experimental aspects as well as possible in MC Examples shown here: Pile-up Jet response Electron acceptance on detector level Corrections from quark to jets Use data ('data-driven' techniques) to verify that MC is correct w.r.t all relevant aspects 18 / Response Response MC Data Non-perturbative correction s = 2.76 TeV anti-k t R=0.6 y <0.3 Pythia 6 AMBT2B CTEQ6L1 Pythia 6 AUET2B LO** Pythia 6 Perugia 2010 Pythia 8 4C Herwig UE Pythia 6 AUET2B CTEQ6L1 Uncertainty 2 10 (b) R = 0.6 ATLAS Preliminary Simulation 2 10 jet p [GeV] 2 10 p [GeV] T Figure 2: Non-perturbative correction factors for the inclusive jets cross section for anti-k t jets with R = 0.4(a)andR = 0.6 (b) in the jet rapidity y < 0.3 as a function of the jet p T for Monte Carlo simulations 1 R = 0.4, LCW+JES anti-k t Data jet Z +jet Multijet ATLAS Preliminary s = 8 TeV, < 0.8 Total in situ uncertainty Statistical component T 3

19 Monte Carlo Simulations MC contains two aspects description of detector response efficiency, resolutions description of shapes (physics model) acceptance This allows to translate the cross section measurement into a determination of a correction: N.B. assuming good description of efficiency and acceptance by MC uncertainty? 19

20 Monte Carlo for Processes with jets

21 Parton shower

22 erstanding of LHC physics. The construction, maintenance, validation and extension of event is therefore one of the principal tasks of particle-physics phenomenology today. MC simulation of LHC event t" H" t" Detector simulation Particles Hadronisation p" ictorial representation of a t th event as produced by an event generator. The hard interaction (big ed blob) is followed by the decay of both top quarks and the Higgs boson (small red blobs). Additional ard QCD radiation is produced (red) and a secondary interaction takes place (purple blob) before he final-state partons hadronise (light green blobs) and hadrons decay (dark green blobs). Photon adiation occurs at any stage (yellow). p" QCD and QED radiation Hard partonic scattering Incoming parton distributions Additional partonic scatters

23 A Monte Carlo Event Modelling of the soft underlying event Multiple perturbative scattering. Hard Perturbative scattering: Usually calculated at leading order in QCD, electroweak theory or some BSM model. Perturbative Decays calculated in QCD, Initial and EW Final or some State BSM parton showers resum the large QCD Finally the unstable theory. logs. hadrons are decayed. Non-perturbative modelling of the hadronization process.

24 Uncertainties Statistical uncertainties, due to finite number of events Systematic uncertainties, due to errors and biases in the analysis Simplest, most-often-used approach: assume that systematic errors are mutually independent, i.e. uncorrelated make list of all sources of systematic uncertainties remove those that are correlated with others repeat analysis for variation of each uncertainty separately add variations up in quadrature More complex treatment of systematics not addressed today Most analysis work goes into dedicated studies aiming to minimize the systematic uncertainty 24

25 Table of uncertainties Example: CMS top pair production in di-lepton channel Experimental aspects Theory uncertainties backgrounds. Source e + e µ + µ e ± µ Trigger efficiencies Lepton efficiencies Lepton energy scale Jet energy scale Jet energy resolution b-jet tagging Pileup Scale (µ F and µ R ) Matching partons to showers Single top quark VV Drell Yan Non-W/Z leptons Total systematic Integrated luminosity Statistical e + e µ + µ e ± µ e total (%) ± ± ± s tt (pb) ± 5.2 ± 18.6 ± ± 4.5 ± 18.6 ± ± 2.6 ± 11.4 ± 6.2

26 SM processes No hope to observe light objects ( W,Z,H) in the fully hadronic final state! We need to rely on the presence of an isolated lepton! Fully hadronic final states can be extracted from the backgrounds only with hardo(100 GeV) pt cuts-> works for heavy objects! 26

27 QCD Sector

28 Snapshot of QCD

29 QCD vertices

30 Colour factors

31 QCD Potential

32 Jets from quarks and gluons Quarks and gluons cannot exist as free particles -> hadronization Collimated stream of charged and neutral hadrons -> QCD jets

33 Where do Jets come from at LHC? Fragmentation of gluons and (light) quarks in QCD scattering d σ 2 nb d ηdp T TeV η=0 inclusive jet cross-section s =1.8 TeV s =14 TeV Most often observed interaction at LHC p T (TeV)

34 Multi-jet events at LHC

35 Jet multiplicity Another possible test of QCD is obtained by checking the jet multiplicity Tests also the modelling of the radiation 35

36 Where do Jets come from at LHC? Decay of heavy Standard Model (SM) particles Prominent example: t bw jjj t bw lν j top mass reconstruction qq% qʹ ʹ q% WW Hjj

37 Where do Jets come from at LHC? Associated with particle production in Vector Boson Fusion (VBF) E.g., Higgs

38 Where do Jets come from at LHC? Decay of Beyond Standard Model (BSM) particles E.g., SUSY M l ef f pt, j pt, jets leptons = + + p T missing transverse energy jets electrons or muons

39 What is a jet?

40 How to identify jets? Jet algorithm should collect all particles in the same way for: Leading order partons Partons+gluon emission Parton shower (soft) Hadrons-> detector

41 Definition (experimental point of view): bunch of particles generated by hadronisation of a common confined source Quark, gluon fragmentation Jets Signature Energy deposit in EM and HAD calorimeters Several tracks in the inner detector Calorimeter energy measurement - Gets more precise with increasing particle energy - Gives good energy measure for all particles except µ s and ν s - Does not work well for low energies - Particles have to reach calorimeter, noise in readout 41

42 jet algorithms

43 Jet Reconstruction Task

44 Jet Reconstruction How to reconstruct the jet? Group together the particles from hadronization 2 main types Cone kt 44

45 Jet reconstruction algorithms: cone

46 Jet reconstruction algorithms: Kt

47 arxiv: v3 Di-jet quark flavours

48 Jet physics: jet energy scale Before looking at jet physics be aware of few issues, first of all when we have steeply falling cross sections-> we have a sensitivity of its measurement from the energy scale -Jet energy determined from calorimeter (+tracking information) -Sophisticated calibration procedure Different contributions to JES error. (jets reconstructed with the Anti-kT alogrithm cone 0.6 that is used in ATLAS)

49 Jet physics: JES calibration from data Different physics processes can be used to calibrate the JES. - recoil against Z and photons -reconstruction of W s in ttbar events Such methods are useful for different energy ranges and can be used at different ECM 49

50 Jet production NLO QCD works over ~9 orders of magnitude! excellent exp. progress: jet energy scale uncertainties at the 1-2% level for central rapidities: similar exp. and theo. uncertainties, 5-10% inclusive jet data : starts to be important tool for constraining PDFs, eg.also by using ratios at different c.o.m. energies 50