Marina Cobal Università di Udine

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

2. The structure of an event Oneincomingparton from each of the protons enters the hard process, wherethen a number of outgoingparticles are produced. Itis the nature of thisprocessthatdetermines the main characteristics of the event. Hard subprocess: described by matrixelements

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

4. Resonances •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

5. The structure of an event: ISR Oneshowerinitiatorparton from eachbeammay start off a sequence of branchings, suchasq → qg, whichbuild up an initial-state shower. Initial state radiation: spacelikepartonshower

6. The structure of an event: FSR The outgoingpartonsmaybranch, just like the incomingdid, to build up final-state showers. Final state radiation: timelikepartonshowers

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

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

9. Underlying Event • Studyingunderlyingeventiscrucial for understanding high pT SM eventsat LHC. • ingredient for manyanalyses. In facttheyaffect: the jet reconstructions and leptonisolation, jet tagging etc.. • One can look atchargedtrackmultiplicities • Nch in transverseregionswhich are littleaffected by the high pTobjects. • Reasonablydescribed by models

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’inthat 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 mm with 25 primary vertices Z in mm event with 25 vertices

12. Pile up without pile-up Et ~ 81 GeV Et ~ 58 GeV Prog.Part.Nucl.Phys.60:484-551,2008 • 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) • Statistically independent of hard scattering • Similar models used for soft physics as in underlying event

13. Pile up with design luminosity pile-up Et ~ 81 GeV Et ~ 58 GeV Prog.Part.Nucl.Phys.60:484-551,2008 • 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) • Statistically independent of hard scattering • Similar models used for soft physics as in underlying event

14. Challenge Pile up: example ETmiss Important for quantities, affected by soft hadrons, for example; ETmiss = -| 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.

15. Minimum bias events The underlying event • The “soft part” associated with hard scatters • 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?) • In parton-parton scattering, the UE is usually defined to be everything except the two outgoing hard scattered jets: • Beam-beam remnants. • Additional parton-parton interactions. • ISR + FSR • Need minimum bias data if want to: • Study general characteristics of proton-proton interactions • Investigate multi-parton interactions and the structure of the proton etc. • Understand the underlying event: impact on physics analyses? • Can we use “minimum bias” data to model the “underlying event”? • At least for the beam-beam remnant and multiple interactions?

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

17. Minimum bias • Itisinteresting by itsown to studysuchevents. Also an ingredient for manyanalysesyouwillsee. • A necessary first step for precisionmeasurements (suchas top-quark mass) • A keyingredient to modelling pile-up • As can be seenmost of the events do havequitelowpT • Anyhowthoseeventsconstitute a noise of fewGeV per bunchcrossing

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 • Apply corrections (a.k.a. scale factors) to MC where necessary

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 ?

20. Monte Carlo for Processes with jets

21. Parton shower

22. MC simulation of LHC event Detector simulation Particles Hadronisation QCD and QED radiation Hard partonic scattering Incoming parton distributions Additional partonic scatters

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

25. Table of uncertainties Example: CMS top pair production in di-lepton channel Experimental aspects Theory uncertainties backgrounds

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!

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? inclusive jet cross-section • Fragmentation of gluons and (light) quarks in QCD scattering • Most often observed interaction at LHC

34. Multi-jet events at LHC

35. Jet multiplicity • Anotherpossible test of QCD is • obtained by checking the jet multiplicity • Testsalso the modelling of the • radiation

36. top mass reconstruction Where do Jets come from at LHC? • Decay of heavy Standard Model (SM) particles Prominent example:

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

38. missing transverse energy electrons or muons jets Where do Jets come from at LHC? • Decay of Beyond Standard Model (BSM) particles • E.g., SUSY

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

42. jet algorithms

43. Jet Reconstruction Task

44. Jet Reconstruction • Howtoreconstructthejet? • Group togethertheparticlesfromhadronization • 2 maintypes • Cone • kT

45. Jet reconstruction algorithms: cone

46. Jet reconstruction algorithms: Kt

47. Di-jet quark flavours arXiv:1210.0441v3

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 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