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

The structure of an event 2 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

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

Resonances 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

The structure of an event: ISR 5 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

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

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)

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

Underlying Event 9 Studying underlying event is crucial for understanding high p T SM events at LHC. ingredient for many analyses. In fact they affect: the jet reconstructions and lepton isolation, jet tagging etc.. One can look at charged track multiplicities N ch in transverse regions which are little affected by the high p T objects. Reasonably described by models

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.

Pile up ATLAS event; Z in  with 25 primary vertices Z in  event with 25 vertices

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 E t ~ 58 GeV E t ~ 81 GeV without pile-up Prog.Part.Nucl.Phys.6 0: ,2008 Pile up

E t ~ 58 GeV E t ~ 81 GeV with design luminosity pile-up Prog.Part.Nucl.Phys.6 0: ,2008 Pile up 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

Challenge Pile up: example E T miss 14 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. without PU suppression with PU suppression Important for quantities, affected by soft hadrons, for example; E T miss = -| Σ pT | Use data!

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?) Minimum bias events  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”?  At least for the beam-beam remnant and multiple interactions? The underlying event  The “soft part” associated with hard scatters

Minimum bias 16 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 Δp ~ h/Δx Distributed uniformly in η: dN/d  = 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

Minimum bias 17 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

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 ?

Monte Carlo for Processes with jets

Parton shower

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

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

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

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

SM processes 26 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!

QCD Sector

Snapshot of QCD

QCD vertices

Colour factors

QCD Potential

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

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

Multi-jet events at LHC

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

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

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

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

What is a jet?

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

Jets 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 41 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

jet algorithms

Jet Reconstruction Task

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

Jet reconstruction algorithms: cone

Jet reconstruction algorithms: K t

Di-jet quark flavours arXiv: v3

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)

Jet physics: JES calibration from data 49 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

Jet production 50 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, % inclusive jet data : starts to be important tool for constraining PDFs, eg.also by using ratios at different c.o.m. energies