hcal and jet/met

CMS 101++ June 18-20, 2008 1Frank Chlebana, Fermilab

HCAL and Jet/METHCAL and Jet/METHCAL and Jet/METHCAL and Jet/MET

CMS 101++June 18, 2008

Frank Chlebana, Fermilab


OutlineOutlineOutlineOutline

• Calorimeters• The CMS Hadronic Calorimeters• Jet Clustering Algorithms• Problems with Clustering Algorithms• Jet Energy Corrections• Resources• How You Can Get Involved• The Challenge


Energy Loss in MaterialsEnergy Loss in MaterialsEnergy Loss in MaterialsEnergy Loss in MaterialsElectromagnetic shower in a cloud chamberAlternating layers of “absorbers” and “active” material

Energy loss through Bremstrahlung and pair production

Pair production continues until photons’ energy is too low to produce pairs

Low energy particles dissipate energy through ionization

Hadronic showering is more complicated than EM showering Involves strong and weak interactions

Scintillator samples the number of particles in each layer → energy


ShoweringShoweringShoweringShowering

Energy resolution for HAD calorimeters are typically worse than for EM calorimeters

Neutrinos escape undetected

Muons unlikely to Bremstrahlung and dissipate energy

Long lived particles (KS, KL, Λ) may escape before decaying or interacting

Simulation of a cosmic shower induced by a 250 GeV proton compared to a 250 GeV photon

Hadronic showers start later and have a greater lateral spread than EM showers


Components of CMSComponents of CMSComponents of CMSComponents of CMS

HCAL ForwardCalorimeter

ECAL


Barrel (HB) and EndBarrel (HB) and Endcap (HE) Calorimeterscap (HE) CalorimetersBarrel (HB) and EndBarrel (HB) and Endcap (HE) Calorimeterscap (HE) Calorimeters

Passive layers of brass to induce showering

About 5% of the light is captured in the fiber

Fibers sent to a Hybrid PhotoDiode (HDP) with 19 or 73 channels/device

Similar technology used for HB and HE calorimeters

Light readout via an optical fiber doped with wavelength shifter acting as light guide

Fiber is placed in a groove in the scintillator, absorbs scintillator light, re-emits it


Barrel and Endcap CalorimetersBarrel and Endcap CalorimetersBarrel and Endcap CalorimetersBarrel and Endcap Calorimeters

Barrel (HB) |η| < 1.3EndCap (EB) 1.3 < |η| < 3.0

Calorimeters installed and being read out during global runs

Barrel (HB)

Endcap (HE)


Forward Calorimeter (HF)Forward Calorimeter (HF)Forward Calorimeter (HF)Forward Calorimeter (HF)

HF is located about 11 m from the interaction point, covers 3 < |η| < 5

Choice of technology driven by the need to operate in a very high radiation environment

Consists of a large copper block which acts as an absorber embedded with quartz fibers parallel to the beam direction

HAD (143 cm)

EM (165 cm)

5mm

Particles incident on the front surface produce showers in the quartz/copper matrix which produce Cherenkov light


Outer Calorimeter (HO)Outer Calorimeter (HO)Outer Calorimeter (HO)Outer Calorimeter (HO)In the central region (|η|<1.3) HB does not fully contain very energetic hadron showers

Color coding shows depth segmentation

Additional scintillator layers (HO) are located outside the solenoid (which acts as an absorber)

HO used to identify late starting showers and measure energy deposited after HB


Calorimeter ResolutionCalorimeter ResolutionCalorimeter ResolutionCalorimeter ResolutionExperiment Material

(HAD)Resolution EM

ResolutionHAD

ZEUS Uranium – Scintillator

H1 Lead/Steel – Liquid Argon

CDF Iron – Scintillator

DØ Uranium – Liquid Argon

CMS Brass - Scintillator

Atlas Copper – Liquid Argon

E/%17 E/%35

%1/%11 E %2/%50 E

%2/%5.13 E %3/%50 E

%4/%45 E

%5.4/%100 E

%3/%50 E

%3.0/%8.2 E

E/%15

%2.0/%10 E


CaloTowersCaloTowersCaloTowersCaloTowersMost users will access the reconstructed dataDigitized Data → Reconstructed Hits → CaloTowers

CaloTowers are made up from multiple EM Crystals (5x5) and several Hadron sections

Jet clustering uses CaloTowers

Detector/electronics relatedproblems need to be identified before “rechits” are madeMore on this later…


Jet ClusteringJet ClusteringJet ClusteringJet Clustering

After the hard interaction, partons hadronize into stable particles

Stable particles interact with the detectors

Jet algorithms cluster energydeposits in the EM and HAD calorimeter, or more generally four-vectors

Jet algorithms should provide a good correspondence between what is observed and the hard interaction


Clustering AlgorithmsClustering AlgorithmsClustering AlgorithmsClustering Algorithms

Cone-based clustering algorithms: Cone-based algorithms have been traditionally used at hadron colliders Interaction between theorists and experimentalists lead to the evolution of a practical Seedless Infrared Safe Cone algorithm JetClu → Midpoint → SISCone

Sequential combination:kT, Jade and Cambridge/Aachen Merges pairs of four-vectors in order of increasing relative pT

Continues until some stopping requirement is reached Does not have the problems associated with seeded cone algorithms Have been slow to execute (faster version is now available) Jet area not is well defined

Online selection: Select events using towers and clusters Limited by processing time Simplified algorithm (iterative cone) with fixed vertex


Steps in a Clustering AlgorithmSteps in a Clustering AlgorithmSteps in a Clustering AlgorithmSteps in a Clustering Algorithm

Start from a collection of four-vectors, highest pT acts as seed

Sum all four-vectors within cone to form a proto-jet

Repeat until proto-jet is stable (axis of proto-jet aligns with the sum of four-vectors within the cone) or reach maximum number of iterations

Repeat until all towers are usedApply splitting/merging algorithm to ensure four-vectors are assigned to only one proto-jet

→ Left with list of all stable jets


Algorithm Flow ChartsAlgorithm Flow ChartsAlgorithm Flow ChartsAlgorithm Flow Charts

Clustering Algorithm Merging/Splitting Algorithm


Problems with Problems with SomeSome Clustering Algorithms Clustering AlgorithmsProblems with Problems with SomeSome Clustering Algorithms Clustering Algorithms

The addition of a threshold to the seed towers makes the algorithm “collinear unsafe”

Seed based cone algorithms are “infrared unsafe”

Addition of an an infitisimally soft particle can lead to new stable jet configurations → sensitive to hadronization model and order of perturbative QCD calculation

Problems arise when comparing to higher order p-QCD calculations


Performance of Different Jet Performance of Different Jet AlgorithmsAlgorithms

Performance of Different Jet Performance of Different Jet AlgorithmsAlgorithms

Midpoint leaves unclustered towers

Dark Towers

Different jet algorithms find different jets in the same event

Midpoint

kT Clustering

JetClu

kT has jets with poorly defined boundaries

Used by CDF


Jet Energy CorrectionsJet Energy CorrectionsJet Energy CorrectionsJet Energy Corrections

Factorized JEC:Each step uses a well defined methodology and one or two datasetsL1: pile-up and noise measured in ZB/MB events.L2: jet response vs. η relative to the barrel using dijet

balance.L3: jet response vs PT found in barrel using g/Z + jets,

top quark decays…L4: improves jet energy resolution by employing

additional parameterization of JES vs. jet EMF L5-L7: corrects for flavor variations, UE, and brings jet to

parton level.

Room to get involved in all areas of the JEC…


Corrected Dijet MassCorrected Dijet MassCorrected Dijet MassCorrected Dijet Mass

Reconstructed dijet mass distribution for Z’ events

GenJet: clustered stable particles,does not include detector effects, includes neutral particles

“Best” that we can do

CaloJet: clustered calorimeter jets, uncorrected

Corrected CaloJet: jet correctionsapplied to the calorimeter jets

Try to improve the resolution by using information from other detectors


Improving the ResolutionImproving the ResolutionImproving the ResolutionImproving the Resolution

Gaussian signal on top of a falling background spectrum (red)

Better resolution →improved Signal/Background

A small improvement in the resolution can lead to a largeimprovement in the sensitivity for new physics

Improving mjj resolution from 17 to 10% is like have 1.7x more data for some Higgs search channels at CDF

Run longer or work smarter…

±1σ


Energy vs Momentum ResolutionEnergy vs Momentum ResolutionEnergy vs Momentum ResolutionEnergy vs Momentum Resolution

Can use tracking information to improve jet resolution

33.03.04

7202

BL

p

npT

T

pT

Calorimeter energy resolution becomes better as E increases while the tracker’s momentum resolution becomes worse

Jet algorithms using tracking and particle identification (Jet+Tracks and Particle Flow) are available…

For: n=100, B=1T, L=1m, σ=250μm

» 250 GeV/c we can’t reliably measure the charge of the particle at the 3σ level


Jet Resolution ImprovementsJet Resolution ImprovementsJet Resolution ImprovementsJet Resolution ImprovementsWe do see that algorithms that make use of tracking detectors yield jets with improved resolution

Comparison of:

Calorimeter JetsParticle FlowJets + Tracks

Will be interesting to compare resolutionswhen we have real dataMore challenging environment


Understanding METUnderstanding METUnderstanding METUnderstanding MET

DØ (V.Shary CALOR04)

Many important signatures involve Jets + Missing ET

Identify and treat:

Calorimeter noiseDead ChannelsHot ChannelsHDP dischargeHDP ion feedback

Use the global run data to look at real data…Plenty to do in the area of Data Quality Monitoring and a great place to get involved


HCAL Readout in Global RunsHCAL Readout in Global RunsHCAL Readout in Global RunsHCAL Readout in Global Runs• Sample of 1000 events from a Global Run• Full calibrated reco chain with ICone5 Jets

• Includes DT, DTTF, HCAL, TRK, TRG subsystems

• HCAL: HB, HE+, HO• Trigger on DT at ~45 Hz

ET of CaloJets

Plots from: Daniel Miner,University of Rochester

Lots to understand…

Important and a fun place to get involved

Puts you at an advantage to get out early physics results

φ

η


Points of FailurePoints of FailurePoints of FailurePoints of Failure

So far only considered a small part of the readout chain…


Data Quality MonitoringData Quality MonitoringData Quality MonitoringData Quality MonitoringBefore we can use the data for physics analysis we need to ensure we are collecting good data and understand the readout and detector problems

Need to develop tools to clean up the data and treat bad channels

Understand beam conditions and developselection criteria to

Establish a solid foundation from which to build on…


Specific Projects/TasksSpecific Projects/TasksSpecific Projects/TasksSpecific Projects/TasksSome specific studies

Help with tuning FastSimNoise, Pileup correction to the JES Optimization of split/merging Cell energy threshold optimizationJet ID and cleanupUse of tracks in Jets and PFlowType II corrections (MET)

MET significanceMET reconstruction and performanceIntegration of Jet and MET in PATCode maintainersValidation of Data Mixing ModuleImplementation of simulation uncertainty capabilityHLT trigger objects and performance

Come talk to one of the convenersJetMET, JetAlgo, MET, JEC (See JetMET org chart)


CMS JetMET OrganizationCMS JetMET OrganizationCMS JetMET OrganizationCMS JetMET Organization

Missing ETGreg LandsbergFilip Moortgat

Jet AlgorithmsPhilipp Schieferdecker

Marek Zielinski

TasksTasks

ValidationFrank ChlebanaValidation

Frank Chlebana

Physics ToolsAttilio SantocchiaPhysics Tools

Attilio Santocchia

JetMET GroupG. Dissertori

D. Elvira

Simulation/CSA07Joanna Weng

Simulation/CSA07Joanna Weng

SoftwareRobert Harris (Jet)

Fedor Ratnikov (Jet)Bobby Scurlock (MET)

SoftwareRobert Harris (Jet)

Fedor Ratnikov (Jet)Bobby Scurlock (MET)

Documentation/User SupportFedor Ratnikov

Documentation/User SupportFedor Ratnikov

Trigger PerformanceJochen Cammin

Trigger PerformanceJochen Cammin

Online SelectionLenny Apanasevich

Online SelectionLenny Apanasevich

HCAL DPGOlga KodolovaTaylan Yetkin

HCAL DPGOlga KodolovaTaylan Yetkin

Particle Flow/Joanna Weng

Alexandre Zabi

Particle Flow/Joanna Weng

Alexandre Zabi

ECAL DPGDaniele Del ReECAL DPG

Daniele Del Re

Jet Energy ScaleRobert Harris

Ia Iashvilli

Group RepresentativesGroup Representatives

Red indicates person resident at LPC


CMS Jet/MET Group: V.Daniel Elvira, G.Dissertori ([email protected])

https://twiki.cern.ch/twiki/bin/view/CMS/JetMET

Jet Energy Correction: R.Harris, Ia Lashvili ([email protected])

MET Group: G.Landsberg, F.Moortgat ([email protected])

Jet Algorithms: M.Zielinski, P.Schieferdecker ([email protected])

HCAL DPG: M.Velasco, V.Gavrilov ([email protected])

https://twiki.cern.ch/twiki/bin/view/CMS/HcalDPG

LPC Jet/MET Group: M.Zielinski, F.Chlebana ([email protected])

http://www.uscms.org/LPC/lpc_jetmet/lpc_jm.html

Denotes USCMS Member

Mailing Lists and ContactsMailing Lists and ContactsMailing Lists and ContactsMailing Lists and Contacts

https://hypernews.cern.ch/HyperNews/CMS/cindex


There is a lot of local expertise at the LPCContact a convener to discuss your interest, see list from previous slide

Some documentation:CMS: Technical Design ReportDetectors: “Experimental Techniques in High Energy, Nuclear, and

Particle Physics”, T.FerbelJet Algorithms: “Run II Jet Physics hep-ex/0005012”

Examples, Code Browser, and Database Lookuphttps://twiki.cern.ch/twiki/bin/view/CMS/WorkBookJetRecohttp://cmssw.cvs.cern.ch/cgi-bin/cmssw.cgihttp://cmsdbs.cern.ch/DBS2_discovery

ResourcesResourcesResourcesResources


The ChallengeThe ChallengeThe ChallengeThe ChallengeLater on during the workshop you have the opportunity to attend tutorials on running jobs and finding datasets

Best way to gain experience is to get your hands dirty, so….

1)Reproduce plot for the Z’ dijet mass resolution2)Add resolution for Jet+Tracks algorithm

Hints:

Look at WorkBook for some examples DBDiscovery to find datasets Code Browser useful to find examples of how to use the software Talk to people at the LPC, that is what we are here for…

hcal and jet/met

Documents