Click to edit Master title style IEEE short course on: Calorimetry Calorimeter systems at collider experiments Erika Garutti (DESY)

Click to edit Master title style IEEE short course on: Calorimetry From single calorimeter detectors to calorimeter in a detector system Calorimeters for jets Particle flow algorithms to improve jet energy resolution Highly granular calorimeters - techniques for analog and digital calorimetry Outline

Click to edit Master title style IEEE short course on: Calorimetry From single calorimeters to a HEP detector CMS ECAL Endcap ATLAS barrel HCAL and coil Calorimeters are in general one component of a complex detector system Typical of collider detector is the onion-like Structure of the detector system

Click to edit Master title style IEEE short course on: Calorimetry Detectors for collider experiments Typical onion-like structure for most of modern collider detectors - The tracking system comes first (minimum material budget) -The calorimeter stops (most of) the particles so has to come second -Muons can escape the calorimeter and require an extra detector CMS

Click to edit Master title style IEEE short course on: Calorimetry Particles are not kind! The distinction between electromagnetic and hadronic calorimeter is not rigorous for a hadron ~30-40% of first hard interaction of a hadron happen in the EM-calo W The choice of a high Z material for the EM-calo minimizes the hadron interactions before the Had-calo: ~30 X 0 to stop an EM shower = 1 int  of Tungsten (W) or 3 int  of Iron (Fe) Fe

Click to edit Master title style IEEE short course on: Calorimetry Particles are not kind! About int  are needed to contain hadrons with energy ~100 GeV ~1.2 m of W or 2.2 m of Fe W The choice of a high Z material for the Had-calo minimizes its depth Fe [cm]

Click to edit Master title style IEEE short course on: Calorimetry ideal calo  ideal calo system Ideal calorimeter e- 100 GeV  GeV = k x 100 GeV Implications: e/  = 1 L  30 X 0 && L  11  int L  [g/cm 3 ] int [cm]L [m] PbWO 4 BGO Fe Pb W Calorimeter system requirements  identification (EM/Had segment.) separation of jets (lateral segment.) calo contained inside magnetic coil

Click to edit Master title style IEEE short course on: Calorimetry Why not using tracker (has better resolution)? Particles are not alone! Jets are a collimated group of particles that result from the fragmentation of quarks and gluons They are measured as clusters in the calorimeter momentum of cluster is correlated to the momentum of the original quark At collider experiments particles come typically in “jets”

Click to edit Master title style IEEE short course on: Calorimetry Why are jets measured in the calorimeter? At high energy calorimetry is a must magn. spectr. particle E or p [GeV]

Click to edit Master title style IEEE short course on: Calorimetry Phenomenology of jets Partons (quark/gluon) are produced from the interaction of beam particles Partons fragment into hadrons Jets clustering algorithm: – Typically uses a geometric assumption to group particles from the same parton (cone) A fraction of the parton energy can be lost (out of the cluster) Jet = sum of many particles (e, ,p,n,K,…) technically: (E EM CAL + E HAD CAL )clusters + muon momentum + E miss

Click to edit Master title style IEEE short course on: Calorimetry Jet versus calorimeter energy scale Jets are complicated processes EM and Had Calo calibrations are generally not sufficient to get calibrated jet energy – More work needs to be done!! Jet energy scale is crucial for many important measurements: – Top quark mass (used to constrain Higgs boson) – Higgs searches / branching ratio – Search for beyond physics the standard model Measurements often performed by comparing real data with simulations – Need to get both physics and detector simulation right

Click to edit Master title style IEEE short course on: Calorimetry Absolute jet energy scale Response to single particles non- linear (in test beam) However, jets are identified as one single objects by clustering algorithm For a 50 GeV jet: calibration is not the same whether: – one 50 GeV pion – 10 times 5 GeV pions or whether: – one 50 GeV  0 or  +/- CMS test beam

Click to edit Master title style IEEE short course on: Calorimetry Absolute jet energy scale Response to single particles non- linear (in test beam) However, jets are identified as one single objects by clustering algorithm For a 50 GeV jet: calibration is not the same whether: – one 50 GeV pion – 10 times 5 GeV pions or whether: – one 50 GeV  0 or  +/- Solution: Get the average energy scale: Simulate an “average” particle configuration inside jet Use test beam information to get calibration factor for single particles

Click to edit Master title style IEEE short course on: Calorimetry What is inside a jet? E particle /E jet ? There are wide variations to the average particle energy inside a jet … but also on the energy carried by different type of particles in a jet These fluctuations add uncertainty to the jet energy scale determination

Click to edit Master title style IEEE short course on: Calorimetry Jet energy resolution at LHC Stochastic term for hadrons only: ~93% and 42% respectively jet

Click to edit Master title style IEEE short course on: Calorimetry ideal calo  ideal calo system Ideal calorimeter e- 100 GeV  GeV = k x 100 GeV Calorimeter system requirements  identification (EM/Had segment.) separation of jets (lateral segment.) calo contained inside magnetic coil Calorimeter system e- 100 GeV  GeV Sampling calorimeters can have highest density Different material in EM/Had segments Different layer thickness in the same material Extra material (support/cables) between calos different sampling factors

Click to edit Master title style IEEE short course on: Calorimetry Sampling Method Weights applied to different calorimeter compartments Enlarged cone size yields increased electronic noise H1 Method Weights applied directly to cell energies Better resolution and residual nonlinearities Energy weighting for jets Back-to-back dijet events |  |=0.3 Parameter Sampling MethodH1 Method  R=0.4  R=0.7  R=0.4  R=0.7 a (%GeV 1/2 )66.0 ± ± ± ± 1.1 b (%)1.2 ± ± ± ± 0.2  2 prob. (%) ATLAS Can the jet energy resolution be better?

Click to edit Master title style IEEE short course on: Calorimetry LEP-like LEP-like detector M j1j2 M j3j4 Precision jet physics  Require jet energy resolution improvement by a factor of 2  Worse jet energy resolution (60%/  E) is equivalent to a loss of ~40% lumi Jet1 Jet2 Jet3 Jet4 ILC design goal W Z 0 M j1j2 M j3j4  jet ~3% Perfect Note due to Breit-Wigner tails best possible separation is 96 % reasonable choice for LC jet energy resolution: minimal goal  E /E < 3.5 % reasonable choice for LC jet energy resolution: minimal goal  E /E < 3.5 % lepton machine (ILC: e + e TeV, 1-3 TeV ) build a detector with excellent jet energy resolution At the Tera-scale, we will do physics with W’s and Z’s as Belle and Babar do with D + and D s At the Tera-scale, we will do physics with W’s and Z’s as Belle and Babar do with D + and D s Br qq ~70%

Click to edit Master title style IEEE short course on: Calorimetry Calorimeter for Particle Flow Jet energy resolution is worse than (or at most as good as) hadron resolution [world best: ZEUS HCAL  had ~35%/  E] How to improve on jet energy resolution:  Resolution in hadronic calorimeter limited by “fluctuations” : number of  0 produced & amount of invisible energy in one nuclear interaction Two approaches: - measure the shower components in each event  access the source of fluctuations (Dual/Triple Readout) - minimize the influence of the calorimeter (in particular hadronic one)  use combination of all detectors

Click to edit Master title style IEEE short course on: Calorimetry The first idea: Energy flow First algorithm developed by ALEPH (LEP) in the early 90ies: Combine energy measurement from the calorimeter with the momentum measurement from the tracking p=20 GeV E calo = 25 GeV E n = 5 GeV Energy of neutral hadron obtained by subtraction: E n = E calo – p track BUT:  had ~ 60%  E  E had = 25 ± 3 GeV  E n = 5 ± 3 GeV Calorimeter resolution important in the subtraction method To not double count the energy: energy deposited in the calorimeter by the tracks has to be masked  Generally granularity of had. (and em) calorimeter is the limiting factor

Click to edit Master title style IEEE short course on: Calorimetry Particle Flow paradigm  reconstruct every particle in the event up to ~100 GeV Tracker is superior to calorimeter  use tracker to reconstruct e ±,  ±,h ± ( of E jet ) use ECAL for  reconstruction ( ) (ECAL+) HCAL for h 0 reconstruction ( ) HCAL E resolution still dominates E jet resolution But much improved resolution (only 10% of E jet in HCAL) PFLOW calorimetry = Highly granular detectors + Sophisticated reconstruction software Typical single particle energy at LC

Click to edit Master title style IEEE short course on: Calorimetry Particle Flow expectations at LC Goal Jet energy resolution: Current Pflow performance (PandoraPFA + ILD) uds-jets (full GEANT 4 simulations) E JET  E /E =  / √E jj |cos|<0.7  E /E j 45 GeV25.2 %3.7 % 100 GeV29.2 %2.9 % 180 GeV40.3 %3.0 % 250 GeV49.3 %3.1 % Equivalent stochastic term shown for comparison PFA resolution is not stochastic tails in Gaussian distribution = CONFUSION Benchmark performance using jet energy resolution in Z decays to light quarks:

Click to edit Master title style IEEE short course on: Calorimetry State of the art of Particle Flow algorithm Currently best performing algorithm: PandoraPFA High granularity Particle Flow reconstruction is highly non-trivial ClusteringTopological Association 30 GeV 12 GeV 18 GeV Iterative Reclustering 9 GeV 6 GeV Photon ID Fragment ID Mark Thomson, NIM 611 (2009) For more details: many complex steps (not all shown) many complex steps (not all shown)

Click to edit Master title style IEEE short course on: Calorimetry Confusion in Particle Flow If these hits are clustered together with these, lose energy deposit from this neutral hadron (now part of track particle) and ruin energy measurement for this jet. Level of mistakes, “confusion”, determines jet energy resolution not the intrinsic calorimetric performance of ECAL/HCAL Three types of confusion: i) Photonsii) Neutral Hadronsiii) Fragments Failure to resolve photon Failure to resolve neutral hadron Reconstruct fragment as separate neutral hadron

Click to edit Master title style IEEE short course on: Calorimetry Technical aspects of Particle Flow Use calorimeter measurement to “guide” the clustering: re-cluster if E cluster differs too much from track momentum  Back to an “Energy Flow” method but much higher sophistication  Hadronic calorimeter resolution effects the clustering performance (second order effect)

Click to edit Master title style IEEE short course on: Calorimetry Detector design at ILC “no” material in front – calorimeter inside the solenoid large radius and length – to better separate the particles large magnetic field – to sweep out charged tracks small Moliere radius – to minimize shower overlap small granularity– to separate overlapping showers ILD: International Large Detector HCAL ECAL PandoraPFA currently used to optimize the ILD detector design ECAL: SiW sampling calorimeter longitudinal segmentation: 30 layers transverse segmentation: 5x5 mm 2 pixels Steel-Scintillator tile sampling calorimeter longitudinal segmentation: 48 layers (6 I ) transverse segmentation: 3x3 cm 2 tiles HCAL:

Click to edit Master title style IEEE short course on: Calorimetry Optimization of HCAL 3cm x 3cm tiles looks reasonable (5M ch. vs 50M for 1x1cm and 500k ch for 10x10cm) for low-energetic jets the confusion term of PFA is less sensitive to tile size Material X 0 /cm  M /cm I /cmX 0 / I Fe Cu W Pb ? Maximum containment inside the solenoid  small I HCAL will be large: absorber cost/structural properties important small granularity – to separate overlapping showers

Click to edit Master title style IEEE short course on: Calorimetry Understand Particle Flow performance

Click to edit Master title style IEEE short course on: Calorimetry Time structure of the hadronic shower Steel HCAL Timing for 250 GeV jet (corrected for time of flight) 95 % of energy in 10 ns 99 % in 50 ns In steel suggests optimal timing window in range >10 ns How is the situation in W? Previous studies performed assuming a r/o electronics gate of 200ns

Click to edit Master title style IEEE short course on: Calorimetry Time structure of the hadronic shower both #n and #p far from closed shells naively would expect more nuclear interactions with W Problem: expect longer time profile (decays, secondary interactions) Furthermore: not clear how well modeled in Geant 4 Tungsten HCAL Steel HCAL Tungsten is much “slower” than Steel only 80 % of energy in 25 ns only 90 % in 100 ns how much due to thermal n ? single K L s (QGSP_BERT) 0.3 MiP cut

Click to edit Master title style IEEE short course on: Calorimetry Particle Flow performance vs time cut Tungsten HCAL Steel HCAL For no time cut (1000 ns) peformance of CLIC_ILD very good - somewhat better than ILD (thicker HCAL, larger B) For high(ish) energy jets – strong dependence on time cut - suggests time window of > 10 ns - need something like 50 ns to get into “flat region”

Click to edit Master title style IEEE short course on: Calorimetry Summary on Particle Flow Algorithm Interplay of highly granular detectors and sophisticated pattern recognition (clustering) algorithms Basic detector parameters thoroughly optimized using PandoraPFA Time structure of hadronic shower is an important parameter in the feasibility study & in the design of the readout electronics  needs validation A PFLOW detector is not cheap: do we believe in simulations ?

Click to edit Master title style IEEE short course on: Calorimetry The zoo of PFLOW calorimeters

Click to edit Master title style IEEE short course on: Calorimetry Energy deposited by a charged particle in the active material of a sampling calorimeter follows a Landau distribution  Long-tail Therefore large fluctuations in energy deposition for a single particle Typical calorimeters have multiple particles crossing each cell analogue readout – including Landau fluctuations A sufficiently high granularity calorimeter may only have a single particle crossing each cell possibility of digital readout, i.e. count charged particles – insensitive to Landau fluctuations Analogue.vs. Digital readout

Click to edit Master title style IEEE short course on: Calorimetry Analogue.vs. Digital readout Non-linear behavior for dense showers photon analysis ECAL: Analog readout required S.Magill (ANL) hadron analysis HCAL: either Analog or Digital readout Slope = 23 hits/GeV Calorimeter cell size 1x1cm 2

Click to edit Master title style IEEE short course on: Calorimetry The zoo of PFLOW calorimeters * Credit: the following slides are based on work done by the CALICE collaboration