Calorimetry and particle identification

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1 Calorimetry and particle identification Summary of two selected HCPSS 2012 courses R. Märki EPFL - LPHE 8 October /47 R. Märki Calorimetry and particle identification

2 Outline I attended the 7th Annual Fermilab-CERN HCPSS in August 2012 and I summarize two selected topics in this presentation. Calorimetry Advantages Calorimeter types Calibration Examples Particle identification Principle Strategy and complete example of CMS More techniques Efficiency and purity 2/47 R. Märki Calorimetry and particle identification

3 Calorimetry advantages Who do calorimetry?! Pros: Cons: Measure neutrals as well as charged particles Resolution improves with particle energy If hermetic, can be used to measure missing particles (eg. neutrinos) Fast trigger Non-linear response Must be BIG (hence expensive) Needs non-trivial engineering for design, construction and signal extraction 3/47 R. Märki Calorimetry and particle identification

4 Calorimetry advantages Combined with tracking, the energy resolution is highly improved Example of CMS: 4/47 R. Märki Calorimetry and particle identification

5 Material interactions Particles interact in matter and deposit energy Bethe-bloch for charged particles Mean free path (or radiation length) important for calorimeter design 5/47 R. Märki Calorimetry and particle identification

6 Shower developpement Example here: electrons Longitudinal shower: several radiation lengths are needed to completely stop a particle. Lateral shower: the so called Moliere radius R M X 0 (21MeV /E c ) contains 90% of the electromagnetic cascade, though there are long tails. longitudinal lateral 6/47 R. Märki Calorimetry and particle identification

7 Sampling calorimeters Only part of the deposited energy de/dx is measured The sampling fraction is defined as (de/dx)active medium / (de/dx) absorber The energy measurement is linear for an infinite detector E particle = k (de/dx) absorber /(de/dx) active medium P (de/dx) active medium Number of particles in the shower is statistical but scales like: N shower E particle /E critical Energy deposition in the shower is a statistical process σ E 1/ N shower σ E 1/ E particle 7/47 R. Märki Calorimetry and particle identification

8 Homogeneous calorimeters Commonly Scintillator (solid and liquid) Liquid Argon Less commonly Gas proportional tubes Silicon Example: CMS Lead-Tungstate Calorimeter - response to high energy electrons 8/47 R. Märki Calorimetry and particle identification

9 Electromagnetic calorimeters Both sampling and homogeneous are frequently used Need fine granularity to distinguish photons from π 0 for instance, discussed more in PID part Usually preshower with even finer granularity over 1-2 first radiation lengths In a sampling electromagnetic calorimeter, the sampling fraction changes in the shower 9/47 R. Märki Calorimetry and particle identification

10 Hadronic calorimeters Hadronic calorimeters are usually sampling calorimeters Hadron showers have a complex composition: EM energy (eg π 0 γγ) : O(50%) Visible non-em energy (eg de/dx) : O(25%) Invisible non-em energy (eg nuclear breakup) :O(25%) Escaped energy (eg ν) :O(1%) Therefore the simulation is complicated as well 10/47 R. Märki Calorimetry and particle identification

11 Example of calorimeters - CDF The sampling calorimeter of CDF Lead absorber with sheets of plastic scintillator The left picture was taken by myself this summer! 11/47 R. Märki Calorimetry and particle identification

12 Example of calorimeters - D0 Homogeneous calorimeter at D0 Uranium metal bathed in liquefied argon 12/47 R. Märki Calorimetry and particle identification

13 Example of calorimeters - ATLAS HCAL ATLAS HCAL: Sampling calorimeter Absorber: steel Scintillating tiles 8m diameter 12m long 13/47 R. Märki Calorimetry and particle identification

14 Example of calorimeters - ATLAS Argon ATLAS ECAL (and HCAL in the forward region): Sampling calorimeter Absorber: lead and stainless steel Liquid argon to sample Accordeon shaped electrodes 14/47 R. Märki Calorimetry and particle identification

15 Example of calorimeters - CMS HCAL CMS HCAL: Sampling calorimeter Absorber + plastic scintillator (scintillator plates 2m long) 15/47 R. Märki Calorimetry and particle identification

16 Example of calorimeters - CMS ECAL Very famous and compact CMS ECAL Homogeneous calorimeter Lead tungstate (PbWO 4 ) crystal tiles Before: pre-shower lead / silicon strips 16/47 R. Märki Calorimetry and particle identification

17 Calorimeter calibration - ATLAS Optical chain calibration: (in real time) tiles with source (Cs 137 ) PMT with laser readout electronics with test pulse Aging effects can be measured and taken into account: 17/47 R. Märki Calorimetry and particle identification

18 Calorimeter calibration - CMS Very first calibration in test beam ECAL calibrated with electrons (and photons) HCAL calibrated with π 0 (normal incidence, no working ECAL in front) need for correction The energy calibration is parametrized with E = a + b(p, η)ecal + c(p, η)hcal a, b and c are determined with isolated tracks in minimum bias events 18/47 R. Märki Calorimetry and particle identification

19 Detector aging - CMS EM crystals The aging can be monitored using the calibration methods seen before Monitor using laser calibration system Response using E/p in W eν 19/47 R. Märki Calorimetry and particle identification

20 Particle identification Already in calorimeters there are different shower responses for electrons and hadrons 20/47 R. Märki Calorimetry and particle identification

21 Particle identification General detector response depending on particle 21/47 R. Märki Calorimetry and particle identification

22 Particle identification - example in CMS 22/47 R. Märki Calorimetry and particle identification

23 Particle identification - example in CMS 23/47 R. Märki Calorimetry and particle identification

24 Particle identification - example in CMS During reconstruction the event is cleaned up: 1 Find and remove muons (σ track ) 2 Find and remove electrons ( min[σ track, σ ECAL ] ) 3 Find and remove charged hadrons (σ track ) 4 Find and remove converted photons ( min[σ track, σ ECAL ] ) 5 Find and remove V0 s (σ track ) 6 Find and remove photons (σ ECAL ) 7 Left with neutral hadrons (10%) (σ HCAL + fake) 24/47 R. Märki Calorimetry and particle identification

25 Particle identification - example in CMS Link tracks to ECAL and HCAL 25 ECAL cells underneath each HCAL cell 25/47 R. Märki Calorimetry and particle identification

26 Particle identification - example in CMS Top view helps to see the links The captions correspond to what was simulated What is actually reconstructed: γ, γ, γ, π +, π 26/47 R. Märki Calorimetry and particle identification

27 Particle identification - example in ATLAS 27/47 R. Märki Calorimetry and particle identification

28 Particle identification - example in ATLAS 28/47 R. Märki Calorimetry and particle identification

29 Particle identification - when E p Few energy in calorimeter compared to measured momentum Mainly due to muons Muon ID very efficient, 98% in CMS The resting 2% still contribute significantly Looser muon cuts used but still many cases left True origin: fake tracks and interactions in tracker material 29/47 R. Märki Calorimetry and particle identification

30 Particle identification - when E p Tracker acts like a pre-shower (silicon is heavy) Has up to 2 radiation lengths for certain pseudo-rapidities CMS ATLAS 30/47 R. Märki Calorimetry and particle identification

31 Particle identification - when E p Reduce hits progressively Start from very pure track seeding Remove used hits and start over with looser requirements For charged hadrons: from 85% efficiency, 20% fake rate to 93% efficiency, 1-2% fake rate 31/47 R. Märki Calorimetry and particle identification

32 Particle identification - Time of Flight Measure time difference between two detector plane crossings Different times for different particles of same momentum β = d/c t and p = γmcβ t = dp/γm Difference very small for relativistic particles Example for a 12m distance: 10 GeV/c K ns 10 GeV/c π ns One needs to measure 50 ps difference for a 12m distance which is already a large scale 32/47 R. Märki Calorimetry and particle identification

33 Particle identification - Ionization Particles lose energy according to the Bethe-Bloch formula Energy loss depends on momentum and mass If energy or momentum loss is measured, one can discrimanate between particles Hard to distinguish π and µ though, as their masses are very close 33/47 R. Märki Calorimetry and particle identification

34 Particle identification - Transition radiation A charged particle flying into a medium with different n (or different dielectric constant, as n = ε) will have its relative velocity with respect to c changed This change results in the emission of transition radiation (photons) Emitted energy proportional to the boost (γ) of the particle Hence also quite good for high energy particles 34/47 R. Märki Calorimetry and particle identification

35 Particle identification - Cherenkov radiation A charged particle having a velocity higher than c emits Cherenkov radiation The light is emitted in a cone, like the waves from a motorboat The angle of the cone is proportional to the velocity cos(θ c ) = 1/βn 250 e µ π 200 K Aerogel θ C max 242 mrad p θ C (mrad) C 4 F 10 gas mrad 32 mrad π K CF 4 gas Momentum (GeV/c) 35/47 R. Märki Calorimetry and particle identification

36 Particle identification - Electron ID Electrons radiate around 70% of the energy in the track by bremsstrahlung Photons have > 50% chance to convert into e + e pair Hence, energy spreads in ϕ ( to B) Standart Kalman Filter pattern recognition gives up quickly Need to account for Bethe-Heitler energy loss (bremsstrahlung) Use sum of Kalman Filters (Gaussian Sum Filter) to approximate non-gaussian part 36/47 R. Märki Calorimetry and particle identification

37 Particle identification - Electron ID Very important to identify/recover bremsstrahlung photons Otherwise their energy is counted twice: (in track + again in ECAL) Holds also for electron pair converted bremsstrahlung photons How it is done in CMS: Check if tangent of track points to ECAL cluster Link cluster to track Also test compatibility between ECAL cluster E and p along GSF track 37/47 R. Märki Calorimetry and particle identification

38 Particle identification - Electron ID BUT! Everything that we have just seen can be used to discrimanate between e and π for instance π radiate much less, so one can: count the number of hits linked to the track look at p count the number of bremsstrahlung γ associated to the track look at E bremsstrahlung look at shower shape along ϕ and η look at linked HCAL energy Everything put into a MVA gives 95% efficiency for isolated electrons and 70-80% efficiency in jets K S π + π 38/47 R. Märki Calorimetry and particle identification

39 Particle identification - Photon ID If not converted, the only way to measure photons are calorimeters When looking at unconverted photons, everything known has already been removed from the event. Then: Use fine segmentation to look at shower shape Use isolation criteria Clustering algorithm plays a big role (be sure that all energy is linked to the cluster!) 39/47 R. Märki Calorimetry and particle identification

40 Particle identification - Efficiency and purity Assume ID is uncorrelated with isolation The true number of photons among N A is equal to N(γ) = N A background This background is N B M A /M B Hence the purity is P = 1 N B /N A M A /M B Efficiency can also be simulated Or use tag and probe method 40/47 R. Märki Calorimetry and particle identification

41 Related physics results The Higgs in H γγ! 41/47 R. Märki Calorimetry and particle identification

42 Thank you for your attention

43 Backup slides 43/47 R. Märki Calorimetry and particle identification

44 CMS event Massive Pile-up at CMS 44/47 R. Märki Calorimetry and particle identification

45 Material interactions in tracking system at CMS Interaction vertices in the CMS tracker 45/47 R. Märki Calorimetry and particle identification

46 LHCb RICH PID LHCb φ K + K result from 2009 ( s = 900GeV ) without and with RICH PID information 46/47 R. Märki Calorimetry and particle identification

47 Tag and probe muons at CMS Fit J/ψ mass for dimuons which pass or do not pass PID cut Evaluate efficiency and purity 47/47 R. Märki Calorimetry and particle identification

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