IEEE short course on: Calorimetry
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Calorimeter systems
at collider experiments
Erika Garutti
(DESY)
21/10/2011
erika.garutti@desy.de
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IEEE short course on: Calorimetry
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Master title style
• 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
21/10/2011
erika.garutti@desy.de
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IEEE short course on: Calorimetry
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style
FromClick
singletocalorimeters
totitle
a HEP
detector
Calorimeters are in general one
component of a complex detector
system
ATLAS barrel HCAL and coil
CMS ECAL Endcap
Typical of collider detector is the onion-like
Structure of the detector system
21/10/2011
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IEEE short course on: Calorimetry
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editcollider
Masterexperiments
title style
Detectors
CMS
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
21/10/2011
erika.garutti@desy.de
- Muons can escape the calorimeter
and require an extra detector
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IEEE short course on: Calorimetry
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are nottitle
kind!style
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
The choice of a high Z material for the
EM-calo minimizes the hadron
interactions before the Had-calo:
~30 X0 to stop an EM shower =
1 lint of Tungsten (W) or 3 lint of Iron (Fe)
21/10/2011
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W
Fe
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IEEE short course on: Calorimetry
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are nottitle
kind!style
About 11-12 lint are needed to contain
hadrons with energy ~100 GeV
[cm]
~1.2 m of W or 2.2 m of Fe
Fe
W
The choice of a high Z material for the
Had-calo minimizes its depth
21/10/2011
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IEEE short course on: Calorimetry
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title
style
ideal
calo
ideal calo
system
Ideal calorimeter
Calorimeter system requirements
e- 100 GeV
= k x 100 GeV
p- 100 GeV
= k x 100 GeV
• g identification (EM/Had segment.)
• separation of jets (lateral segment.)
• calo contained inside magnetic coil
L
Implications:
• e/p = 1
• L 30 X0 && L
[g/cm3]
PbWO4
BGO
Fe
Pb
W21/10/2011
8.28
7.13
7.87
11.34
19.25
11 lint
int [cm]
19.5
21.88
16.7
17.6
9.9
L [m]
2.1
2.4
1.8
1.9
1.1erika.garutti@desy.de
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IEEE short course on: Calorimetry
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Master
title style
Particles
not alone!
At collider experiments particles come typically in “jets”
• 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
21/10/2011
Why not using
tracker (has better
resolution)?
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IEEE short course on: Calorimetry
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tomeasured
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title
style
Why are
jets
in the
calorimeter?
• Measure charged + neutral particles
At high energy calorimetry is a must
magn.
spectr.
• Performance of calorimeters
improves with energy
• DE/E  1/ E + const.
• while in a magnetic spectrometer
• Dp/p  p
particle E or p [GeV]
• Obtain information on energy flow: total (missing) transverse energy,
incoming direction (with high segmentation)
• Obtain information fast (<100ns feasible)
 recognize and select interesting events in real time (trigger)
21/10/2011
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IEEE short course on: Calorimetry
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title
style
Phenomenology
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,g,p,p,n,K,…)
technically: (EEM CAL + EHAD CAL )clusters + muon momentum + Emiss
21/10/2011
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IEEE short course on: Calorimetry
to calorimeter
edit Master energy
title style
JetClick
versus
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
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IEEE short course on: Calorimetry
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to editjet
Master
title
style
Absolute
energy
scale
• Response to single particles nonlinear (in test beam)
• However, jets are identified as one
single objects
by clustering
CMS test
beam
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 p0 or p+/-
21/10/2011
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IEEE short course on: Calorimetry
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to editjet
Master
title
style
Absolute
energy
scale
• Response to single particles nonlinear (in test beam)
• However, jets are identified as one
single objects by clustering
algorithm
Solution:
• Get the average energy scale:
Simulate an “average” particle
configuration inside jet
• Use test beam information to get
calibration factor for single particles
• 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 p0 or p+/-
21/10/2011
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IEEE short course on: Calorimetry
ClickWhat
to editis Master
inside atitle
jet?style
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
Eparticle/Ejet
𝜎𝑗𝑒𝑡
1
𝑎
𝑐
?
=
𝑓𝑐ℎ𝑎𝑟 𝜎𝑐ℎ𝑎𝑟 ⊕ 𝑓𝑒𝑚 𝜎𝑒𝑚 ⊕ 𝑓ℎ𝑎𝑑 𝜎ℎ𝑎𝑑 =
⊕ 𝑏⊕
𝐸𝑗𝑒𝑡
𝐸𝑗𝑒𝑡
𝐸
𝐸
21/10/2011
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IEEE short course on: Calorimetry
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to editresolution
Master title
Jet energy
at style
LHC
jet
jet
Stochastic term for hadrons only: ~93% and 42% respectively
21/10/2011
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IEEE short course on: Calorimetry
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edit Master
title
style
ideal
calo
ideal calo
system
Ideal calorimeter
Calorimeter system requirements
e- 100 GeV
= k x 100 GeV
p- 100 GeV
= k x 100 GeV
• g identification (EM/Had segment.)
• separation of jets (lateral segment.)
• calo contained inside magnetic coil
Calorimeter system
e- 100 GeV
Sampling calorimeters can have highest density
p- 100 GeV
Different material in EM/Had segments
Different layer thickness in the same material
Extra material (support/cables) between calos
21/10/2011
erika.garutti@desy.de
different
sampling
factors
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IEEE short course on: Calorimetry
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to edit
Master title
style
Energy
weighting
for jets
Back-to-back dijet events
Sampling Method
• Weights applied to different calorimeter compartments
• Enlarged cone size yields increased electronic noise
E jet  EPS  EEM  gEHAD   EEM 3  EHAD
|h|=0.3
H1 Method
• Weights applied directly to cell energies
• Better resolution and residual nonlinearities
E jet  EPS  EM ( EM , j )   EM , j   HAD ( HAD, j )   HAD, j   C EC
j
ATLAS
21/10/2011
Parameter
j
Sampling Method
H1 Method
DR=0.4
DR=0.7
DR=0.4
DR=0.7
a (%GeV1/2)
66.0 ± 1.5
61.2 ± 1.3
53.9 ± 1.3
51.5 ± 1.1
b (%)
1.2 ± 0.3
1.4 ± 0.2
1.3 ± 0.2
2.5 ± 0.2
2 prob. (%)
1.6
erika.garutti@desy.de
0.8
27.3
66.7
Can the
jet energy
resolution
be better?
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IEEE short course on: Calorimetry
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title style
jet physics
lepton machine (ILC: e+ e- @ 0.5-1 TeV, CLIC: @ 1-3 TeV )
LEP-like
ILC
designdetector
goal
Mj1j2
At the Tera-scale, we will do physics with
W’s and Z’s as Belle and Babar do with D+ and Ds
ΔΕ
 60%/ E
ΔΕ jet
jet  30%/ E jj
Jet1
Jet2
Jet3
Jet4
W
Brqq~70%
Z0
Require jet energy resolution improvement by a factor of 2
Mj3j4
Worse jet energy resolution (60%/E) is equivalent to a loss of ~40% lumi
Perfect
Note due to Breit-Wigner tails best possible separation is 96 %
sjet ~3%
LEP-like
build a detector with excellent jet energy resolution
reasonable choice for LC jet
energy resolution:
minimal goal sE/E < 3.5 %
21/10/2011
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IEEE short course on: Calorimetry
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title Flow
style
Calorimeter
for Particle
• Jet energy resolution is worse than (or at most as good as) hadron resolution
[world best: ZEUS HCAL shad~35%/ E]
• How to improve on jet energy resolution:
 Resolution in hadronic calorimeter limited by “fluctuations” : number of p0
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
21/10/2011
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IEEE short course on: Calorimetry
Click
edit
Master
titleflow
style
Theto
first
idea:
Energy
First algorithm developed by ALEPH (LEP) in the early 90ies:
• Combine energy measurement from the calorimeter with the momentum
measurement from the tracking
Ecalo= 25 GeV
p=20 GeV
En = 5 GeV
Energy of neutral hadron obtained by subtraction: En = Ecalo – ptrack
BUT:
shad ~ 60% E
 Ehad = 25 ± 3 GeV  En = 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
21/10/2011
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IEEE short course on: Calorimetry
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to editFlow
Master
title style
Particle
paradigm
 reconstruct every particle in the event
up to ~100 GeV Tracker is superior to calorimeter 
use tracker to reconstruct e±,m±,h± (<65%> of Ejet )
use ECAL for g reconstruction (<25%>)
(ECAL+) HCAL for h0 reconstruction (<10%>)
HCAL E resolution still dominates Ejet resolution
But much improved resolution (only 10% of Ejet in HCAL)
21/10/2011
PFLOW calorimetry = Highly granular detectors
+ Sophisticatederika.garutti@desy.de
reconstruction software
Typical single particle
energy at LC
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IEEE short course on: Calorimetry
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edit expectations
Master title style
Particle
at LC
Goal Jet energy resolution:
Benchmark performance using jet energy
resolution in Z decays to light quarks:
Current Pflow performance (PandoraPFA + ILD)
uds-jets (full GEANT 4 simulations)
EJET
sE/E = /√Ejj
|cosq|<0.7
sE/Ej
45 GeV
25.2 %
3.7 %
100 GeV
29.2 %
2.9 %
180 GeV
40.3 %
3.0 %
250 GeV
49.3 %
3.1 %
Equivalent stochastic term shown for comparison
PFA resolution is not stochastic
tails in Gaussian distribution = CONFUSION
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IEEE short course on: Calorimetry
toart
edit
title algorithm
style
StateClick
of the
of Master
Particle Flow
High granularity Particle Flow reconstruction is highly non-trivial
Currently best performing algorithm: PandoraPFA
many complex steps
Clustering
Topological Association
(not all shown)
Iterative Reclustering
18 GeV
30 GeV
12 GeV
Photon ID
Fragment ID
9 GeV
9 GeV
6 GeV
21/10/2011
For more details:
erika.garutti@desy.de
Mark Thomson, NIM 611 (2009) 24-40
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IEEE short course on: Calorimetry
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titleFlow
style
Confusion
in Particle
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) Photons
Failure to resolve photon
21/10/2011
ii) Neutral Hadrons
Failure to resolve
neutral hadron
erika.garutti@desy.de
iii) Fragments
Reconstruct fragment as
separate neutral hadron
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IEEE short course on: Calorimetry
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title style
Technical
of Particle
Flow
Use calorimeter measurement to
“guide” the clustering:
• re-cluster if Ecluster 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)
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IEEE short course on: Calorimetry
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design title
at ILCstyle
PandoraPFA currently used to optimize the ILD detector design
ILD: International Large Detector
“no” material in front
large radius and length
large magnetic field
small Moliere radius
small granularity
HCAL
ECAL
21/10/2011
– calorimeter inside the solenoid
– to better separate the particles
– to sweep out charged tracks
– to minimize shower overlap
– to separate overlapping showers
ECAL:
• SiW sampling calorimeter
• longitudinal segmentation: 30 layers
• transverse segmentation: 5x5 mm2 pixels
HCAL:
• Steel-Scintillator tile sampling calorimeter
• longitudinal segmentation: 48 layers (6 lI)
• transverse segmentation: 3x3 cm2 tiles
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IEEE short course on: Calorimetry
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of title
HCALstyle
Material
X0/cm
rM/cm
lI/cm
X0/lI
Fe
1.76
1.69
16.8
9.5
Cu
1.43
1.52
15.1
10.6
W
0.35
0.93
9.6
27.4
Pb
0.56
1.00
17.1
30.5
?
• Maximum containment inside
the solenoid  small lI
• HCAL will be large: absorber
cost/structural properties
important
• small granularity – to separate
overlapping showers
• 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
21/10/2011
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IEEE short course on: Calorimetry
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style
Understand
Flowtitle
performance
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IEEE short course on: Calorimetry
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title style
TimeClick
structure
the hadronic
shower
Previous studies performed assuming a r/o electronics gate of 200ns
Timing for 250 GeV jet
(corrected for time of flight)
• 95 % of energy in 10 ns
• 99 % in 50 ns
Steel HCAL
• In steel suggests optimal timing
window in range >10 ns
How is the situation in W?
21/10/2011
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IEEE short course on: Calorimetry
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title style
TimeClick
structure
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
single KLs (QGSP_BERT)
0.3 MiP cut
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 ?
21/10/2011
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IEEE short course on: Calorimetry
ClickFlow
to edit
Master title
Particle
performance
vsstyle
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”
21/10/2011
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IEEE short course on: Calorimetry
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Master
title
style
Summary
onedit
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 ?
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IEEE short course on: Calorimetry
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Master
title style
The
zoo
PFLOW
calorimeters
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IEEE short course on: Calorimetry
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style
Analogue
.vs.Master
Digitaltitle
readout
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
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IEEE short course on: Calorimetry
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style
Analogue
.vs.Master
Digitaltitle
readout
photon analysis
hadron analysis
ECAL: Analog readout required
HCAL: either Analog or Digital readout
Eg   N i
S.Magill (ANL)
Non-linear behavior
for dense showers
Slope = 23 hits/GeV
Calorimeter cell size 1x1cm2
21/10/2011
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IEEE short course on: Calorimetry
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to of
edit
Master
title style
The
zoo
PFLOW
calorimeters
21/10/2011
* Credit:
the following slides are based on workerika.garutti@desy.de
done by the CALICE collaboration
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