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From the ATLAS electromagnetic calorimeter to SUSY
Freiburg, 15/06/05 Dirk Zerwas LAL Orsay

• Introduction
• ATLAS EM-LARG
• Electrons and Photons
• SUSY measurements
• Reconstruction of the
• fundamental parameters
• Conclusions

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Introduction

• LHC CERNs proton-proton collider at 14TeV
• 2800 bunches of 1011 protons
• bunch crossing frequency 40.08MHz
• Low Luminosity 1033cm-2/s meaning 10fb-1 per
  experiment (3 years)
• High Luminosity 1034cm-2/s meaning 100fb-1
  per experiment (n years)
• SLHC most likely 1035cm-2/s meaning 1000fb-1
  per experiment (2015)
• startup for physics late 2007

Two multipurpose detectors ATLAS, CMS

• The experimental challenges of the LHC
  environment
• bunch crossing every 25ns
• 22 events par BX (fast readout, 40MHz ? 200Hz,
  event-size 1.6MB)
• High radiation ?FE electronics difficult
  (military and/or space technology)
• and with that do precision physics!

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Physics at the LHC
Process Events/s
Events/year other machines W?e?
15 108
104 LEP/ 107 TeV. Z ?ee
1.5 107 107
LEP tt 0.8
107 104 TeVatron bb
105 1012
108 Belle/Babar QCD jets
102 109
107 pTgt200GeV

You have heard already much about the physics
from Sven Heinemeyer, Tilman Plehn, Christian
Weiser, plus in-house expertise on
ATLAS-Tracker, ATLAS-Muons, Higgs physics,..so
try to find things of added value not covered so
far CaloSUSYreco
If the machine works well Factory of Z, W, top
and QCD jets. Will be limited quickly by
systematics!

• Measurements
• W mass to 20MeV needs control of the
  linearity/energy scale (0.02 energy scale)
• Higgs mass measurement (if etc) in ??
• SUSY precision measurements with leptons
• Stringent requirements on the energy scale,
  uniformity and linearity
• of the ATLAS-EM Calorimeter response!
  
  Startup date getting closer, need to prove
  that we understand and are prepared Calo!

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The ATLAS Electromagnetic Calorimeter

• Liquid Argon Sampling Calorimeter
• lead (s.s.) absorbers (1.1, 1.5mm Barrel)
• liquid Argon gap 2.2mm 2kV (barrel)
• varying gap and HV in the endcap
• accordion structure ? no dead area in f
• easy to calibrate

f
R 4m
R 2.8m
Z 0m
Z 3.2m
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The barrel and endcap EM-calorimeters!
Some numbers 2048 barrel absorbers 2048 barrel
electrodes giving 32 barrel modules (4years of
production and assembly) 16 endcap modules All
assembled and inserted in their cryostats Barrel
cryostat in pit waiting for electronics
Barrel
Thickness 24-30X0
Granularity (typical ?? X ?f ) Presampler
0.025x0.1 (up to ?1.8) Strips
0.003x0.1 (EC ?) Middle 0.025x0.025
(main energy dep) Back 0.05 x0.025
Endcaps
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Calibration of the ATLAS EM calorimeter

• General Strategy and Sequence for electrons and
  photons
• Calibration of Electronics
• necessitates a good understanding of the physics
  and calibration signal
• Corrections at the cluster level
• position corrections
• correction of local response variations
• corrections for losses in upstream (Inner
  detector) material and longitudinal leakage
• Refinement of corrections depending on the
  particle type (e/?)
• uniformity 0.7 with a local uniformity in
  ??X?f0.2x0.4 better than 0.5
• inter-calibrate region with Zee
• What can be studied where?
• Calibration of electronics studied in testbeam
• Corrections at cluster level testbeam and ATLAS
  simulations
• uniformity testbeam
• Zee simulation
• The best Monte Carlo is the DATA! For ATLAS
• Testbeam ? TestbeamMC ? ATLASMC ? ATLAS

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ATLAS series modules in testbeam

• 1998-2002 prototype and single module tests at
  CERN
• 4 ATLAS barrel modules
• 3 ATLAS endcap modules
• Single electron beams
• 20-245GeV
• Studies of
• energy resolution
• linearity
• uniformity
• particle ID
• 2004 combined testbeam endcap and barrel
  including tracking and muons

FE electronics Sitting directly on the
feedthrough as in ATLAS
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The Signal/Electronics Calibration
Preamp shaper (3gains) SCA
Calibration signal 0.2
Physics signal

• Electronics
• bipolar signal
• time to peak 50ns (variable)
• 40MHz sampling of 5 samples (125ns)
• three gain system 1/9.5/10
• (automatic choice)

60 30 10
L (nH)

• From 5 samples in time to one energy
• Optimal Filtering coefficients
• exponential versus linear
• different entry points
• inductance effect parallel versus serial
• electronic gains

L non-uniform 2-3 effect on E along ?

?
0
1.4
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DigressionFrom physics to industry.
Hamac SCA Atlas Calorimeter Electronics. Sampling
of 3x4 signals at 40MHz, 13.5 bits of dynamic
range with simultaneous write and read in
rad-hard technology (DMILL). Same type of chip
used in digital oscilloscope
keep the high dynamic range and
increase the sampling rate and bandwidth while
using the cheapest technology on the market 0.8µ
pure CMOS (patent filed in April
2001). Instruments are based on the MATACQ chip
which is a sampling matrix able to sample data at
2GS/s over 2560 points and 12 bits of dynamic
range with a very low power consumption compared
to standard systems. This structure has first
been used in the design of the new digital
oscilloscope family of Metrix (0X7000). This
product is the first autonomous 12-bit scope on
the market.
Award for technology transfer to industry of the
SFP (?DPG) Also used in a 4-channel VME and GPIB
board. The latter offers the 2GS/s 12bits
facility with low power at low cost. Its
perfectly suited for high dynamic range precise
measurements in harsh environments (CAEN).
Dominique Breton LAL-Orsay, Eric Delagnes
CEA-Saclay
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Cluster Corrections

• Clustering with fixed size
• Correct position S-shape in eta
• Correct phi offset
• S shape eta in strips
• local energy variations phi (accordion)
• local energy variations eta

ATLAS simulation S-shape
Testbeam phi modulation Endcap
Variation of correction as function of ? under
control (smooth behaviour)
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Cluster Corrections longitudinal weighting
Non-negligeable amount of material before the
calorimeter Reconstruction needs to optimise
simultaneously energy resolution and
linearity. Method based on Monte Carlo and tested
with data in one point ? 0.68
EPS energy in presampler Ei energy in
calorimeter compartments
Correct for energy loss upstream
of Presampler (cryostatbeam line material)
Energy lost between PS and calo (Cable/board)
Small dependence of calo sampling fraction
lateral leakage with energy
Longitudinal leakage depth function of depth
only
0.9 X0, 4.1 _at_10 GeV
1.5 X0, 3.6 _at_10 GeV
gt 30 X0, 0.3 _at_10 GeV
fbrem extracted from simulation and beam
transport of H8 beam line, not present in ATLAS
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Linearity

• Dedicated setup was used in 2002 to have a very
  precise beam energy measurement
• - Degaussing cycle for the magnet to ensure B
  field reproducibility at
• each energy (same hysteresis)
• Use a precise Direct Current-Current Transformer
  with a precision of 0.01
• Hall probe from ATLAS-Muon in magnet to
  cross-check magnet calibration
• ? lots of help from EA-team (I. Efthymiopoulos)
• ? Limitation of calorimeter linearity
  measurement is 0.03 from beam energy knowledge
• Absolute energy scale is not known in beam test
  to better than 1
• Relative variation is important

• Achieved better than 0.1 over 20-180 GeV but
• - done only at one ? position in a setup with
  less material than in ATLAS and no B field
• No Presampler in Endcap (ATLAS) for ? gt1.8

Systematics at low energy 0.1
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Energy resolution
Resolution at ?0.68

• Local energy resolution well understood since
  Module 0 beam tests and well reproduced by
  simulation
• Uniformity is at 1 level quasi online
• but achieving ATLAS goal (0.7 ) difficult

Good agreement for longitudinal shower
development between data and testbeam MC
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Cluster Energy Corrections
In ATLAS use a simplified formula E(corr)
Scale(eta)(Offset(eta)W0(eta)EPSE1E2W3(eta)
E3)
50GeV
3x7
10GeV
100GeV
0.1-0.2 spread from 10GeV to 1TeV over all eta
remember testbeam was 1point proof that the
method works!
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Energy resolution in ATLAS Simulation
Energy resolution in ATLAS wrt testbeam 20
worse Typically 2-4 X0 in front of
calorimeter Good correlation with
resolution Current method at the limit of its
sensitivity For historians wrt TDR 25
degradation, but in TDR simulation Inner Detector
Material description incomplete
100GeV resolution
X0 in front of strips
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Barrel uniformity _at_ 245 GeV in testbeam

• In beam setup, one feedthrough had quality
• problem ( open symbols) due to large
• resistive cross talk (non-ATLAS FT).
• ? gt 7 is ATLAS like and can be used as
• reference
• uniformity better than 0.5
• Energy scale differs by 0.13
• ?quality of module construction is excellent

rms 0.62
Module P13
0.45
Module P13 ? gt 7
4.5
0.49
Module P15 ? gt 7
Module P13 Energy resolution
Similar results for endcap modules
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Position/Direction measurements in TB
? mid
550 µm at ?0
245 GeV Electrons
? strip
?
250 µm at ?0
sZ20mm
H? ?? vertex reconstructed with 2-3 cm accuracy
in ATLAS in z Precision of theta measurement
50mrad/sqrt(E)
sZ5mm
Good agreement of data and simulation
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Z?ee

• uniformity 0.2x0.4 ok in testbeam
• description of testbeam data by Monte Carlo
  satisfactory
• make use of Z?ee Monte Carlo and Data in ATLAS
  for intercalibration of regions
• 448 regions in ATLAS (denoted by i)
• mass of Z know precisely
• Eireco Eitrue(1ai)
• Mijreco Mijtrue(1(aiaj)/2)
• fit to reference distribution (Monte Carlo!!!)
• beware of correlations, biases etc

At low (but nominal) luminosity, 0.3 of
intercalibration can be achieved in a week (plus
E/P later on)! Global constant term of 0.7
achievable!
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Mass resolution of Higgs bosons
H ? ZZ ? 4e Mass scale correct within 0.1GeV
s2.2GeV
H??? 120.96GeV s 1.5GeV
H ??? Note that the generated Higgs mass is
120GeV Effect calibration with electrons, so
the photon calibration is off by 1-2 Getting
from Electron to photon in ATLAS will require MC!
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Particle Identification/jet rejection
Dijet cross section 1mb Z ? ee 1.5 10-6
mb W ? e? 1.5 10-5 mb Need a rejection
factor of 105 for electrons Use the shower shape
in the calorimeter
Use the tracker Use the combination of the
calotracker
Cut based analysis gives for electrons an
efficiency of about 75-80 with a rejection
factor of 105 Multivariate techniques are being
studied for possible improvements (likelihood,
neural net, boost decision tree)
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Soft electrons

• Two possibilities for seeded electron
  reconstruction
• calo
• tracker
• Reconstruction of electrons close to jets
  difficult, and interesting (b-tagging) especially
  for soft electrons. Dedicated algorithm
• builds clusters around extrapolated impact point
  of the tracks
• calculates properties of the clusters
• PDF and neural net for ID
• useful per se as well as for b-tagging

H?bb
pions
J/Psi
WH
ttH
What can we do now with all that?
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Supersymmetry
See talks by Sven and Tilman Here only a
reminder for completeness sake
3 neutral Higgs bosons h, A, H 1 charged Higgs
boson H and supersymmetric particles

• The parameters of the Higgs sector
• mA mass of the pseudoscalar Higgs boson
• tanß ratio of vacuum expectation values
• mass of the top quark
• stop (tR, tL) sector masses and mixing

spin-0 spin-1/2 spin-1
Squarks qR, qL q
Gluino g g
Sleptons lR, lL l
h,H,A Neutralino ?i1-4 Z, ?
H Charginos?i1-2 W
Theoretical limit mh? 140GeV/c2

• Many different models
• MSSM (minimal supersymmetric extension SM)
• mSUGRA (minimal supergravity)
• GMSB
• AMB
• NMSSM

• Conservation of R-parity
• production of SUSY particules in pairs
• (cascade) decays to the lightest sparticle
• LSP stable and neutral neutralino (?1)
• signature missing ET

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At the LHC
Large cross section for squarks and gluinos of
several pb, i.e. several kEvents sum jet-PT and
ET ?effective mass Squarks and gluinos up to
2.5TeV straight forward Largest background for
SUSY is SUSY (but)
SUSY
SM
Large masses means long decay chains Selection
multijet with large PT (typically 150,100,50 GeV)
and OS-SF leptons Invariant masses jet-lepton,
lepton-lepton, lepton-lepton-jet related to masses
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SUSY at the LHC (and ILC)
m0 100GeV m1/2 250GeV A0 -100GeV
tanß 10 sign(µ) favourable for LHC and ILC
(Complementarity)
Moderately heavy gluinos and squarks
Heavy and light gauginos

• t1 lighter than lightest ?
• ? BR 100 t?
• ?2 BR 90 tt
• cascade
• qL ? ?2 q ? lR l q ? l l q?1
• visible

Higgs at the limit of LEP reach

light sleptons
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Examples of measurements at LHC
Gjelsten et al ATLAS-PHYS-2004-007/29
From edges to masses System overconstrained
plus other mass differences and edges
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• Using the kinematical formula (no use of model)
  and a toy MC for the correlated energy scale
  error
• energy scale leptons 0.1
• energy scale jets 1
• Mass determination for 300fb-1 (thus 2014)

Coherent set of measurements for LHC (and ILC)
Physics Interplay of the LHC and ILC Editor G.
Weiglein hep-ph/0410364
Polesello et al use of ?1 from ILC (high
precision) in LHC analyses improves the mass
determination
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From Mass measurements to Parameters

• SFITTER (R. Lafaye, T. Plehn, D. Z.) tool to
  determine supersymmetric parameters from
  measurements
• Models MSUGRA, MSSM, GMSB, AMB
• The workhorses
• Mass spectrum generated by SUSPECT
• (new version interfaced) or SOFTSUSY
• Branching ratios by MSMLIB
• NLO cross sections by Prospino2.0
• MINUIT
• The Technique
• GRID (multidimensional to find a
• non-biased seed, configurable)
• subsequent FIT
• Other approaches
• Fittino (P. Bechtle, K. Desch, P. Wienemann)
• Interpolation (Polesello)
• Analytical calculations

Beenakker et al
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Results for MSUGRA
Once a certain number of measurements are
available, start with the most constrained model
Start SPS1a LHC ILC LHCILC
m0 100 1TeV 1TeV 1TeV
m1/2 250 1TeV 1TeV 1TeV
tanß 10 50 50 50
A0 -100 0GeV 0GeV 0GeV

• Two separate questions
• do we find the right point?
• need and unbiased starting point
• what are the errors?

SPS1a ?LHC ?ILC ?LHCILC
m0 100 3.9 0.09 0.08
m1/2 250 1.7 0.13 0.11
tanß 10 1.1 0.12 0.12
A0 -100 33 4.8 4.3

• Convergence to central point
• errors from LHC
• errors from ILC 0.1
• LHCILC slight improvement
• low mass scalars dominate m0

Sign(µ) fixed
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Masses versus Edges
SPS1a ?LHC masses ?LHCedges
m0 100 3.9 1.2
m1/2 250 1.7 1.0
tanß 10 1.1 0.9
A0 -100 33 20
Sign(µ) fixed

• use of masses improves parameter determination!
• edges to masses is not a simple coordinate
  transformation

?m0 Effect on mlR Effect on mll
1GeV 0.7/50.14 0.4/0.085
Similar effect for m1/2
need correlations to obtain the ultimate
precision from masses.
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Total Error and down/up effect
Theoretical errors (mixture of c2c and educated
guess)
Higgs sleptons Squarks,gluinos Neutralinos, charginos
3GeV 1 3 1
Higgs error Sven Heinemeyer et al.
SPS1a ?LHCILCexp ?LH ILCth
m0 100 0.08 1.2
m1/2 250 0.11 0.7
tanß 10 0.12 0.7
A0 -100 4.3 17
Including theory errors reduces sensitivity by an
order of magnitude
SPS1a SoftSUSYup ?LHCLC
m0 100 95.2 1.1
m1/2 250 249.8 0.5
tanß 10 9.82 0.5
A0 -100 -97 10

• Running down/up
• spectrum generated by SUSPECT
• fit with SOFTSUSY (B. Allanach)
• central values shifted (natural)
• m0 not compatible

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Between MSUGRA and the MSSM

• Start with MSUGRA, then loosen the unification
  criteria,
• less restricted model defined at the GUT scale
• tanß, A0, m1/2 , m0sleptons, m0squarks, mH2 , µ
• experimental errors only

Sfitter-team and Sabine Kraml
SPS1a LHC ?LHC
m0sleptons 100 100 4.6
m0squarks 100 100 50
mH2 10000 9932 42000
m1/2 250 250 3.5
tanß 10 9.82 4.3
A0 -100 -100 181

• Higgs sector undetermined
• only h (mZ) seen
• slepton sector the same as MSUGRA
• light scalars dominate determination of m0
• smaller degradation in other parameters, but
  still precision

The highest mass states do not contain the
maximum information in the scalar sector, but
they do in the Higgs sector!
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MSSM
With more measurements available fit the low
energy parameters
LHC
ILC
LHCILC
MSSM fit bottom-up approach 24 parameters at the
EW scale

• LHC or ILC alone
• certains parameters must be fixed
• LHCILC
• all parameters fitted
• several parameters improved

• Caveat
• LHC errors theory errors
• ILC errors ltlt theory errors
• SPA project improvement of
• theory predictions and standardisation

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Impact of TeVatron Data?
Higgs mass from ??

• With Volker Buescher (Uni Freiburg)
• 2008 too early for Higgs to ?? with 10fb-1 at
  LHC
• only central cascade SUSY measurements are
  available ?1, ?2, qL, lR
• Higgs is sitting on the edge of LEP exclusion
• WHZH 6 events per fb-1 and experiment at
  TeVatron
• end of Run ?mh 2GeV
• adding background ?mh 4-5GeV

No Higgs, edges from the LHC m0 100 14
GeV m1/2 250 10 GeV tanß 10 144 A0
-100.37 2400 GeV
Higgs hint plus edges from the LHC m0 100
9 GeV m1/2 250 9 GeV tanß 10 31
A0 -100 685 GeV

• A hint of Higgs from the TeVatron would help the
  LHC at least the first year!
• mtop from TeVatron with 2GeV precision makes
  impact on fit negligible

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And the Egret point?
Tri-lepton signal promissing
Les Houches 2005 P. Gris, L. Serin, L.Tompkins,
D.Z.

• Measurements
• Higgs masses h,H,A
• mass difference ?2-?1
• mass difference g- ?2
• Sufficient for MSUGRA

m0 1400 (50 530)GeV m1/2 180 (2-12)
GeV A0 700 (181-350) GeV tanß 51
(0.33-2)

• Uncertainties
• b quark mass
• t quark mass
• Higgs mass prediction

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Conclusions

• Construction of ATLAS-EM calorimeter modules
  finished
• Testbeam studies have driven the improvement of
  the understanding
• of the combined optimisation of linearity and
  resolution of the calorimeter
• EM calibration under control
• electron (and photon identification) are at the
  required level
• with multivariate approaches under study
• SFitter (and Fittino) will be essential to
  determine SUSYs fundamental
• parameters
• mass differences, edges and thresholds are more
  sensitive than masses
• the LHC will be able to measure the parameters
  at the level
• LC will improve by a factor 10
• LHCLC reduces the model dependence
• EGRET in MSUGRA, LHC has enough potential
  measurements to
• confront the hypothesis
• Many thanks to Laurent Serin for his help in the
  preparation of the talk!