Search for Standard Mod el Higgs in Two Photon Final State at ATLAS
description
Transcript of Search for Standard Mod el Higgs in Two Photon Final State at ATLAS
Search for Standard Model Higgs in Two Photon Final State
at ATLAS
HYEON JIN KIMJUNE 25, 2010
Outline• Standard Model and Higgs Boson• ATLAS at the LHC• Photon and Electron Identification (ID) in
ATLAS with a Covariant Matrix based Method (H-matrix)
• A Data Driven Method for Photon Identification Efficiency Measurement
• Photons Showers in ATLAS Cosmic-ray Muon Data
• Prospect for Higgs Search using H ➝ • Conclusions
June 25, 2010 2Search for H → γ γ
STANDARD MODEL AND HIGGS BOSON
Standard Model
June 25, 2010 4Search for H → γ γ
• The Standard Model of particle physics describes elementary particles and how they interact. • Matter is made of fermions.
✒ Leptons and quarks• The interactions between
elementary particles ✒ The electromagnetic, the strong and the weak interactions ✒ mediated by particles called gauge bosons.• Gauge invariance requires all
these particles to be massless!✒ Experimental values of the masses of
the W and Z gauge bosons suggest otherwise.
✒ ∼85-90 times the mass of a proton
Higgs Mechanism• Higgs mechanism can give mass to
W, Z bosons without breaking gauge invariance.✒ It keeps the photon massless.
• The Higgs boson has not yet been observed experimentally.✒ The search for the Higgs boson is one
of the most important goals of the ATLAS experiment at the Large Hadron Collider (LHC).
• Despite the prediction of Higgs, the theory does not provide a direct estimate of its mass. ✒ The LEP experiments have set a 95% confidence level
(CL) lower limit on the Higgs mass: mH > 114.4 GeV @ 95% CL.
June 25, 2010 5Search for H → γ γ
Higgs production & decay mode at LHC
• Large center of mass energy ✒ Gluon fusion is the dominant production channel over the whole range
• H ➝ has relatively small branching ratio but a clean signature with two back-to-back photons✒ The EM calorimeter identify electrons and photons against overwhelming
background from hadronic jets June 25, 2010 6Search for H → γ γ
Gluon Fusion
Vector Boson Fusion
ATLAS at the LHC
LHC (Large Hadron Collider)
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Lake of Geneva
Airport
CMS
ATLAS
LHCb
ALICE
• s = 14 TeV (7 times higher than Tevatron) search for new massive particles up to m ~ 5 TeV• Ldesign = 1034 cm-2 s-1 (>102 higher than Tevatron) search for rare processes with small σ (N = Lσ )
ATLAS (A Toroidal LHC Aparatus)
June 25, 2010 9Search for H → γ γ
Proton Beam
Proton Beam
Installed just across the CERN main site, 92 m below ground.
Tile barrel
Tile extended barrel
LAr forward calorimeter
LAr hadronic end-cap
LAr EM end-cap
LAr EM barrel
Electromagnetic (EM) CalorimeterMeasure energy and direction of &
e
• Presampler (|| < 1.8) ✒ correct for energy lost in dead
material in front of calorimeter.
• The barrel EM calorimeter (||<1.475) ✒ 1st layer : /0 separation, position measurement ✒ 2nd layer : main energy measurement ✒ 3rd layer : high energy shower tails Hadron/EM separation
• The end-cap calorimeter (1.375< ||< 3.2)
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accordion-shaped
PHOTON AND ELECTRON IDENTIFICATION IN ATLAS WITH
A COVARIANT MATRIX BASED METHOD (H-matrix)
Motivation• e/ identification with high efficiency and high rejection
against jets is crucial for H ➝ search• Measure and understand e/ ID efficiencies and background
rejection✒ Improve Higgs search efficiency
• Selection of e/ from jets is based on & their characteristic features in EM calorimeter.
• Covariant matrix technique (H-matrix ) w/ used at DØ for e-ID✒ Used EM shower shape correlations ✒ Proved to be a great tool for e/ and hadrons separation
• Benefit from fine cell sizes of ATLAS Calorimeter • Improve e/ ID by generating a 2 quantity utilizing H-matrix
technique
June 25, 2010 12Search for H → γ γ
Principle of H-matrix• H-Matrix exploits the correlation in transverse and longitudinal electromagnetic shower shapes. • The correlations between the variables are reflected through the covariant matrix, M, whose elements are
• e/-likeness is presented by 2 a given candidate object m.
where, Hij (covariant matrix)-1 and yi is discriminating variables. • A shower that closely resembles an e or shower will have a
m2 ~ n dim.
June 25, 2010 13Search for H → γ γ
( ) ( )dim
2 ( ) ( )
, 1
m mm i i ij j j
i j
y y H y yχ=
= − −∑
( )( )( ) ( )
1
1 Nn n
ij i i j jn
M y y y yN
γ
2
Discriminating Variables (i)• Longitudinal Variables
✒ Fractional energies in each layer of EM cal (fi, i =0~3).✒ Fractional energy in 1st layer of hadronic cal (f4)
• Transverse Variables✒ Fractional energy in shower core (R37).✒ The second layer of EM calorimeter
a. The Ratio of energy in 3x7 over 7x7 (R) & in 3x3 over 3x7 (Rφ)b. Lateral width in (ω2)
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f2R ω2
f4
Discriminating Variables (ii)
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• Transverse Variables✒ The first layer of EM calorimeter
a. Shower width over 3 strips around maximal energy deposit (ω3stips)b. Shower width over 20 strips (ωtot1)c. Energy fraction outside of shower core (Fside)d. Energy difference (ΔE) & fractional energy of 2nd maximal energy (Rmax2) in
1st layer EM calorimeter
Fside Rmax2
ω3strips
ΔE = Emin – Emax2
Photons at 1.52 < ||
< 1.8
Mean values & Covariant Matrix M• Build H-matrix separately for e and
✒ The shower shapes are different b/w electron and photon.✒ The single electron and photon MC samples
• The discriminating variables have energy and position (in ) dependences• The covariant matrix is parameterized by using energy & .
June 25, 2010 16Search for H → γ γ
200 GeV electrons
• 12 subdivisions of based on granularities & the thickness of absorber in EM calorimeter.
Available instrumentation in region
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Dim = 14 Barrel absorber thickness 11 || < 0.2
2 0.2 ≤ || < 0.4
3 0.4 ≤ || < 0.6
4 0.6 ≤ || < 0.8Dim = 14 Barrel absorber thickness 2
5 0.8≤ || < 1.0
6 1.0 ≤ || < 1.2
7 1.2 ≤ || < 1.37
Dim = 14 End-cap w/ presampler8 1.52 ≤ || < 1.8
Crack region 1.37 ≤ || < 1.52 no H-matrix
Dim = 13 End-cap w/o presampler9 1.8 ≤ || < 2.0
10 2.0≤ || < 2.2
11 2.2 ≤ || < 2.37
Dim = 8 End-cap w/o presampler & strips
12 2.37 ≤ || < 2.47
• Mean values are parameterized as function of energy.✒ f3 : ✒ others :✒ f4, ΔE and Rmax2 : Linear interpolation between the two adjacent energy
points• Determine the energy dependence of M
✒ Linear interpolation between the two adjacent energy points
Parameterization
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Single electrons samples at 0.6 < ||< 0.8
€
y i(E) = a× E + b× 1E+ c
€
y i(E) = a×1E+ b× 1
E+ c
1.0 < ||< 1.2
€
M( f1, ωtot1)
= 1N
( f1(n ) − f1)(ωtot1
(n ) −ω tot1)n=1
N
∑
H-matrix for Background
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Jet H-matrix
jet2
• To enhance H-matrix performance, H-matrix is need to be optimized using information of both signal and background (i.e. jets)✒ Log-likelihood ratio : the exact shapes of background for p.d.f.
construction ✒ Cut-based algorithm: sets the cuts values by looking at both the signal
and backgrounds shapes
• To incorporate background shape, H-matrix for background is built.
• -jet samples in different ET
ranges are used for jet H-matrix.
• Photon H-matrix incorporate jet H-matrix.
✒ 2 = ½ (2 jet
2) for combined photon and jet H-matrix
Obtained from H → (mH = 120 GeV) & dijet samples
γ2
• Efficiency and rejection ✒ Efficiency (ε) = ✒ Rejection =
H-matrix Performance• Samples : generated by PYTHIA
and full detector simulation ✒ Z → ee✒ H → with mH = 120 GeV ✒ Highly EM dijet sample
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€
Ne /γreco
Ne /γtrue
( ) ( )dim
2 ( ) ( )
, 1
m mm i i ij j j
i j
y y H y yχ=
= − −∑ €
nN jets
N fake
• Using means values of shower variables and covariant matrix M, 2 is calculated by
Photon H-matrix
Photon-jet H-matrix
e2
Electron H-matrix
Electron H-matrix Performance
• H-matrix performance compared to cut-based method✒ The tune of e
2 cut values in different ET bins
✒ Provides the same efficiency at the cut-based in each ET bin.
• Rejection power calculated ✒ H-matrix shows better
rejection.June 25, 2010 21Search for H → γ γ
Photon–jet H-matrix
Photon–jet H-matrix Performance• Efficiency change with ET
✒ Adjust the 2 cut value in different
ET bins to make the efficiency constant with respect to ET of the photon.
• Tuned 2 cut values to give same efficiency as cut-based algorithm
✒ Its performance equivalent to that of cut-based algorithm.
June 25, 2010 22Search for H → γ γ
Combined photon and jet H-matrix enhance photon H-matrix performance.
Photon H-matrix
Photon-jet H-matrix
Systematic Uncertainty
Source Relative Error
EM energy scale ± 0.2 %
Data to simulation discrepancies
± 0.33%
Total ± 0.4%
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Emeasured = Etrue (1+0.02)
• Effect of data to simulation discrepancies in shower shapes
✒ Shower property differ in data from their distribution from simulation✒ Measure the potential effect of data to simulation discrepancies on the performance of the H-matrix
• Effect of different EM scales in data and simulation
✒ EM scale uncertainty is known to about 2%In early period of ATLAS data taking.✒ Emeasured /Etrue is 1.00 ±0.02
Emeasured = Etrue (1- 0.02)
Discrepancies : 0.5% ~ 5%
A DATA DRIVEN METHOD FOR
PHOTON IDENTIFICATION EFFICIENCY MEASUREMENT
• Pure photon sample is important✒ To measure photon efficiency✒ To understand shower shapes
• No known physics process to give pure photon samples.• Z→μμ is source of pure photons at high center of mass and luminosity.• This method tested by using Z→μμ MC sample• Z→μμ events in Z→μμ are selected by :
✒ Photon non collinear to muons✒ Invariant mass cut of 2 muons and photon
Motivation
June 25, 2010 25Search for H → γ γ radiation
FSR (Final state radiation)
ISR (Initial state radiation)
3-body decay
Simulation Samples and Event Selection• Sample (√s = 10 TeV)
✒ Signal : Z→μμ generated by PYTHIA , ALPGEN and full detector simulation
✒ Background a. tt (MC@NLO + JIMMY)b. gg → WW → μμ (gg2WW + JIMMY)c. bb → μμ (PYTHIAB)
• Z➝μμ event selection✒ Cut A: select 2 muons per event (ETμ1 > 20 GeV, ETμ2 > 6 GeV )✒ Cut B: cut A+ iso cut to muon (Et cone < 5 GeV)✒ Cut C: cut B + 1 loose photon per event (ET > 10 GeV)✒ Cut D: cut C+ ΔR cut (Min(ΔR(μ1, ), ΔR(μ2, )) >0.2) where ΔR = √(Δφ2 + Δ2)✒ Cut E: cut D+ Mass cut (81 < Mμμ < 101 GeV)
June 25, 2010 26Search for H → γ γ
Kinematic Variables
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Photons fr Z →μμ,Photons fr H → (mH = 120
GeV/c2)
Shower Shape Variables
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Photons fr Z →μμPhotons fr H → (mH = 120 GeV/c2)
• Photons from Z→ μμ have identical shower shape to photons from H→ .• These photons can be used to measure photon efficiency in data.
Required 30 < ET < 40 GeV
f0
Fside
Efficiency of in Z➝μμ events• Photon efficiency from Z→ μμ shows consistent behavior with H → • The photons in Z→ μμ can be used to measure photon efficiency.
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Efficiency of H-Matrix vs. ET Efficiency of cut-based ID vs. ET
H→ Z→μμ
H→ Z→μμ
Cross-section = 1143 pb for Z→ μμ
Statistical Uncertainty
June 25, 2010 30Search for H → γ γ
• The expected statistical error versus luminosity for different ET bins. • This graph takes only into account the 1/√N behavior of the statistical error in each bin
For 200 pb−1 2% for 10 < ET <
20 GeV, 3% for 20 < ET <
40 GeV, 4% for 40 < ET<
60 GeV.
√s = 10 TeV
Sources of Background Photons in pp➝Z ➝ μμ Events
June 25, 2010 31Search for H → γ γ
Process 10 < ET < 25 GeV ET > 25 GeV ET > 10 GeV
Inner brem 201 701 902 (74%)
Early showering of inner brem
29 103 132 (11%)
Hadron decay (ω, η, η’, π0 )
4 164 168 (14%)
ISR or FSR from parton 0 10 10 (1%)
Inner brem 171 516 687 (85%)
Early showering of inner brem
24 72 96 (12%)
Hadron decay (ω, η, η’, π0 )
2 21 23 (3%)
ISR or FSR from parton 0 1 1 (0.1%)
85< M < 95 GeV
81< M < 101 GeV
Contamination by Other Standard Model Processes
June 25, 2010 32Search for H → γ γ
Integrated luminosity : 200pb-1
Center of mass energy : √s = 10 TeV
Z → μμ(Pythia)
Z → μμ(Alpgen)
WW→μμ tt bb →μμ
Cut A 120292 113032 117 2548 289851
Cut B 114094 107669 107 910 28621
Cut C 3670 2837 6 180 1363
Cut D 3354 2597 5 168 454
Cut E 1148 ±230
1078±216
0.6±0.2 24±4.8
54±27
Mμμ (GeV)
Extrapolation to other Samples, Different distribution
June 25, 2010 33Search for H → γ γ
• The photon identification efficiency is dependent on of the photon.
✒ The total efficiency will not be correct if the photon efficiency derived from the photons from Z → μμ is applied to samples with different distribution.
• To estimate the size of this effect, the photon efficiency is calculated in a -jet sample in different bins
PHOTON SHOWER IN ATLAS COSMIC-RAY
MUON DATA
Motivation• To understand actual detector and e/ ID performance, we
need to compare in data and simulation
✒ Low level calorimeter quantities (noise, resolutions, …)✒ Intermediate level quantities (energy fractions, shower variables)✒ High level (efficiency and rejection of electron/photon ID tools)
• The ATLAS cosmic data from 2008 contain O(108) events• Large sample of EM showers in ATLAS cosmic data
✒ The high-energy bremsstrahlung photons produced from cosmic muons✒ Actual shower distribution in data
• Unlike photon from collision, photon from cosmic-ray muon has different energy profile in each layer of EM calorimeter✒ Shower shape distribution may differ✒ Study shower shape with place where photon emitted from cosmic muon. June 25, 2010 35Search for H → γ γ
Photon Emission Point (i)• Find photon emission point from
muon in cosmic✒ Photon shower variables are
sensitive depending on where photon radiated from muon track
✒ Track parameters of muon & positions of EM shower in the1st and 2nd layers
✒ The interception point of muon track and photon trajectory
• X and Y : the transverse coordinates of the emission points of the photons from μ → μ
• R = √ X2 + Y
2
✒ equivalent to the true value of μ → μ vertex radius Rvertex
June 25, 2010 36Search for H → γ γ
R √ X2 + Y
2
Photon Emission Point (ii)• The most probable value for R corresponds to middle of EM• Photon have less probability to be recognized as photon if
the shower occurs in different region of ATLAS
June 25, 2010 37Search for H → γ γ
Rγ - Rvertex
Cosmic Data and Simulation• Data: Triggered by L1Calo and IDCosmic data streams
✒ merged two data stream with removing double counted events
• Cosmic simulation : produced with inner detector volume
June 25, 2010 38Search for H → γ γ
Preselection ID Cosmic L1Calo Cosmic MC≥ 1 μ (φμ< 0) 3.7x106 3.6x106 9.1x106
+ 1 γ 35191 246852 53428
+ pT(γ) > 5GeV 20778 170429 26584
+ μ has ID track 7276 8449 5699
+ After duplicate removal 10241 5699
Cut Flow
Comparison of Kinematic Variables• Kinematic variables of photon in MC & data have good agreement.• Impact parameter d0 of muon shows difference in MC & data
✒ It could be the differences of trigger & tracking efficiencies in MC & data
June 25, 2010 39Search for H → γ γ
Shower Shape Comparison • Longitudinal shower variables
June 25, 2010 40Search for H → γ γ
• Most distributions of shower variables are in agreement between data & MC• Data is well modeled by simulation.• Z→ μμ allows to do similar studies in collision data with much higher precision
PROSPECT FOR HIGGS SEARCH
USING H ➝
Signal and Background Process• Signal process (√s = 10 TeV )
✒ Gluon fusion process : masses of Higgs are 115, 120, 130, and 140 GeV/c2
• Background processes (√s = 10 TeV )✒ Irreducible background
a. Two prompt photons from qq → or gg → qb. Bremsstrahlung from qg → q → q .
✒ Reducible backgrounda. -jet events where a leading 0 in a jet has been misidentified as one photon b. jet-jet events where both jets have been misidentified as photons.
• Signal selection✒ cuts : || < 1.37 or 1.52 < || < 2. 37 (remove crack regions) ✒ pT cut on photons : pT1 > 40 GeV, pT2> 25 GeV
June 25, 2010 42Search for H → γ γ
Kinematic Variables
June 25, 2010 43Search for H → γ γ
Leading photon
Subleading photon
H ➝ (mH = 120 GeV/c2)
H ➝ (mH = 140 GeV/c2)
√s = 10 TeV √s = 10 TeV
Signal Significance
Mass(mH)
(2 < 3) (2 < 5)Signal Btot S/√Btot Signal Btot S/√Btot
115 375 9066 3.9 446 11637 4.1
120 455 14046 3.8 541 18784 3.9
130 409 7411 4.8 487 10105 4.8
140 301 7471 3.5 358 9598 3.7
June 25, 2010 44Search for H → γ γ
• Signal significance : expected number of signal and background events.
• Requiring event preselection, mass cut mH ± 1.4σ and H-matrix cut.
• Using the fake rates and efficiency for different 2 cut values the expected number of photon events at 100 fb−1 and √s = 10 TeV are obtained.
Conclusions (i)• A covariant matrix based algorithm has been developed to
identify electrons and photons.✒ Exploits the high granularity of the ATLAS EM calorimeter and use
correlations between various EM shower shape variables✒ To enhance further the jet rejection a jet H-matrix has been built and
combined with the photon H-matrix.✒ The electron H-matrix shows significantly better performance than the
current standard ATLAS cut-based electron. ✒ The combined photon-jet H-matrix shows also excellent jet rejection
but is comparable to the ATLAS cut-based method
• Prior to the LHC beam, considerable amount of cosmic data were collected with the ATLAS detector✒ Provided a great opportunity to study the detector response and
compare it to the predictions of the simulation✒ The shower shapes of photon in the cosmic-ray data and simulation are
in good agreement. ✒ The shower shape variables produced by the GEANT simulation can be
relied on.June 25, 2010 45Search for H → γ γ
Conclusions (ii)• A new process has been studied that will allow to measure the
photon identification efficiency directly with the ATLAS data. ✒ Using bremsstrahlung photons in Z → μμ events a pure sample of prompt
photons can be isolated.✒ It is possible to precisely extract efficiencies for photons with ET below 40 GeV
• H → is very challenging and will only be possible to discover this signal once the ATLAS and the LHC have reached their design performance. ✒ The photon H-matrix provides a powerful tool to reject the γ +jet and jet-jet
backgrounds to the H → signal.
• The validation of the photon H-matrix should become possible in data with the Z → μμ events well before the search for H → becomes statistically competitive.
• With the upcoming ATLAS data it will soon be possible to measure the photon identification performance in real data
(Now ready for data in Higgs search)June 25, 2010 46Search for H → γ γ
Backup
The Latest Result From Tevatron• The LEP EW working group has combined the experimental data
from several precision EW measurements of SM parameters. ✒ the LEP experiment has set a 95% confidence level (CL) limit on the Higgs
mass: mH > 114.4 GeV @ 95% CL.
June 25, 2010 48Search for H → γ γMH = 85 GeV/c2+35
-27
H ➝ channel• Very rare decay (BR ~10-3)• Background
✒ Irreducible: continuum✒ Reducible: -jet and jet-jet
• Keys✒ Excellent energy and angular resolutions, ✒ Excellent efficiency, jet rejection✒ High granularity and response uniformity✒ H width negligible, resolution dominated by detector✒ σ(M)/M
June 25, 2010 49Search for H → γ γ
pp
H
ATLAS Coordinate System• The ATLAS Coordinate System is a right-handed system• The x-axis pointing to the centre of the LHC ring, the z-axis
following the beam direction and the y-axis going upwards. ✒ At ATLAS positive z points towards LHCb. ✒ The azimuthal angle φ = 0 corresponds to the positive x-axis and φ increases clock-wise looking into the positive z direction. ✒ The polar angle θ is measured from the positive z axis.
June 25, 2010 50Search for H → γ γ
Parameterization of Shower Variables • Mean value of shower shape variables vary with incident energy of
e/γ• Mean values are parameterized as function of energy.
✒ f4, ΔE and Rmax2 : Linear interpolation between the two adjacent energy points
✒ f3 : ✒ others :
June 25, 2010 51Search for H → γ γ
Single electrons samples at 0.6 < ||< 0.8
€
y i(E) = a× E + b× 1E+ c
€
y i(E) = a×1E+ b × 1
E+ c
Covariant Matrix • Using mean values of shower variables the covariant
matrix M are calculated at each bins e.g:
• Determine the energy dependence of Mij ✒ Linear interpolation between the two adjacent energy points
June 25, 2010 52Search for H → γ γ
€
M( f1, ω tot1) =1N
( f1(n ) − f1)(ω tot1
(n ) −ω tot1)n=1
N
∑
||< 0.2 1.0 < ||< 1.2
γ2
2 of H-matrix• Using means values of shower variables and covariant
matrix M, 2 is calculated by
• The 2 distribution of H-Matrix ✒ 2 for jet MC sample is compared with that obtained from real photon in MC H➝ ✒ shows dramatic difference
June 25, 2010 53Search for H → γ γ
( ) ( )dim
2 ( ) ( )
, 1
m mm i i ij j j
i j
y y H y yχ=
= − −∑
Photon H-matrix
Electron H-matrix Performance (i)• Samples : generated by Pythia and full detector simulation
✒ Z ➝ ee✒ H ➝ with mH = 120 GeV
• Event selection ✒ Electrons are within ∆R < 0.2 of the Monte Carlo truth electron
resulting from the Z decay. ✒ Electrons are in 0 ≤ || ≤ 1.37 or 1.52 ≤ || ≤ 2.47 ✒ Jets have ET >17 GeV and are in 0 ≤ || ≤ 1.37 or 1.52 ≤ || ≤ 2.47
• Efficiency and rejection ✒ Efficiency (ε) = ( : # of true e and : # of
reconstructed e pass selection) ✒ Rejection = ( : # of jets, : # of fake photons in
jets pass event selection and : # of jets per events)June 25, 2010 54Search for H → γ γ€
nN jets
N fake€
Nereco
Netrue
€
Nereco
€
Netrue
€
N fake
€
N jets
€
n
Photon H-matrix Performance (i)• Samples : generated by Pythia and full detector simulation
✒ H ➝ with mH = 120 GeV ✒ Highly EM dijet sample.
• Event selection ✒ Photons are within ∆R < 0.2 of the Monte Carlo truth electrons
resulting from the H decay. ✒ Photons are in 0 ≤ || ≤ 1.37 or 1.52 ≤ || ≤ 2.37 ✒ Jets have ET >25 GeV and are in 0 ≤ || ≤ 1.37 or 1.52 ≤ || ≤ 2.37
• Efficiency and rejection ✒ Efficiency (ε) = ( : # of true and : # of
reconstructed pass selection) ✒ Rejection = ( : # of jets, : # of fake photons in jets
pass event selection and : # of jets per events)June 25, 2010 55Search for H → γ γ€
nN jets
N fake€
Nγreco
Nγtrue
€
Nγreco
€
Nγtrue
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N fake
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N jets
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n
Photon H-matrix Performance (ii)
June 25, 2010 56Search for H → γ γ
• Efficiency change with ET✒ Adjust the
2 cut value in different ET bins to make the efficiency constant with respect to ET of the photon.
• The track isolation cut ✒ additional rejection against jets, but leads to slightly lower
efficiency
ET of jets and photons > 25 GeV
Shower Shape Comparison (i)
June 25, 2010 57Search for H → γ γ
• Shower variables in the 2nd layer variables
Shower Shape Comparison (ii)
June 25, 2010 58Search for H → γ γ
• Shower shape variables in the 1st layer
Sample B
ID
LArTile
RID
Sample C
Shower Shape with R
June 25, 2010 59Search for H → γ γ
Sample A
Clearly there is difference in 3 samples
Sample A: R < RID
Sample B: R ≥ RID & φγ > 0
Sample C: R ≥ RID & φγ < 0
ωtot1
Shower Shape with R
• the EM shower in sample B is more wider than sample C
• sample B : shower initiated in the 3rd layer of EM or Tile
• sample C: shower initiated in the 1st layer of EM
June 25, 2010 60Search for H → γ γ
In the sample C, photon emitted in the lower hemisphere has
similar behavior as photon from collision
Discriminating Variables• Z➝μμ events in Z➝μμ are selected by :
✒ Photon non collinear to muons ✒ Invariant mass cut of 2 muons and photon
June 25, 2010 61Search for H → γ γ
3-body decay
Detector brem
Shower Shape Variables
June 25, 2010 62Search for H → γ γ
Photons fr Z →μμPhotons fr H →
Photons fr Z →μμPhotons fr H →
Photons fr Z →μμPhotons fr H →
Photons fr Z →μμPhotons fr H →
Shower Shape Variables
June 25, 2010 63Search for H → γ γ
Photons fr Z →μμPhotons fr H →
Photons fr Z →μμPhotons fr H →
Photons fr Z →μμPhotons fr H →
Photons fr Z →μμPhotons fr H →
Motivation• Higgs boson is the last missing building block of the Standard Model.• The Higgs decaying to two photon final state is one of the cleanest
discovery channels for Higgs in the low mass range 115 < mH ≤ 150 GeV/c2.
• The H→ signal should be visible as a small peak above background. • This channel is challenging due to the its low branching ratio times
cross section and the high QCD cross-section of the background.
June 25, 2010 64Search for H → γ γ
(a)Gluon fusion : gg H➝ (b)Vector boson (W/Z ) fusion
(VBF) : qq ➝ W+ W−, Z Z ➝ qqH(c) tt associated production : qq, gg ➝ tt + H (d) W/Z associated production : qq ➝ (W, Z ) ➝ (W, Z ) +
H
Distribution of m
June 25, 2010 65Search for H → γ γmH [GeV]
• The expected diphoton mass spectrum after the application of event selections at an integrated luminosity of 100 fb−1
• The background contributions are obtained with MC samples normalized to their cross-sections.
Introduction (i)• The search for the Higgs particle is one of the most important goals of the
ATLAS experiment at the Large Hadron Collider (LHC). ✒ The ATLAS electromagnetic (EM) calorimeter measures the energy and direction of electrons and photons ✒ The EM calorimeter identify electrons and photons against overwhelming background from hadronic jets
• The discrimination against background from jets can be achieved by measuring the detailed shape of the EM showers.
✒ The shower shape variables are correlated.
• The covariant matrix technique, or H-matrix method, used correlations b/w shower shape for electron and photon identification.
June 25, 2010 66Search for H → γ γ
Introduction (ii)• It is important to validate the Monte Carlo simulation modeling of the ATLAS
detector ✒ High-energy bremsstrahlung photons produced by cosmic ray muons passing through the ATLAS calorimeter ✒ The shower shape variables from the cosmic ray data are compared with the prediction from the Monte Carlo simulation.
• The process Z µµγ is studied as a possible signal in the upcoming ATLAS ➝data to measure the photon identification efficiency.
✒ This channel could provide a pure sample of photon at the large integrated luminosity expected at the LHC
June 25, 2010 67Search for H → γ γ
Signal Significance
Mass(mH)
Signal(2 < 3)
Background (2 < 3) Btot S/√Btot
γγ γ-jet jet-jet
115 375 7593 34.88 1438 9066 3.9
120 455 10431 85.62 3529 14046 3.8
130 409 5180 52.85 2178 7411 4.8
140 301 6244 29.07 1298 7471 3.5
June 25, 2010 68Search for H → γ γ
Mass(mH)
Signal(2 < 5)
Background (2 < 5) Btot S/√Btot
-jet jet-jet
115 446 9036 51.68 2549 11637 4.1
120 541 12414 126.59 6243 18784 3.9
130 487 6165 78.31 3862 10105 4.8
140 358 7431 43.07 2124 9598 3.7
• Signal significance : expected number of signal and background events. • Requiring event preselection, mass cut mH ± 1.4σ and H-matrix cut.
June 25, 2010 69Search for H → γ γ