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


• 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.


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)


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)


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)


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


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.


( ) ( )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)


f2R ω2

f4

Discriminating Variables (ii)


• 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 & .


200 GeV electrons

• 12 subdivisions of based on granularities & the thickness of absorber in EM calorimeter.

Available instrumentation in region


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


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


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


€

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.


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%


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)


Kinematic Variables


Photons fr Z →μμ,Photons fr H → (mH = 120

GeV/c2)

Shower Shape Variables


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.


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


• 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


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


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


• 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


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


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


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


Shower Shape Comparison • Longitudinal shower variables


• 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


Kinematic Variables


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


• 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


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.


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 :


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


€

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


( ) ( )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

€

N fake

€

N jets

€

n

Photon H-matrix Performance (ii)


• 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)


• Shower variables in the 2nd layer variables

Shower Shape Comparison (ii)


• Shower shape variables in the 1st layer

Sample B

ID

LArTile

RID

Sample C

Shower Shape with R


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


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


3-body decay

Detector brem



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.


(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.


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


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


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.


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Search for Standard Mod el Higgs in Two Photon Final State at ATLAS

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