# Presentation: 593124

## Studies of ppW/Z+ (W/Z 2jets)

- Sources of the background
- MC generators
- Setting the limit

- Marina Brozovic, Duke University, 02/07/02

## 2 jet + photon background

- 2 jet +  processes
- Most of the processes produce a photon by radiation from a quark. The jets can be coming from  gluons or quarks.
- The Monte Carlo consists of 3 parts:
-                    1. Owens LO matrix elements
-                    2. Herwig
-                    3. QFL

- Marina Brozovic, Duke University, 02/07/02

## 3 jet background

- 3 jet process, where 1 jet fakes a photon
- We generate 2 to 2 process in PYTHIA(gg  gg, gg  qiqbari,
-       qi qj  qi qj,  qi g  qi g)
- after QFL, look for the events that due to gluon radiation and hadronization have 3 or more jets.
- DIBOSON group code calculates  the probability of central jet faking a photon. It also gives us the 4-vector of the fake photon. It is VERY difficult to fake a 23~GeV photon.

- Marina Brozovic, Duke University, 02/07/02

## Photon cuts

-         ppW/Z+ (W/Z  jets) events generated = 199508
-  ***********************************
-  PHOTONS
-  cnt_reg   = 124032     photon central
-  cnt_fid    = 108668     photon fiducial
-  cnt_3dt   = 94099       num 3D tracks <= 1
-  cnt_nwns= 93667      num strip hits,num wire hits >=1
-  cnt_spt4  = 64813      sum pt in 0.4 cone
-  cnt_is4    = 62853      isolation in 0.4
-  cnt_lsht   = 62061      lateral sharing and HAD/EM
-  cnt_chav = 61621      average chi**2<20.
-  cnt_es2   = 61167      cuts on strip energy
-  cnt_ew2  = 60637      cuts on wire energy
-  cnt_et      = 31212      Et>23 GeV
-  cnt_1pho = 31204      1 photon only
-  cnt_trig   =  24832      photon trigger

- Marina Brozovic, Duke University, 02/07/02

## Jet Cuts

- --------------------------
-  JETS
-  --------------------------
-  cnj_num  = 12564    num jets=2,(Et>10,|deta|<2.4)
-  cnj_et       =  10963    et jet1 and jet2 >15 GeV
-  cnj_track  = 9857     num tracks jet1,jet2>0
-  cnj_dvtx   =  9857    |vtx_jet1-vtx_jet2|<10 cm
-  cnj_rms    = 9844     rms jet_vtx1 and jet_vtx2 <5 cm
-  cnj_rjj      =  8388   Delta r (jet-jet)>2.
-  ---------------------------
-  cnt_vtx=  8388  z  vertex <60 cm                     Z all jets      W all jets
-  **efficiency: 4.2% ,********events=90pb****-1****(6.5+6.35)pb*0.042**
-                                                **49 W/Z + ******** events**

- Marina Brozovic, Duke University, 02/07/02

## 2 jet + background

-  Et > 15 GeV,  |d|<2.4

-  Et > 15 GeV,  |d|<1.1

- Marina Brozovic, Duke University, 02/07/02

## Relative sizes of the backgrounds

**2 jet + photon**
- Et (jet) > 5 GeV
- Et() > 12 GeV
- =13 nb

**3 jet (fake photon) **
- Et(jet) > 15 GeV**          **
- gg  gg             pythia=41  nb
- gg  q qbar       pythia=2    nb
- qi qj qi qj              pythia=5.7 nb
- q g  qg            pythia=32  nb
-                      total**(2 ******** 2 )=**80.7  nb

- Marina Brozovic, Duke University, 02/07/02

## Relative sizes of the backgrounds cont.

**3 jet (fake photon) **
- total(**2 ******** 2 **)=80 nb

**2 jet + photon**
- =13 nb
- 852 056 events generated
- 4 465 pass all the cuts
**0.068 nb**

- Marina Brozovic, Duke University, 02/07/02

## Setting the limit

******S(m) dm=1   signal**

******B(m) dm=1  MC 2jet background**

- Generate sample of N0  events according to distribution B(m)
- Observable function is some mixture of   signal and background
-                          **D(m,f)=N****0*****( (1-f)*B(m) + f*S(m) )**

- Marina Brozovic, Duke University, 02/07/02

## Adjusting the background to data 

- 2 jet + background vs. data

- Weights

- 2 jet + background adjusted to data

- Marina Brozovic, Duke University, 02/07/02

## Finding the ratio fmin

- We have to find which ratio f of the signal and background fits the best to the data D(m,f)=N0*( (1-f)*B(m) + f*S(m) )
- Run f from –1 to 1 in iterations of 0.1, and calculate for each f its  2
-                                     2(f)=(Ni-(mi,f))2  / (Ni)2
- (mi,f)=D(m,f) dm  is the number of events in particular             mass bin
- N0= Ni, (Ni)=Ni
- From the 2(f) distribution, we determine fmin
- Repeat the procedure on many samples, so that we get fmin distribution

- Marina Brozovic, Duke University, 02/07/02

## Example of the procedure

- Marina Brozovic, Duke University, 02/07/02

## Setting the limit for the data

**f****95%(CL) ****<0.0282**

- 2min

- 2min+4    95% CL

- 

- 2

- 2

- f

- fmin

- 2min+1   68% CL

- Marina Brozovic, Duke University, 02/07/02

## fmin distribution

- Marina Brozovic, Duke University, 02/07/02

## Conclusions

**Limit  for the number of events:**** **
**                **Nselected* **f****95%(CL)**  <** ****153**       **95%CL**
-                                                        (SM predicts 49)
- Systematic errors have to be added....

**Limit  for the cross section*BR:**
- (ppW+)*BR(W2jet)+(ppZ+)*BR(Z2jet) =
-                         Nselected* **f****95%(CL)**    <   **38pb         95%CL**
**                         **Luminosity*efficiency               (SM predicts 13 pb)

- Marina Brozovic, Duke University, 02/07/02