1. 2vtx tagged dijets mass resolution study
Univeristy of Notre Dame
Hong Luo Mar 16th 2005

2. Get the Pt resolution of 2vtx tagged Jet from data.
Method
Get the Pt resolution of 2vtx tagged Jet from data.
Use the Pt resolution to do the Jet Pt smearing for QCD MC samples, then get the mass resolution.
Data selection:
All QCD trigger data (by d0correct v ) up to April, 2004 in Common Sample Group: ~32Million events ( pb-1 ) .
Secondary Vertices skimmed:
Removed bad events. (offline data quality: SMT,CAL,CFT,MUO &JET)
Request both two leading jets contained a secondary vertex.
Central region requirement: Both jets with |Rapidity|< ~20200 events.

3. Jet Pt resolution study
X: Average Jet Pt : (Pt0 + Pt1)/2
Y: Pt imbalance A with RMS error bar:
A = 2*( Pt0 – Pt1 ) / (Pt0 + Pt1)
Profile Plot for Jet Pt imbalance
Event cut:
1. Each events contains only two jets.
2. Jet type: both are JCCB and
CoorJCCB.
3. Jet Pt cut for Jet Trigger efficient:
JT_25: 50Gev
JT_45: 70Gev
JT_65: 100Gev
JT_95: 150Gev
4. Jets || cut: || > 2.84.

4. Jet Pt resolution study
---- fit result
---- error applied results
Parameter correlation coefficients:
P P P2 P P P
[(Pt) / Pt]2 = [1/2 * (A)]2
Fitting function: [(Pt) / Pt]2 = P02 / X2 + P12 / X + P22

5. Mass resolution study
Use MC qcd samples with different Pt range:
Apply the same criteria of event selection and cut.
Do the Jet Pt smearing to MC qcd samples:
Jet Pt smeared as a normal distribution with RMS calculated by the obtained Jet Pt resolution curve
For each event, draw randomly to get the smeared Jets Pt. Then recaculate the invariance mass: M’
Get the (mass):
(M’ – M) / M.
(mass) distribution for different Pt range MC qcd samples.
Red curve: gaussian fits.

6. Mass resolution Curve
---- fit result
---- error applied results
Parameter correlation coefficients:
P P P2 P P P
Fitting function: [(M) / M]2 = P02 / X2 + P12 / X + P22