20110422 Defense Beta

Dijet Production in Polarized Proton-Proton Collisions at

200 GeVMatthew Walker

April 22, 2011

STAR

Matthew WalkerSTAR Thesis DefenseApril 22, 2011

Outline

✦ Theoretical Motivation

✦ Experimental Overview

✦ Cross Section Analysis

✦ Asymmetry Analysis

✦ Conclusions

2


Theoretical Motivation✦ Polarized DIS tells us that the

spin contribution from quark spin is only ~30%.

3

D. de Florian et al., Phys. Rev. D71, 094018 (2005). D. de Florian et al., Phys. Rev. Lett. 101 (2008) 072001

-0.04

-0.02

0

0.02

0.04

-0.04

-0.02

0

0.02

0.04

-0.04

-0.02

0

0.02

0.04

10 -2 10 -1

DSSVDNS KREDNS KKP

DSSV !"2=1DSSV !"2=2%

x!u–

x!d–

x!s–

x

GRSV maxgGRSV ming

x!g

x

-0.2

-0.1

0

0.1

0.2

0.3

10 -2 10 -1 1

Without RHIC data With RHIC data

Substantial improvement for

0.05 < x < 0.2, but large

uncertainties at low x

x 110-110-2

8

parabola and the 1! uncertainty in any observable would correspond to !"2 = 1. In order to account for unexpectedsources of uncertainty, in modern unpolarized global analysis it is customary to consider instead of !"2 = 1 betweena 2% and a 5% variation in "2 as conservative estimates of the range of uncertainty.

As expected in the ideal framework, the dependence of "2 on the first moments of u and d resemble a parabola(Figures 3a and 3b). The KKP curves are shifted upward almost six units relative to those from KRE, due to thedi"erence in "2 of their respective best fits. Although this means that the overall goodness of KKP fit is poorer thanKRE, #d and #u seem to be more tightly constrained. The estimates for #d computed with the respective best fitsare close and within the !"2 = 1 range, suggesting something close to the ideal situation. However for #u, they onlyoverlap allowing a variation in !"2 of the order of a 2%. This is a very good example of how the !"2 = 1 does notseem to apply due to an unaccounted source of uncertainty: the di"erences between the available sets of fragmentationfunctions.

-0.2

0

0.2

0.4

-0.2

0

0.2

0.4

-0.06

-0.04

-0.02

0

0.02

0.04

0.06

10-2

10-2

x(!u+!u–)

x(!d+!d–)

x!uv

x!dv

x!g–

x!u–

xBj

x!d–

xBj

x!s–

xBj

KRE (NLO)

KKP (NLO)unpolarizedKRE "

2KRE "

min+1

KRE "2

KRE "min

+2%

-0.06

-0.04

-0.02

0

0.02

0.04

0.06

10-2

FIG. 4: Parton densities at Q2 = 10 GeV2, and the uncertainty bands corresponding to !!2 = 1 and !!2 = 2%

An interesting thing to notice is that almost all the variation in "2 comes from the comparison to pSIDIS data.The partial "2 value computed only with inclusive data, "2

pDIS , is almost flat reflecting the fact the pDIS data are

not sensitive to u and d distributions. In Figure 3, we plot "2pDIS with an o"set of 206 units as a dashed-dotted line.

The situation however changes dramatically when considering #s or #g as shown in Figures 3c and 3f, respectively.In the case of the variation with respect to #s, the profile of "2 is not at all quadratic, and the distribution is muchmore tightly constrained (notice that the scale used for #s is almost four times smaller than the one used for lightsea quarks moments). The "2

pDIS corresponding to inclusive data is more or less indi"erent within an interval aroundthe best fit value and increases rapidly on the boundaries. This steep increase is related to a positivity constraints on!s and !g. pSIDIS data have a similar e"ect but also helps to define a minimum within the interval. The preferredvalues for #s obtained from both NLO fits are very close, and in the case of KRE fits, it is also very close to thoseobtained for #u and #d suggesting SU(3) symmetry.

8

parabola and the 1! uncertainty in any observable would correspond to !"2 = 1. In order to account for unexpectedsources of uncertainty, in modern unpolarized global analysis it is customary to consider instead of !"2 = 1 betweena 2% and a 5% variation in "2 as conservative estimates of the range of uncertainty.

As expected in the ideal framework, the dependence of "2 on the first moments of u and d resemble a parabola(Figures 3a and 3b). The KKP curves are shifted upward almost six units relative to those from KRE, due to thedi"erence in "2 of their respective best fits. Although this means that the overall goodness of KKP fit is poorer thanKRE, #d and #u seem to be more tightly constrained. The estimates for #d computed with the respective best fitsare close and within the !"2 = 1 range, suggesting something close to the ideal situation. However for #u, they onlyoverlap allowing a variation in !"2 of the order of a 2%. This is a very good example of how the !"2 = 1 does notseem to apply due to an unaccounted source of uncertainty: the di"erences between the available sets of fragmentationfunctions.

-0.2

0

0.2

0.4

-0.2

0

0.2

0.4

-0.06

-0.04

-0.02

0

0.02

0.04

0.06

10-2

10-2

x(!u+!u–)

x(!d+!d–)

x!uv

x!dv

x!g–

x!u–

xBj

x!d–

xBj

x!s–

xBj

KRE (NLO)

KKP (NLO)unpolarizedKRE "

2KRE "

min+1

KRE "2

KRE "min

+2%

-0.06

-0.04

-0.02

0

0.02

0.04

0.06

10-2

FIG. 4: Parton densities at Q2 = 10 GeV2, and the uncertainty bands corresponding to !!2 = 1 and !!2 = 2%

An interesting thing to notice is that almost all the variation in "2 comes from the comparison to pSIDIS data.The partial "2 value computed only with inclusive data, "2

pDIS , is almost flat reflecting the fact the pDIS data are

not sensitive to u and d distributions. In Figure 3, we plot "2pDIS with an o"set of 206 units as a dashed-dotted line.

The situation however changes dramatically when considering #s or #g as shown in Figures 3c and 3f, respectively.In the case of the variation with respect to #s, the profile of "2 is not at all quadratic, and the distribution is muchmore tightly constrained (notice that the scale used for #s is almost four times smaller than the one used for lightsea quarks moments). The "2

pDIS corresponding to inclusive data is more or less indi"erent within an interval aroundthe best fit value and increases rapidly on the boundaries. This steep increase is related to a positivity constraints on!s and !g. pSIDIS data have a similar e"ect but also helps to define a minimum within the interval. The preferredvalues for #s obtained from both NLO fits are very close, and in the case of KRE fits, it is also very close to thoseobtained for #u and #d suggesting SU(3) symmetry.

1

2=

1

2!"+ Lq +!G+ Lg

x


Theoretical Motivation✦ Extracting gluon polarization

4

-1

-0.75

-0.5

-0.25

0

0.25

0.5

0.75

1

-1 -0.8 -0.6 -0.4 -0.2 -0 0.2 0.4 0.6 0.8 1a L

Lcosθ*

gg ! gg

qg ! qg

qq ! qq qq̄ ! qq̄

gg ! qq̄

=!f1 ! !f2 ! !h · aLL ! Dh

f

f1 ! f2 ! !h ! Dhf

ALL =d!!

d!

long-range short-range long-range

!f1

!f2

!h

!G(Q2) =! 1

0!g(x,Q2)dxExtract ∆g(x,Q2) using a global fit

1

2=

1

2!"+ Lq +!G+ Lg


Inclusive jets

✦ Run 6 results: GRSV-max/GRSV-min ruled out, a gluon polarization between GRSV-std and GRSV-zero favored

✦ Run 9 results: good agreement with DSSV, GRSV-std and GRSV-zero excluded

5

D. de Florian et al. PRL 101 (2008) 072001.


Correlation Measurements✦ Reconstructing multiple physics

objects (di-jets, photon/jet) provides information about initial parton kinematics

✦ STAR well suited for correlation measurements with its large acceptance

6

M =!x1x2s

!3 + !4 = lnx1

x2

x1 =1!s(pT3e

!3 + pT4e!4)

x2 =1!s(pT3e

!!3 + pT4e!!4)

STAR Collaboration PRL 100 (2008) 232003


Experimental Setup

✦ RHIC produces polarized proton beams up to 250 GeV in energy

✦ Siberian snake magnets in the AGS and RHIC help protect beam from depolarizing resonances

7


STAR Detector

8

Not shown:Zero-degree calorimeters, time-of-flight, polarimeters

!=-1!=0

!=1

TPC

BEMC

YellowBlue

West

East

Tai Sakuma

BBC

Tai Sakuma, Thesis, MIT (2010)


Jet Terminology

9

Partons

Hadrons, Leptons

Tracks, Energy Depositions

Parton Branching, Hadronization, Underlying Event

Detector Effectspa

rton

part

icle

dete

ctor

Jet

π0

π+

g

q


Data✦ 2005 Data: 2.27 pb-1 taken during RHIC Run 5

✦ 2009 Data: 10.3 pb-1 taken during RHIC Run 9

10

✦ Jet Patch Trigger:

✦ 1x1 in φxη patch of towers in the BEMC (400 towers)

✦ Midpoint Cone Algorithm with Split-Merge

✦ Cone Radius: 0.4, 0.7

✦ Seed 0.5 GeVTai Sakuma, Thesis, MIT (2010)


Cross Section Formula

11

dσi/dMi = differential cross section in bin iΔMi = bin width in invariant mass of bin iL = LuminosityAvert = vertex acceptanceϵreco,vert = reconstruction + vertex efficiencyαij = matrix element for unfolding method (more later)ϵmisreco = efficiency for reconstructing dijets that have an associated particle dijetϵtrig = trigger efficiencyJj = reconstructed yield in bin j

d!i

dMi

=1

!Mi

1

L

1

Avert

1

"reco,verti

!

j

#ij"misrecoj

1

"trigj

Jtrigj,reco


2005 Data/Simulation Comparison

12

20 30 40 50 60 70 80 90 100 110

10

210

310

Data

Simulation

-0.2 0 0.2 0.4 0.6 0.8 1

10

210

310

0 0.05 0.1 0.15 0.2 0.25 0.3

310

20 30 40 50 60 70 80 90 100 1100.5

0.6

0.7

0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

-0.2 0 0.2 0.4 0.6 0.8 10.5

0.6

0.7

0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

0 0.05 0.1 0.15 0.2 0.25 0.30.5

0.6

0.7

0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

2005 STAR Preliminary

data

/si

mul

atio

nno

rmal

ized

yi

elds

M =!x1x2s !34 =

!3 + !42

=1

2ln

x1

x2cos !! = tanh

"3 ! "42

✦ Run 5 di-jet data shows good agreement with simulations

✦ Asymmetric pT cut applied to the jets for comparison with more stable NLO calculations


Unfolding

13

Used a matrix unfolding scheme based on G. D’Agostini, NIM A 362 (1995), p. 487.Purpose of unfolding - undo “smearing” caused by

Detector effects, eg:Double counting electronsHadronic responseLost tracksEnergy Leakage

Falling spectrum


Uncertainties

14

Statistical - besides data statistics, account for effects from MC finite statistics in correction factors and unfoldingSystematic -

Jet Energy Scale - more next slideBeam Background - < 0.5% from varied neutral energy cutNormalization

Luminosity - 8% from MB cross section uncertaintyAcceptance - 6% from difference in timebin distributions between MB and BJP2


Jet Energy Scale Uncertainty

15

Neutral Energy Uncertainty - 4.9 %BEMC Scale Uncertainty - 4.8 %BEMC Efficiency Uncertainty - 1 %

Charged Energy Uncertainty - 5.6 %Track Scale Uncertainty - 1%Track Finding Efficiency Uncertainty - 5%Hadron Response of the BEMC - 2.3 %



16

Data

High

Nominal

Low

High; High

High; Nominal

High; Low

Nominal; High

Nominal

Nominal; Low

Low; High

Low; Nominal

Low; Low

Yield

BEMC Min

BEMC Max

Reconstruction TriggerCorrections

UnfoldingOther Efficiencies

High; High

High; Nominal

High; Low

Nominal; High

Nominal

Nominal; Low

Low; High

Low; Nominal

Low; Low

Matthew WalkerSTAR Thesis DefenseApril 22, 2011 17

2005 Dijet Cross Section

Invariant Mass (GeV)20 30 40 50 60 70 80 90 100 110

)2 (p

b/G

eV/c

dMσd

-110

1

10

210

310

410

510


)2 (p

b/G

eV/c

dMσd

-110

1

10

210

310

410

510

2005 STAR Data with Statistical Uncertainties

Systematic Uncertainties

NLO Calculation (de Florian, et al.)

NLO with Hadronization and UE Corrections

STAR Run 5 Data

= 200 GeVs Jet + Jet + X at →p+p = 0.4coneR

| < 0.5ηΔ < 0.8, |η0.2 < | > 2.0φΔ|

10% Normalization Uncertainty (not shown)

)2Invariant Mass (GeV/c20 30 40 50 60 70 80 90 100 110

(dat

a-th

eory

)/the

ory

-1

-0.5

0

0.5


(dat

a-th

eory

)/the

ory

-1

-0.5

0

0.5 = 2M, M/2µScale Uncertainty on NLO,


Cone Radius Dependence

18

Tai Sakuma, Thesis, MIT 2010

M (GeV/c2)

Comparison of data with theory for different cone

radii shows clear dependence


2006 Cross Section

19

Mjj [GeV]

d3!/dMd!

3d!4

[pb/

GeV

]

1

10

102

103

104

105

30 40 50 60 70 80 90

Systematic Uncertainty

TheoryNLO pQCD + CTEQ6M

Had. and UE. Corrections

STAR Run-6

Dijet Cross Sectionpp @ 200 GeVCone Radius = 0.7max(pT) > 10 GeV, min(pT) > 7 GeV-0.8 < ! < 0.8, |!!| < 1.0|!!| > 2.0

!!Ldt = 5.39pb!1

d3!

dMd!3d!4

✦ Unpolarized differential cross section between 24 and 100 (GeV/c2)

✦ NLO theory predictions using CTEQ6M provided by de Florian with and without corrections for hadronization and underlying event from PYTHIA

✦ Statistical Uncertainties as lines, systematics as rectangles

STAR Preliminary



2006 Cross Section

✦ Comparison to theory (including hadronization and underlying event correction) shows good agreement within systematic uncertainties

✦ Agreement confirms our use of pQCD to extract gluon polarizations

20

Mjj [GeV]

(Dat

a - T

heor

y) /

Theo

ry-1.0

-0.5

0.0

0.5

1.0

30 40 50 60 70 80 90

Systematic UncertaintyTheoretical Uncertainty

STAR Run-6

Theory: CTEQ6M NLO pQCD Had. UE. Corrections

Data-theory Comparisonof Dijet Cross Sectionpp @ 200 GeVCone Radius = 0.7max(pT) > 10 GeV, min(pT) > 7 GeV-0.8 < ! < 0.8, |!!| < 1.0, |!!| > 2.0

!!Ldt = 5.39 pb!1 STAR Preliminary



Asymmetry Measurment

✦ Asymmetry formula:

✦ N++: like sign dijet yields

✦ N+-: unlike sign dijet yields

✦ R: relative luminosity

✦ P: polarization

21

ALL =1

PBPY

N++ !RN+!

N++ +RN+!

✦ 2009 Data: 10.3 pb-1

analyzed from Run 9

✦ Significant increase in data size over previous years and small increase in polarization


2009 Asymmetry

✦ The value of ALL in a bin j is given by the above formula

✦ αjk are the matrix elements for the unfolding

✦ Changing the jet energy scale results in different unfolding matrices

✦ Formula above represents unpolarized unfolding, could also introduce a second unfolding matrix for polarized unfolding

22

!k !jk(

!i PB,iPY,i(N

++i,k +N!!

i,k )! PB,iPY,iRi(N+!i,k +N!+

i,k ))!

k !jk(!

i P2B,iP

2Y,i(N

++i,k +N!!

i,k )! P 2B,iP

2Y,iRi(N

+!i,k +N!+

i,k ))


2009 Simulation

✦ New simulation needed:

✦ Different detector components installed in 2009 than in previous simulations

✦ Different trigger algorithms used

✦ Simulation geometry bugs fixed

✦ Previous simulation effectively integrated 5.3 x 10-4 pb-1

✦ Goal for new simulation: 1 pb-1

✦ Solution: use cloud computing resources

23


Cloud Computing Projects

24

date Facility toolstype of task

# of VMs

# jobs/VM

CPU days

calendar days

input (TB)

output (TB)

remarks

2009, March Amazon EC2Nimbus Globus PBS batch

simu 100 1 500 5 0 0.3works like normal globus GK grid site

2009, November Amazon EC2 EC2 simu 10 1 or 2 1 1 0 0.01use commercial interface

2010, FebruaryGLOW Madison Uni Wisconsin

CondorVM simu 430 1 130 0.6 0 0.1 call home model

2010, JulyClemson Uni, SC

Kestrel, QEMU-KVM

simu 1000 1 17,000 20 0 7 VM lifetime 24 h, no ssh to VM

2011, FebruaryMagellan NERSC

Eucalyptus data reco 20 6 or 7 600+ 20+ 2 1 almost real-time

processing

Clemson

STARAmazonEC2

GLOW

NERSC


2009 Simulation

✦ Prepare a VM Image✦ Start with a KVM image of Scientific Linux 5.3✦ Add ~50 additional required packages✦ Install STAR libraries, ~2.5M lines of code✦ Setup grid toolkit and credentials✦ Install database server✦ Setup scripts to interact with job manager

✦ Setup monitoring scheme✦ Design HTTP based API for jobs to record messages in a

database✦ Write monitoring software

25


2009 Simulation

26


2009 Simulation

27

✦ 9 STAR MC productions with partonic pT > 2 GeV (lower than before)

✦ PYTHIA 6.4.23, proPt0 (latest and greatest in PYTHIA and tuning)

✦ Over 12 billion events generated by PYTHIA, filtered to allow only 36 million to undergo detector simulation (GEANT3), and 10 million through full reconstruction

DateJul17 Jul24 Jul31

N M

achi

nes

0

200

400

600

800

1000

1200

1400

Available Machines

Working Machines

Idle Machines

✦ Took over 400,000 CPU hours and generated 7 TB of files transferred to BNL

✦ Expansion of 25% of STAR computing resources

✦ Would have taken over one year without cloud resources

✦ Largest physics simulation on cloud, largest STAR simulation (CPU hours, output size)


Data/Simulation Run 9

✦ Run 9 data simulation agreement is good

28

20 30 40 50 60 70 80 90 100

Norm

aliz

ed Y

ield

s

310

410

510

610 Data Simulation

-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1

410

510

0 0.1 0.2 0.3 0.4 0.5 0.6

510

)2Invariant Mass (GeV/c20 30 40 50 60 70 80 90 100

(Dat

a-Si

mu)

/Sim

ulat

ion

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

34η

-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

*)θcos(0 0.1 0.2 0.3 0.4 0.5 0.6-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

STAR Run 9 Data Preliminary Jet + Jet + X→p+p

= 200 GeVs

= 0.7coneR < 0.8η-0.8 <

| < 1.0ηΔ || > 2.0φΔ|

STAR Preliminary


Uncertainties

✦ Statistical - Uncertainties from all sources of statistical combined using a Monte Carlo that samples the distributions: data, simulation, polarization, relative luminosity

✦ Systematic

✦ Jet energy scale: change unfolding matrices

✦ Non-longitudinal effects: 0.025 x ALL

✦ Relative Luminosity: δR = 1x10-3

✦ Theory Scenario dependent trigger efficiencies

29


False Asymmetries

30

)2Invariant Mass (GeV/c20 30 40 50 60 70 80

-0.1

-0.05

0

0.05

0.1

LLRaw ALLRaw A


-0.1

-0.05

0

0.05

0.1

YellowAYellowA


-0.1

-0.05

0

0.05

0.1

BlueABlueA


-0.1

-0.05

0

0.05

0.1

Like-signALike-signA


-0.1

-0.05

0

0.05

0.1

Unlike-signAUnlike-signA

Consistent with zero



31

Neutral Energy Uncertainty - 2.1 %BEMC Scale Uncertainty - 1.9 %BEMC Efficiency Uncertainty - 1 %

Charged Energy Uncertainty - 5.4 %Track Scale Uncertainty - 2%Track Finding Efficiency Uncertainty - 5%


Scenario Dependent Efficiencies

32


LL,u

npol

- A

LL,p

olA

-0.02

-0.01

0

0.01

0.02

0.03

0.04

DSSV

GRSV STD

GRSV Zero


Run 9 Asymmetry

33

]2M [GeV/c20 30 40 50 60 70 80

LLA

-0.02

0

0.02

0.04

0.06

0.08

East - East and West - West Barrel

MC GS-C(pdf set NLO)

2009 STAR Data


]2M [GeV/c20 30 40 50 60 70 80

LLA

-0.02

0

0.02

0.04

0.06

0.08

East Barrel - West Barrel

Scale uncertaintyGRSV stdDSSV

]2M [GeV/c20 30 40 50 60 70 80

LLA

-0.02

0

0.02

0.04

0.06

0.08

Full Acceptance

p+ p ! jet + jet +X

!s = 200 GeV

PreliminarySTAR

East West East West

η=0η=0 η=1η=-1 η=1η=-1

Matthew WalkerSTAR Thesis DefenseApril 22, 2011 34

Kinematic Sensitivity

-210 -110 1-210

-110

1

10

210

310

410

510

-210 -110 1-210

-110

1

10

210

310

410

510


x

-110

1


x

-110

1

East Barrel - East Barrel East Barrel - West Barrel

1x

2x

: 20.0 < M < 30.01x

: 20.0 < M < 30.02x

: 70.0 < M < 80.01x

: 70.0 < M < 80.02x

PreliminarySTAR

p+ p ! jet + jet +X

!s = 200 GeV

X X

XX


Summary✦ 2006 Dijet cross section (5.39 pb-1) shows good agreement with

NLO calculations, validating pQCD as an analysis framework

✦ 2009 asymmetry strongly favors DSSV over GRSV std and GS-C; separation into different acceptances allows for first constraints on the shape of Δg(x)

35

]2M [GeV/c20 30 40 50 60 70 80

LLA

-0.02

0

0.02

0.04

0.06

0.08

East - East and West - West Barrel

MC GS-C(pdf set NLO)

2009 STAR Data


]2M [GeV/c20 30 40 50 60 70 80

LLA

-0.02

0

0.02

0.04

0.06

0.08

East Barrel - West Barrel


]2M [GeV/c20 30 40 50 60 70 80

LLA

-0.02

0

0.02

0.04

0.06

0.08

Full Acceptance

p+ p ! jet + jet +X

!s = 200 GeV

PreliminarySTAR


Backup

36

7 October 2009 Collaboration Meeting

UNFOLDING

Consider the true bin with 49 < M < 64The spectrum at right represents the contributions to this true bin from each of the reconstructed mass binsThe red bin is the contribution from the same bin in reconstructed massThe contributions from blue bins is ~50%

37

)2Reconstructed Invariant Mass (GeV/c20 30 40 50 60 70 80 90 100 110

Un

fold

ed

Yie

ld

0

20

40

60

80

100

120

140

160

< 64.15particle

Contributions to corrected bin 48.83 < M < 64.15particle

Contributions to corrected bin 48.83 < M

There are important off diagonal components that must be considered


UNFOLDING

38


Un

fold

ed

Yie

ld

0

200

400

600

800

1000

1200

< 24.25particle




Un

fold

ed

Yie

ld

0

200

400

600

800

1000

1200

1400

1600

< 30.01particle




Un

fold

ed

Yie

ld

0

200

400

600

800

1000

1200

< 37.90particle




Un

fold

ed

Yie

ld

0

100

200

300

400

500

600

< 48.83particle




Un

fold

ed

Yie

ld

0

20

40

60

80

100

120

140

160

< 64.15particle




Un

fold

ed

Yie

ld

0

2

4

6

8

10

12

14

16

18

< 85.92particle




Un

fold

ed

Yie

ld

0

0.1

0.2

0.3

0.4

0.5

0.6

< 117.29particle



Here are the same plots for all of the binsThe last bin has contributions from ONLY other bins


UNFOLDINGMethod used based on G. D’Agostini, NIM A 362 (1995), p. 487.Also used by (along with H1, ZEUS, HARP, and others):

IceCube: arXiv:0811.1671L3: arXiv: hep-ex/0507042D0: arXiv: hep-ex/9807029

Use PYTHIA to populate the unfolding matrix A (in the naming convention of D’Agostini) using the reconstructed invariant mass and the particle invariant massNormalize so that A does not change the integral of the spectrumThe following equation describes the matrix elements of A:

39

!ij =J(reconstructed bin j|particle bin i)

J(reconstructed bin j)


2005/2006 Comparison

40


)2 (p

b/G

eV/c

4ηd 3ηdM

dσd

-110

1

10

210

310

410

510

2005 STAR Data with Statistical UncertaintiesSystematic UncertaintiesTai Run 5 BHT2 DataTai Run 6 BHT2 DataTai Run 5 BJP2 DataTai Run 6 BJP1 Data


(Dat

a-M

att)/

Mat

t

-0.50

0.51

1.52

2.53


2006 Asymmetry

✦ Run 6 Longitudinal double helicity asymmetry

✦ Systematic uncertainties show effects on trigger efficiency from different theory scenarios

✦ Scale uncertainty (8.3%) from polarization uncertainty not shown

41

Mjj [GeV]

ALL

-0.02

0.00

0.02

0.04

0.06

0.08

30 40 50 60 70 80

Dijet ALLpp @ 200 GeVCone Radius = 0.7max(pT) > 10 GeVmin(pT) > 7 GeV-0.8 < ! < 0.8, |!!| < 1.0|!!| > 2.0

Data Run-6

Sys. Uncertainty

GRSV STDDSSV

GRSV !g = 0GRSV !g = !g !!Ldt = 5.39pb!1

STAR Preliminary


2009 Projections

42

East West East West

Wed Sep 22 15:18:55 2010 ]2M [GeV/c20 30 40 50 60 70 80

LLA

-0.02

-0.01

0

0.01

0.02

0.03

0.04

0.05

0.06

east barrel - east barrel and west barrel - west barrel

MCGRSV stdGRSV m03GRSV zeroGS-C(pdf set NLO)2009 STAR Data

]2M [GeV/c20 30 40 50 60 70 80

LLA

-0.02

-0.01

0

0.01

0.02

0.03

0.04

0.05

0.06east barrel - west barrel


Projected PrecisionSTAR


Data/Simulation Run 6

43

✦ 2006 Simulation:

✦ 11 STAR MC productions producing 4M events with partonic pT between 3 GeV and 65 GeV

✦ PYTHIA 6.410, CDF Tune A

✦ Run 6 data and simulation agreement is good



Dijet Run 9 Projected

44

20110422 Defense Beta

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