Transcript
Page 1: D G/G from  high-p T  events in SMC

G/G from high-pT events in SMC

•Determination of ∆G/G from Photon Gluon Fusion•Analysis in Leading Order where it can be separated•based on simulations with LEPTO•Search for sample with high PGF contribution•application for DIS region, SMC data with Q2 >1GeV2

E.Rondio

for Spin Muon Collaboration (SMC)

Sołtan Institute for Nuclear Studies

Warsaw, Poland

Workshop on Hadron Structure and Spectroscopy, Paris, March 1st to 3rd 2004

Page 2: D G/G from  high-p T  events in SMC

History

• Idea proposed by R.D.Carlitz, J.C.Collins and A.H.Mueller, Phys.Lett.B 214, 229 (1988)

• Revisited by A.Bravar,D.von Harrach and A.Kotzinian, Phys.Lett.B 421, 349 (1998)

• Method used in HERMES for photoproductionHERMES, A.Airapetian et al., Phys.Rev.Lett.84, 2584 (2000)

• Here application for DIS region, SMC data with Q2 >1GeV2

SMC, B.Adeva et al.., submitted to Phys.Rev.D, hep-ex/0402010

Page 3: D G/G from  high-p T  events in SMC

QCDCQCDCLL

LPLPLL

PGFPGFLL

lhhXlN

RaRaq

q

RaG

ΔGA

G/G evaluation from measured asymmetry

where: AlNlhhX measured asymmetry,

q/q approximated by A1/D asymmetry N,

aLL partonic asymmetry,

R fraction of contributing processes

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Applicability and restrictionsSplitting between processes only in LO >>> when higher order effects expected to be important

it can not be used >>> here scale dependence was checked and found

small, so no clear signal of such strong dependenceUsing information which is not an observable (which type of interaction given event is) >>> so it has to be taken from simulation >>> the above makes analysis model dependent (using Lepto or eg. Pythia can give different results) but … a tool to check reliability is comparison of data with

MC Spin effects do not have to be simulated >>>measurement is independent of assumptions about

polarized parton distributions and spin effects in fragmentation

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Why events with high-pT hadrons ?

PGF

signal

LP QCDC

• Two high-pT hadrons more likely in QCDC and PGF because in LP source of pT only fragmentation in PGF and QCDC in addition pT from hard scattering

background

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Target: butanol, ammonia –

proton d-butanol - deuteron

Beam:

µ+ 190 GeV

Pµ= -0.78±0.03

Measured asymmetry:

lhhXlNTμ fAPP

NN

NN

where: beam, target

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Selected events cover following x, y, Q2

region

xBj xBj

yQ2

[GeV]

Conditions on hadrons in the final state

2 hadrons: pT> 0.7GeV, z>0.1, xF>0.1

(no electron contamination observed after these cuts)

Event selection for asymmetry

vertex in target half, beam through full target length, stable conditions

Kinematic cuts and regions: Q2>1GeV2, 0.4<y<0.9, acceptance for and h

Statistics after selections

proton deuteron

81 178 75 266

below 0.5% of the inclusive sample

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Monte Carlo studies

→ studies for DIS µp interactions at 190 GeV→ LEPTO simulations, Q2 1 GeV2

→ detector and reconstruction effects• geometrical acceptance for hadrons• simulations of trigger conditions• looses in reconstruction (chamber efficiencies)• smearing for scattered µ and hadrons (1/p, angles)• secondary interaction in target for hadrons

→conditions in MC generation scale for hard processes (syst.errors only)

cut-off’s in matrix element calculation parameters of symmetric fragmentation function

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Data and Monte Carlo agree at the level of 10-25%

To be used for selections of PGF and ∆G evaluation

Data and Monte Carlo comparison

Event kinematicsSensitive to trigger mixture, smearing

Hadron variablesSensitive to smearing and MC generation (ff)

Data

MC

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Simulation of exp. conditions

Sensitive to details of target:

position, angle

Good description after inclusion

of hadron secondary interactions

Modification of fragm. function

a=0.5, b=0.1 (stand.)

zbma Tezzzf /1 2

)1()(

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Contribution of PGF processFor SMC experimental

conditions Lepto at generation level RPGF = 8% events with two hadrons

(phad>5GeV) RPGF = 12% additionally pT

had > 0.7 GeV RPGF = 24%

How to get more? Two methods tried:• kinematical selections

(cuts) and • Neural Network

classification (NN)

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The criteria to judge the selection:

PGF(in)

PGF(out)Efficiency

PGF(out)QCDC(out)LP(out)

PGF(out)Purity

Several variables tried

Opposite charges of hadrons –

small effect, 1/3 events lost

Azimuthal angle between hadrons

– no improvement

Best - ∑p2T

Cuts on hadron variables

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Neural network

• input layer: event kinematics (x, y, Q2) and hadron variables (E1,2, pT1,2, charge, azimuthal angle between pT of two selected hadrons), • best way to use correlations• output layer: single unit number within range (0,1)

NN response Architecture: multi-layer feed-forward configuration

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Neural Network responsenumber within range <0,1.> events at high values of NN response are more likely to

be PGF

PGF enriched sample

selected by setting the threshold

on the NN response

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NN treshold

Processes

contributions

for two selection

method

PDG

QCDC

LO

PGF

LO

QCDC

Best result of cut

selection based

on pT2

compared to NN

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Asymmetry AlNlhhX

Systematic uncertainties:

•False asymmetries from acceptance variation

•Calculation of radiative effects (unpolarized and polarized part)

Effect due to restricted phace space

•Polarization of beam and target

•Target material

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Selection Proton AlNlhhX Q2

Deuteron AlNlhhX Q2

pT2 0.0180.0710.010 7.07 0.054

0.0930.008 7.91

NN 0.0300.0570.010 3.30 0.070 0.0770.010

4.00Interpretation of A lN→ lhhX in terms of ∆G/G requires

additional information from MC simulation.

AlNlhhX

pT0.7GeV pT22.5GeV2

NN0.26

Results on Asymmetry

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Input for calculation of ∆G/G

∆q/q approximated by A1·D

neglecting PGF contribution in inclusive

A1 measurements,

ok. only if RPDG(incl)<< RPDG(selected)

From other measurements:

A1 asymmetry taken from fit

to all experimental data

f(x)=xa·(1-ebx)+c ,

Q2 dependence neglected

proton

deuteron

Hermes

Hermes

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Input for calculation of ∆G/G From MC simulations:

• aLL calculated in POLDIS

aLLLP 0.8

aLLQCDC 0.6

aLLPGF -0.44

• fractions of processes Selection RLP RQCDC RPGF

pT22.5GeV2 26% 42% 32%

NN 0.26 38% 30% 32%

Important consistency between data and MC

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Statistical precision of ∆G/G

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Gluon polarization

Separately for proton and deuteron

∆G/G determined for a given fraction of nucleon momentum carried by gluons η

Selection G/G (G/G)stat genPGF

pT22.5GeV2 -0.07 0.40 0.09

NN 0.26 -0.20 0.29 0.07

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Average value final SMC result on

∆G/G =-0.200.290.11

SMCHermes

NNpT1

2+pT22

comparison

• Difference < 2 σ

• Different process DIS vs. Photoproduction

• Factor 2 difference

in ηgluon

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Systematic uncertainty on ∆G/G Contribution to the systematic

due to uncertainty on parameters used in MC :

• sensitivity to fragmentation, • cutoffs in matrix elements calculations• scale dependence (2Q2,Q2/2),

Changes in RPGF < 5%

Similar effect for

pT of faster hadron

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Error source uncertainty on ∆G/G

Precision of A1 fit 0.026Scale change Q2/2 ; 2Q2 0.010Fragmentation function 0.034Cutoffs in matrix elements

0.008

err. from MC and A1 0.053Syst.error from Alhh 0.062

Total 0.115

+20%R / -20%R 0.067 / 0.100

+4% aLL / -4% aLL 0.015 / 0.017

Systematic uncertainty on ∆G/G

Changing only R or aLL

Page 25: D G/G from  high-p T  events in SMC

Summary• The method of ∆G/G evaluation from asymmetry for

events with high-pT hadrons was applied to SMC data in DIS region

• Results obtained for cut selection and neural network ∆G/Gstat. sys. -0.07 ± 0.40 ± 0.11 cut ∑pT

2

∆G/Gstat. sys. -0.20 0.29 0.11 NNpoints to rather small value of gluon polarization

• precision of ∆G/G limited by the statistical error, • systematic error controlable (and can be reduced for

high statistics by precise data/MC comparison)

• Improvement on accuracy of ∆G/G in future: COMPASS at CERN, RHIC at BNL, E161 at SLAC


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