Strasbourg 2006

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Strasbourg 2006

• Low Mass Lepton Pairs Experiments
• Joachim Stroth, Univ. Frankfurt, GSI

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Motivation

• The dilepton signal contains contributions from
  throughout the collision, ..
• ... i.e. also direct radiation from the early
  phase.
• It probes the electromagnetic structure of
  dense/hot nuclear(or partonic) matter.

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Motivation (Chiral Symmetry Restoration)

• Substantial depletion of the condensates already
  in collisions at moderate beam energy.

2-quark condensate
4-quark condensate
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Experimental strategy

• AA collisions
• Radiation from the dense/hot phase
• Identify/subtract combinatorial background
• Identify/subtract contributions from late hadron
  decays
• p,p,g on A
• Modification of (w,f) spectral functions
• High resolution
• elementary reactions
• gain knowledge on production mechanisms

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VM modification in reactions on nuclei

• KEK
• proton induced reactions.
• r drops10 but no broadening

• TAPS/ELSA
• Photoproduction
• w is broadened (G 90 MeV) and dropping

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Overview
Alice
LHC
IT HPID
RHIC
SPS
CERES
TPC
SIS300
SIS 100AGS
upgrade
SIS18 Bevalac
time (technological advance)
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The HADES experiment _at_ GSI

• f symmetry
• hadron blind RICH
• 2 mass resolution (10 without outer tracking)

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CC 2AGeV ee- invariant mass spectrum
signal lt 140 MeV/c2 20971 counts signal gt 140
MeV/c2 1937 counts
100 M electron trigger e e- pairs measured
over 5 orders of magnitude
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HADES data

• Electron pair yield observed in acceptance
• Corrected for reconstruction efficiency
• PLUTO (thermal) event generator yields from TAPS
  measurement and using mt scaling.

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CC 2AGeV Comparison to transport
Conventional sources under control
Vacuum spectral functions Differences in the
description of D's and VM's
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CC 1AGeV HADES data (preliminary)

• Electron pair yield observed in acceptance
• Corrected for reconstruction efficiency
• Substantial yield above the h contribution

preliminary
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The DLS spectrometer _at_ LBL
HADES
DLS
mid-rapidity
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DLS and RQMD (Tübingen Group)
The puzzle remains
C. Fuchs et al.
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Comparison with the DLS results

• generated events processed by the full
• HADES analysis including
• detector (in)efficiency
• reconstruction (in)efficiency

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The CERES Spectrometer _at_ CERN
CERES

• f symmetry
• dE/dX in silicon drift for background rejection
• 3.8 mass resolution (TPC upgrade)

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CERES data
CERES
No substantial 'hole" between w and f pole mass
J. Stachel, ISHIP 2006 and nucl-ex/0511010
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The NA60 spectrometer _at_ CERN

• High resolution tracking by means of silicon
  (pixel) detectors. Mass resolution 2.3 (f)
• Challenge
• Track matching through absorber
• Match in configuration and momentum space

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NA60 acceptance
Gain in statistics over CERES gt 1000
S. Damjanovic, Hot Quarks 2006
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NA60 systematic uncertainties
S. Damjanovic, Hot Quarks 2006
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NA60 centrality dependence
Can this help to reduce uncertainties in the
fireball evolution (surface effects)
S. Damjanovic, Asilomar 2006
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NA60 pT Spectra
different mass bins
comparison to theory
S. Damjanovic, Asilomar 2006
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LMLP in PHENIX _at_ RHIC
S/B between 10-2 10-3
S/B will get much better once the HPID is
operational
A. Toja, Hot Quarks 2006
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From HADES to CBM _at_ FAIR
CBM 8 45 AGeV
HADES 2 8 AGeV
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Dielectron reconstruction in CBM

• Fast, high-precision tracking using silicon
  sensors.
• No electron identification before tracking

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Background rejection performance

• AuAu 25 AGeV, central collisions
• Signal mixed into UrQMD events

T. Galatyuk, CBM coll. meeting 2005
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The muon option in CBM
J/??µµ-
s/b 100
C/Fe absorbers detector layers

• Simulation AuAu 25 AGeV
• Excellent signal to background ratio in high mass
  region.
• Low efficiency for small invariant masses and/or
  low pT (enhancement region).
• Challenging muon detector (high particle
  densities)

?
?
f
A. Kiseleva, Y.Vassiliev
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Challenges for next generation experiments

• Improve characterization
• Double differential (e.g. inv. mass, pt)
• Centrality dependence
• Reduce uncertainties
• Statistical errors
• Fast detectors and DAQ
• Develop a trigger (not always easy, excellent
  detectors needed)
• Systematical errors
• Control combinatorial background (good background
  rejection)
• Fully understand efficiencies of detectors, track
  reconstruction, rejection cuts
• Good to know before design freeze-out
• What precision is really needed to distinguish
  between scenarios?
• Can one control uncertainties due to missing
  information about the fireball evolution?