first measurement of the spectral function in high-energy nuclear collisions
DESCRIPTION
First measurement of the spectral function in high-energy nuclear collisions. Sanja Damjanovic on behalf of the NA60 Collaboration. Quark Matter 2005 August 4 – 9, Budapest, Hungary. Outline. Event sample Data analysis event selection combinatorial background fake matches - PowerPoint PPT PresentationTRANSCRIPT
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S. Damjanovic, QM2005, 4-9 August, Budapest 1
First measurement of the spectral function in high-energy nuclear collisions
Sanja Damjanovic on behalf of the NA60 Collaboration
Quark Matter 2005August 4–9, Budapest, Hungary
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S. Damjanovic, QM2005, 4-9 August, Budapest 2
Outline
Event sample
Data analysis event selection combinatorial background fake matches
Understanding the peripheral data
Isolation of an excess in the more central data
Comparison of the excess to model predictions
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2.5 T dipole magnet
hadron absorber
• Origin of muons can be accurately determined• Improved dimuon mass resolution
Matching in coordinate
and momentum space
targets
beam tracker
vertex trackermuon trigger and tracking
magnetic field
or!
Measuring dimuons in NA60: concept
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5-week long run in Oct.–Nov. 2003
Indium beam of 158 GeV/nucleon ~ 4 × 1012 ions delivered in total ~ 230 million dimuon triggers on tape
present analysis: ~1/2 of total data
Event sample: Indium-Indium
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Data Analysis
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Selection of primary vertex
Beam Trackersensors
windows
The interaction vertex is identified with better than 20 m accuracy in the transverse plane and 200 m along the beam axis.
(note the log scale)
Present analysis (very conservative):
Select events with only one vertex in the target region,
i.e. eliminate all events with secondary interactions
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A certain fraction of muons is matched to closest non-muon tracks (fakes). Only events with 2 < 3 are selected.
Fake matches are subtracted by a mixed-events technique (CB) and an overlay MC method (only for signal pairs, see below)
Muon track matching Matching between the muons in the Muon Spectrometer (MS) and the tracks in the Vertex Telescope (VT) is done using the weighted distance (2) in slopes and inverse momenta. For each candidate a global fit through the MS and VT is performed, to improve kinematics.
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Determination of Combinatorial Background
Basic method:
Event mixing
takes account of charge asymmetry correlations between the two muons, induced by magnetic field sextant subdivision trigger conditions
talk by Ruben
Shahoyan, 5b
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Combinatorial Background from ,K→ decays
Agreement of data and mixed CB over several orders of magnitude Accuracy of agreement ~1%
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Fake Matches Fake matches of the combinatorial background are automatically subtracted as part of the mixed-events technique for the combinatorial background
Fake matches of the signal pairs (<10% of CB) can be obtained in two different ways:
Overlay MC (used for LMR): Superimpose MC signal dimuons onto real events. Reconstruct and flag fake matches. Choose MC input such as to reproduce the data. Start with hadron decay cocktail + continuum; improve by iteration.
Event mixing (used for IMR): More complicated, but vital for offset analysis
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Example of overlay MC: the
Fake-match contribution localized in mass (and pT) space
= 23 MeV fake = 110 MeV
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Subtraction of combinatorial background and fake matches
For the first time, and peaks clearly visible in dilepton channel
Net data sample: 360 000 events
Mass resolution:23 MeV at the position
μμ channel also seen
Fakes / CB < 10 %
Real data !
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Track multiplicity from VT tracks for triggered dimuons, shown separately for opposite-sign pairs, combinatorial background and signal pairs after subtraction of total background (including fakes).
Four multiplicity windows used in the further analysis:
Centrality bin multiplicity ⟨dNch/dη⟩3.8
Peripheral 4–28 17
Semi-Peripheral
28–92 63
Semi-Central 92–160 133
Central > 160 193
Associated track multiplicity distribution
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Signal and background in 4 multiplicity windows
S/B
2 1/3
1/8 1/11
Decrease of S/B with centrality, as expected
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Phase space coverage in mass-pT plane Final data after subtraction of combinatorial background and fake matches
The acceptance of NA60 extends (in contrast to NA38/50) all the way down to small mass and small pT
MC
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Results
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Understanding the Peripheral dataFit hadron decay cocktail and DD to the data
5 free parameters to be fit:
DD, overall normalization
(0.12fixed)
Fit range: up to 1.4 GeV
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Comparison of hadron decay cocktail to data
all pT
Very good fit quality
log
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The region (small M, small pT)
is remarkably well described
Comparison of hadron decay cocktail to data
→ the (lower) acceptance of NA60
in this region is well under control
pT < 0.5 GeV
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Particle ratios from the cocktail fits
and nearly independent of pT; 10% variation due to the
increase of at low pT (due to ππ annihilation, see later)General conclusion:
peripheral bin very well described in terms of known sources low M and low pT acceptance of NA60 under control
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Isolation of an excess in the more central data
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Understanding the cocktailfor the more central data
Need to fix the contributions from the hadron decay cocktail Cocktail parameters from peripheral data? How to fit in the presence of an unknown source?
Nearly understood from high pT data, but not yet used
Goal of the present analysis: Find excess above cocktail (if it exists) without fits
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Conservative approach
Use particle yields so as to set a lower limit to a possible excess
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● data-- sum of cocktail sources
including the
Cocktail definition: see next slide
all pT
Comparison of data to “conservative” cocktail
Clear excess of data above cocktail, rising with centrality
fixed to 1.2
But: how to recognize the spectral shape of the excess?
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Isolate possible excess by subtractingcocktail (without ) from the data
set upper limit, defined by “saturating” the measured yield in the mass region close to 0.2 GeV
leads to a lower limit for the excess at very low mass
and : fix yields such as to get, after subtraction, a smooth underlying continuum
difference spectrum robust to mistakes even at the 10% level;consequences highly localized
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Excess spectra from difference: data - cocktail
all pT
Clear excess above the cocktail , centered at the nominal pole and rising with centrality
Similar behaviour in the other pT bins
No cocktail and no DD subtracted
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Systematics
Level of underlying continuum more sensitive
Illustration of sensitivity to correct subtraction of combinatorial background and fake matches; to variation of the yield
Structure in region completely robust
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Enhancement relative to cocktail use mass range 0.2–0.9 GeV to normalize to
Total data,no DD subtracted
faster than linear rise with centrality, steeper for low pT
Errors are systematic, statistical errors are negligible
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Comparison of excess to model predictions
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Predictions for In-In by Rapp et al (2003) for ⟨dNch/d⟩ = 140, covering all scenarios
Theoretical yields, folded with acceptance of NA60 and normalized to data in mass interval < 0.9 GeV
Only broadening of (RW) observed, no mass shift (BR)
Comparison of data to RW, BR and Vacuum
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Comparison of data to RW, BR and Vacuum
pT dependence same conclusions
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Understanding the spectral shape Dilepton rate Example:
thermal radiation based on white spectral function
propagate this through NA60 acceptance:no structure ! recover white spectrum !
By pure chance, for all pT and the slope of the pT spectra of the direct radiation, the NA60 acceptance compensates for the phase space factors and “extracts” the<spectral function>
integrate over space-time and momenta
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Comparison of data to RW, BR and Vacuum
Data and model predictions as shown (propagated through the NA60 detector) roughly represent the respective spectral functions, averaged over space-time and momenta.
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Conclusions
• pion annihilation is a major contribution to the lepton pair excess in heavy-ion collisions
• no mass shift of the intermediate contrary to Brown / Rho scaling
• broadening of the intermediate , consistent with Rapp / Wambach