This document provides a status update on the LD2 analysis for the E08-025 DVCS experiment. It summarizes that:
1) The selection of n-DVCS events from the data shows good agreement between two parallel analyses, with differences of around 1%.
2) A smearing simulation has been applied to better match the simulation to the data, involving different smearing for different calorimeter regions.
3) Observables are being extracted by fitting the smeared simulation to the data, allowing determination of the different angular dependences of the total cross section.
Principal Component Analysis for Tensor Analysis and EEG classification
DVCS_nov2014
1. Your Logo Here
E08-025 LD2 Analysis Status
DVCS Hall A Collaboration MeetingDVCS Hall A Collaboration Meeting
Camille Desnault
2. DVCS Collaboration Meeting 11/07/14 2/21
E08-025E08-025
LD2LD2
Analysis StatusAnalysis Status
Plan
Selection n-DVCS
Smearing simulation
Extraction observables
• By fitting the simulation to the data
• Matching the simulation to the data
• Target subtractions, Comparison with Malek
kin2High
kin2High
kin2High
kin2Low
3. DVCS Collaboration Meeting 11/07/14 3/21
E08-025E08-025
LD2LD2
Analysis StatusAnalysis Status
Selection n-DVCS Events (Comparison)
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We obtained a GOOD AGREEMENT between our two parallel
analysis
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Example with DVCS events from kin2LowLD2
→→ Mx2 after backgroundMx2 after background
subtractionsubtraction
Difference : 0.3 %
4. DVCS Collaboration Meeting 11/07/14 4/21
E08-025E08-025
LD2LD2
Analysis StatusAnalysis Status
Selection n-DVCS Events (Comparison)
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Differences due to calorimeter calibrations (ex. for raw data of kin2LowLH2)
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Differences due to correction of multicluster events :
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Kin2HighLD2 : cor1 = 2.5% >> (Malek: 2.0%)
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Kin2HighLH2 : cor2 = 1.5% >> (Malek: 1.2%)
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Kin2LowLD2 : cor3 = 4.5% >> (Malek: 3.9%)
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Kin2LowLH2 : cor4 = 2.3% >> (Malek: 2.0%)
With my
calibration
Difference : 1.3 %
With Malek's
calibration
Difference : 0.5 %
Corrections we apply
to the 1-cluster
events differ from :
~ 0.5 %
5. DVCS Collaboration Meeting 11/07/14 5/21
E08-025E08-025
LD2LD2
Analysis StatusAnalysis Status
Selection n-DVCS Events (kin2High)
My number of n-DVCS ≈ 53 000 evts
Malek's number of n-DVCS ≈
49 000 evts
Difference ~ 8 %
6. DVCS Collaboration Meeting 11/07/14 6/21
E08-025E08-025
LD2LD2
Analysis StatusAnalysis Status
Selection n-DVCS Events (kin2Low)
My number of n-DVCS ≈ 60 000 evts
Malek's number of n-DVCS ≈
55 000 evts
Difference ~ 10 %
7. DVCS Collaboration Meeting 11/07/14 7/21
E08-025E08-025
LD2LD2
Analysis StatusAnalysis Status
Smearing Simulation
●
We want the simulation to match the data
●
In order to fit the simulation to the data for the extraction of
the observables
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I look at the Mx2 variable of the proton data to perform the
smearing :
●
I apply different smearings for different calorimeter areas
(the smearing is not supposed to be uniform in the whole
calorimeter)
factGauss
is a factor
selected at random in following a
Gaussian distribution :
Gauss(mean,sigma)
8. DVCS Collaboration Meeting 11/07/14 8/21
E08-025E08-025
LD2LD2
Analysis StatusAnalysis Status
Smearing Simulation (Mx2 Spectra)
Smearing's results of the proton simulation data compared to the experimental proton data
(example of 4 regions of the calorimeter)
9. DVCS Collaboration Meeting 11/07/14 9/21
E08-025E08-025
LD2LD2
Analysis StatusAnalysis Status
Smearing Simulation (Calorimeter)
(Calorimeter's back side)(Calorimeter's back side)
Different combinations
(mean,sigma) for
different regions of the
calorimeter
4 (mean,sigma) values4 (mean,sigma) values
for the 4 regions givenfor the 4 regions given
previously in examplepreviously in example
10. DVCS Collaboration Meeting 11/07/14 10/21
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LD2LD2
Analysis StatusAnalysis Status
Smearing Simulation (Mx2 spectrum)
Smearing's results apply on the
neutron simulation data
compared to the experimental
neutron+deuteron data
Smearing's results apply on the
deuteron simulation data
compared to the experimental
neutron + deuteron data
11. DVCS Collaboration Meeting 11/07/14 11/21
E08-025E08-025
LD2LD2
Analysis StatusAnalysis Status
Extraction Observables
●
Fit of the simulation data to the experimental data
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Minimization of the X² :
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Reference of the 2002 B.M.K. parametrization of the total lepton's
scattering cross section on a nucleon target
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Use of an “effective” parametrization for the expression of the total
cross section :
●
Cint(F), ΔCint(F) and Cint(Feff) are the “effective” observables of
the cross section we find by fitting the simulation to the data
12. DVCS Collaboration Meeting 11/07/14 12/21
E08-025E08-025
LD2LD2
Analysis StatusAnalysis Status
Extraction Observables
(Number of Counts Nsimu)
Number of counts of the simulation “Nsimu” vsNumber of counts of the simulation “Nsimu” vs
the phi anglethe phi angle
→ Example of 1 bin in Mx2 represented twice
(once for the neutron contributions (top) and a second time
for the deuteron contributions (bottom) to the “Nsimu”.
Total number of counts “Nsimu” from the simulation
(neutron+deuteron)
Total number of experimental counts
(neutron+deuteron)
BH
Cint(F)
∆Cint(F)
Cint(Feff)
Tot : BH + Cint(F) + ∆Cint(F) + Cint(Feff)
Number of counts from the simulation :
for each contribution to the total
cross section,
for each particle (n, d)
NeutronNeutron
DeuteronDeuteron
13. DVCS Collaboration Meeting 11/07/14 13/21
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LD2LD2
Analysis StatusAnalysis Status
Extraction Observables
(Number of counts Nsimu)
→ 1 bin in t = -0.255 GeV², → Different bins in Mx2 (0.762,0.788,0.812,0.838,0.863) GeV²
X² = 1.68 X² = 1.02 X² = 0.91 X² = 1.26 X² = 0.69
14. DVCS Collaboration Meeting 11/07/14 14/21
E08-025E08-025
LD2LD2
Analysis StatusAnalysis Status
Extraction Observables
(Effective Cross Section)
Different angular dependences of the total cross section :
Total cross section:
Uncertainties
BH Cint(F) ∆Cint(F) Cint(Feff)
Tot : BH + Cint(F) + ∆Cint(F) + Cint(Feff)
17. DVCS Collaboration Meeting 11/07/14 17/21
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LD2LD2
Analysis StatusAnalysis Status
Conclusion / To do
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Conclusion :
●
After smearing of the simulation, we are able to fit the simulation to the data
in order to extract the observables
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We obtain good fits in the region of 1
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We can find the different angular dependences of the total cross section
for the neutron and the deuteron
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To do :
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Extraction of effective observables for the kin2Low kinematic
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Combined fit of the two kinematics (kin2high and kin2low) for extraction of
“B.M.K.” observables
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and more …
19. DVCS Collaboration Meeting 11/07/14 19/21
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LD2LD2
Analysis StatusAnalysis Status
Selection n-DVCS Events
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Why ?
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We want EXCLUSIVELY the DVCS events
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We want ONLY the n-DVCS among the DVCS events
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BUT : n-DVCS and d-DVCS are not SEPARABLE in Mx2
(due to the resolution of the detectors)
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How ?
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By REMOVING the background of the DVCS
(accidentals of the DVCS (1cluster), pi0, accidentals of the pi0 (2 clusters))
+ by CORRECTING the data from the multicluster events contributions
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By SUBTRACTING the LH2-data to the LD2-data using the Mx2 spectra
+ by APPLYING the Fermi motion to the LH2-data (initial motion of p in LD2)
+ by NORMALIZING the two targets-data
21. DVCS Collaboration Meeting 11/07/14 21/21
E08-025E08-025
LD2LD2
Analysis StatusAnalysis Status
Smearing Simulation
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Why ?
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To make the Mx2 spectrum of the simulation MATCH the Mx2 spectrum of the data
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To make the simulation more REALISTIC, in order to FIT its Mx2 to the data's one.
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How ?
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By SHIFTING the peak (MEAN) in Mx2 of the simulation
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By CHANGING the resolution (SIGMA) in Mx2 of the simulation
(too OPTIMISTIC compared to the experimental's one)
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By MULTIPLYING the final photon 4-vector (kp) by a random factor (RAND)
(RAND is randomly selected under a GAUSSIAN distribution: GAUS(MEANg,SIGMAg)GAUS(MEANg,SIGMAg) )
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By FINDING the optimal combinations of [MEANg,SIGMAg]
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By USING the LH2-data (with only p-DVCS data) and the p-simulation