Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
• Beam test 2003Beam test 2003• Goal: charge discrimination algorithm with high efficiency and low Goal: charge discrimination algorithm with high efficiency and low
contaminationcontamination• Signal characterization for charges from Beryllium to NeonSignal characterization for charges from Beryllium to Neon• Probability PProbability PZZ that a cluster is generated by a particle of charge Z that a cluster is generated by a particle of charge Z• Implementation of a probability test for the estimation of the Implementation of a probability test for the estimation of the
charge associated to a track charge associated to a track • Status of the workStatus of the work
Beam Test Oct 2003: Beam Test Oct 2003: Ion Charge AnalysisIon Charge Analysis
Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
Beam test 2003Beam test 2003
Ions of average energy Ions of average energy »» 10 GeV/n 10 GeV/n extracted from an Indium beam of 158 GeV/n extracted from an Indium beam of 158 GeV/n on a Beryllium target, selected by A/Z ratio:on a Beryllium target, selected by A/Z ratio:- A/Z = 1.00, 6% of tot. ev., mainly - A/Z = 1.00, 6% of tot. ev., mainly protonsprotons- A/Z = 2.00, 77 % of tot. ev., - A/Z = 2.00, 77 % of tot. ev., HeHe component is dominant (Be is suppressed) component is dominant (Be is suppressed)- A/Z = 2.25, 16 % of tot. ev., - A/Z = 2.25, 16 % of tot. ev., 99BeBe component is dominant component is dominant - A/Z = 2.35, 1 % of tot. ev., - A/Z = 2.35, 1 % of tot. ev., 77LiLi component is dominant (He is suppressed) component is dominant (He is suppressed)
Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
Sample selectionSample selectionCalibrationCalibration ● pedped »» 2.5(3) for p(n)-side 2.5(3) for p(n)-side
Clusterizzation Clusterizzation ● Seed with Signal/Noise Seed with Signal/Noise (SN) > 5.(SN) > 5.● Neightboring strips with Neightboring strips with SN > 2.SN > 2.
Identification of an event of Z>2Identification of an event of Z>2● One and only one cluster One and only one cluster for each ladder/side (only 12 clusters)for each ladder/side (only 12 clusters)● Cluster charge amplitude > helium total charge Cluster charge amplitude > helium total charge ● A good probability for A good probability for 22 of the of the linear fitlinear fit between the 6 points of p(n) side between the 6 points of p(n) side
Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
Cluster amplitude: Cluster amplitude: total charge of a cluster, all strips (total charge of a cluster, all strips (ssii))Impact Point (IP): Impact Point (IP): obtained with a 5 point fit obtained with a 5 point fit
impact point VS cluster amplitude: impact point VS cluster amplitude: n-siden-side
NeNe
FFOO
NNCC
BBBeBe
SaturationSaturation
Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
Cluster amplitude: Cluster amplitude: total charge of a cluster, all strips (total charge of a cluster, all strips (ssii))Impact Point (IP): Impact Point (IP): obtained with a 5 point fit obtained with a 5 point fit
impact point VS cluster amplitude: impact point VS cluster amplitude: p-sidep-side
SuperpositionSuperposition
NeNe
FFOONNCCBBBeBe
The charge separation will be done with the n-side knowledge...The charge separation will be done with the n-side knowledge...
Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
n-side: n-side: distribution distribution
Three “Three “ regions” regions”● Readout regionReadout region: : ·· 0.15 or 0.15 or > 0.85 > 0.85● Interstrip regionInterstrip region: 0.15 < : 0.15 < ·· 0.35 or 0.65 < 0.35 or 0.65 < ·· 0.85 0.85 ● Not read strip regionNot read strip region: 0.35 < : 0.35 < ·· 0.65 0.65
RR RRNN104 104 mm 104 104 mm
: : charge center of gravity between the two higher strips charge center of gravity between the two higher strips
Charge samplesCharge samples● 3 different charge specta3 different charge specta● Charge peak selection on the sixth ladder Charge peak selection on the sixth ladder
Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
n-side: signal characterization n-side: signal characterization ● Sixth ladder amplitude selection in a restricted window around the energy loss peaks Sixth ladder amplitude selection in a restricted window around the energy loss peaks
(first ladder peak selection to study the sixth ladder)(first ladder peak selection to study the sixth ladder)● Study the charge distributions on the other laddersStudy the charge distributions on the other ladders● Signal characterization with a Signal characterization with a Landau Landau Gauss + exponential tail Gauss + exponential tail● Low efficiency and great purity samplesLow efficiency and great purity samples
7 parameters7 parameters● 1 for the position (1 for the position (MPVMPV))● 4 shape parameters (slope, 4 shape parameters (slope, ,...),...)● 2 normalizations2 normalizations
Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
n-side: purity of the samplesn-side: purity of the samples● fit the all charges spectrum of the sixth ladder: the only free parameters are the normalizations of the charge fit the all charges spectrum of the sixth ladder: the only free parameters are the normalizations of the charge
distributions distributions ● integration of the charge contributions around the peaksintegration of the charge contributions around the peaks
● sample puritysample purity : : »» 98% 98% with a Z – 1 contamination of with a Z – 1 contamination of »» 1% 1%
● low efficiencylow efficiency
B C NB C N
contamination of B contamination of B In the C sampleIn the C sample
Z – 1Z – 1
improve the efficiency using a likelihood based testimprove the efficiency using a likelihood based test
Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
n-side: shape parametersn-side: shape parameters● Shape parametersShape parameters
– : width of the Gaussian distribution: width of the Gaussian distribution– : width of the Landau distribution: width of the Landau distribution– : slope of the exponential function: slope of the exponential function– wwexpexp: weight of the exponential function (Area: weight of the exponential function (Areaexpexp/Area/Areatottot) )
● Given Z and Given Z and these parameters are these parameters are similarsimilar for the different ladders (the maximum for the different ladders (the maximum variation is of the order of variation is of the order of »»10%) 10%)
● MPV values differ from ladder to ladderMPV values differ from ladder to ladder
wwexpexp
Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
n-side: relative gainn-side: relative gain● Ladder to ladder differences are parametrized by a traslation coefficient:Ladder to ladder differences are parametrized by a traslation coefficient:
● The parameter GThe parameter Gll is independent from Z and is independent from Z and relative gainrelative gain● A unique charge parametrization can be used for all the laddersA unique charge parametrization can be used for all the ladders
GG22 »» 2% 2%
GGll function of Z for different ladders ( function of Z for different ladders ( fixed) fixed) GGll function of Z for different function of Z for different (ladder fixed) (ladder fixed)
Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
n-side: probability and likelihoodn-side: probability and likelihoodProbability distribution on the single ladderProbability distribution on the single ladder● The probabilityThe probability PPZZ that a cluster corresponds to a Z ion is defined as: that a cluster corresponds to a Z ion is defined as:
Some Oxygen in the Some Oxygen in the Fluorine sampleFluorine sample
Likelihood on n laddersLikelihood on n ladders
● we want 0 we want 0 ·· L L ·· 1, then: 1, then:– if L(Z) < 10if L(Z) < 10-50-50 L(Z) = 10 L(Z) = 10-50-50
– L(Z) = 1 + L(Z)/(50L(Z) = 1 + L(Z)/(50¢¢n)n)L(Z = 8)L(Z = 8)
Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
n-side: likelihood ratio test (6 ladders)n-side: likelihood ratio test (6 ladders)
InefficiencyInefficiency(Nitrogen impurity)(Nitrogen impurity) contaminationcontamination
contaminationcontamination(Oxygen impurity)(Oxygen impurity)
inefficiencyinefficiency
● which test for the charge estimation?which test for the charge estimation?– Maximum likelihoodMaximum likelihood: has the maximum efficiency : has the maximum efficiency – Recursive likelihood ratioRecursive likelihood ratio: a parametrized contamination : a parametrized contamination
Separation between Z and Z – 1 Separation between Z and Z – 1 Separation between Z and Z + 1 Separation between Z and Z + 1
Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
n-side: inefficiency and contamination (6 ladders)n-side: inefficiency and contamination (6 ladders)
● cc11 and c and c22 are nearly charge independent are nearly charge independent● for for cc11 = 0.53 e c = 0.53 e c22 = 0.40 = 0.40 efficiency efficiency »»98% and contamination 98% and contamination »»1%1%
● tests have been applied to clean samples (tests have been applied to clean samples (»» 98%) tuning c 98%) tuning c11 and c and c22● inefficiencyinefficiency: percentage of not recognized Z events: percentage of not recognized Z events● contaminationcontamination: percentage of not–Z events recognized as Z: percentage of not–Z events recognized as Z
Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
n-side: inefficiency and contamination (6 ladders)n-side: inefficiency and contamination (6 ladders)
● Inefficiency and contamination can be an Inefficiency and contamination can be an overestimatedoverestimated because the sample are not because the sample are not clean (there is clean (there is »»1% of Z – 1 events in each Z sample) 1% of Z – 1 events in each Z sample)
Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
n-side: charge with only one laddern-side: charge with only one ladderC
harg
e re
cons
truct
ed w
ith th
e
Cha
rge
reco
nstru
cted
with
the
six
thsi
xth
ladd
er la
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Charge reconstructed with the likelihood ratio of Charge reconstructed with the likelihood ratio of 5 ladder5 ladder
1010 0.000.0066
0.990.9933
99 0.010.0133
0.940.9455
0.040.0411
88 0.010.0144
0.950.9533
0.020.0299
0.000.0011
77 0.010.0111
0.950.9588
0.020.0277
0.000.0011
66 0.010.01 0.960.9611
0.020.0266
55 0.000.0099
0.960.9622
0.020.0266
0.000.0011
44 0.940.9455
0.040.0422
0.000.0033
ZZ 44 55 66 77 88 99 1010
● ““real charge” estimated with 5 ladders real charge” estimated with 5 ladders ● the charge on the last ladder is reconstructed with the maximum likelihood methodthe charge on the last ladder is reconstructed with the maximum likelihood method● the right charge is reconstructed at the right charge is reconstructed at »»95%95% while at while at »»3% is reconstructed as Z – 13% is reconstructed as Z – 1
iteration of the charge selection procedure ...iteration of the charge selection procedure ...
Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
p-side: problemsp-side: problems● superposition of the total charge profile function of I.P. for the different ions superposition of the total charge profile function of I.P. for the different ions ● not linear relation between amplitude and energy deposited [ not linear relation between amplitude and energy deposited [ B. Alpat et al., NIM A B. Alpat et al., NIM A
540 (2005) 121–130540 (2005) 121–130 ] ]● a deformed a deformed distribution (the spatial resolution has a strong systematic component) distribution (the spatial resolution has a strong systematic component)
NeNe
FFOONNCCBBBeBe
Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
p-side: problemsp-side: problems
p-sidep-side
● superposition of the total charge profile function of I.P. for the different ions superposition of the total charge profile function of I.P. for the different ions ● not linear relation between amplitude and energy deposited [ not linear relation between amplitude and energy deposited [ B. Alpat et al., NIM A B. Alpat et al., NIM A
540 (2005) 121–130540 (2005) 121–130 ] ]● a deformed a deformed distribution (the spatial resolution has a strong systematic component) distribution (the spatial resolution has a strong systematic component)
Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
p-side: problemsp-side: problems
HeliumHelium CarbonCarbon
MM RRRR
● superposition of the total charge profile function of I.P. for the different ions superposition of the total charge profile function of I.P. for the different ions ● not linear relation between amplitude and energy deposited [ not linear relation between amplitude and energy deposited [ B. Alpat et al., NIM A B. Alpat et al., NIM A
540 (2005) 121–130540 (2005) 121–130 ] ]● a deformed a deformed distribution (the spatial resolution has a strong systematic component) distribution (the spatial resolution has a strong systematic component)
Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
p-side: strip correctionp-side: strip correction
ProofProof● A n-cluster is associated to each p-clusterA n-cluster is associated to each p-cluster● On p-side only the seed strip is considered On p-side only the seed strip is considered ● Interstrip region: 0.45<Interstrip region: 0.45<pp<0.55<0.55● On n-side the cluster amplitude is On n-side the cluster amplitude is
consideredconsidered● Combine the information of all the ladder Combine the information of all the ladder
using the relative gainusing the relative gain
Proposed correctionProposed correction● a polynomial fit of the seed VS n-side amplitudea polynomial fit of the seed VS n-side amplitude● Linearization Linearization (hard, soft)(hard, soft)● Correction applied to all the p-cluster strips Correction applied to all the p-cluster strips (the same for all the ladders)(the same for all the ladders)
no correctionno correctionsoft correctionsoft correctionhard correctionhard correction
HypothesisHypothesis● The The deformation could arise from a not linear behaviour in the single strip signal deformation could arise from a not linear behaviour in the single strip signal
Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
p-side: p-side: distribution distribution
● moremore uniform uniform● Implantation structureImplantation structure
Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
p-side: spatial resolutionp-side: spatial resolution
● ladders allignement ladders allignement ● fit of a 5 point track fit of a 5 point track ● analisys of the analisys of the residual residual x distributionx distribution● evaluation of the spatial resolution (evaluation of the spatial resolution (»» x x - - fitfit))
residual
Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
p-side: charge characterizationp-side: charge characterization● Charge samples are obtained with the n-side likelihood testCharge samples are obtained with the n-side likelihood test● Clean separation in Clean separation in region is now possible also on p-side region is now possible also on p-side● The ladders differences can be parametrized with a single parameter The ladders differences can be parametrized with a single parameter
(relative gain)(relative gain)● A set of p.d.f. have been calculated for the different ions A set of p.d.f. have been calculated for the different ions ● Costruction of a p-side likelihood testCostruction of a p-side likelihood test
Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
p-side: test efficiencyp-side: test efficiency
99 0.000.0055
0.050.05 0.940.9433
88 0.090.0955
0.900.9033
0.000.0022
77 0.100.1099
0.880.8855
0.000.0022
0.000.0011
66 0.000.0022
0.020.0255
0.980.9844
0.000.0055
0.000.0011
55 0.010.0122
0.960.9611
0.020.0266
44 0.940.9499
0.050.05
ZZ 44 55 66 77 88 99
Charge reconstructed with 6 Charge reconstructed with 6 n-siden-side ladders ladders
Cha
rge
reco
nstru
cted
with
6
Cha
rge
reco
nstru
cted
with
6 p
-sid
ep-
side
ladd
ers
ladd
ers
● the p-side charge is reconstructed with the maximum likelihood methodthe p-side charge is reconstructed with the maximum likelihood method● the right charge is recognized in the right charge is recognized in »» 90 90% % of the eventsof the events
Alberto Oliva Alberto Oliva INFN/University of PerugiaINFN/University of Perugia
Tracker meetingTracker meeting24/10/200624/10/2006
Status of the workStatus of the work Implementation of a Implementation of a charge discrimination algorithm with high charge discrimination algorithm with high efficiency and low contamination. An AMS-note is in preparation:efficiency and low contamination. An AMS-note is in preparation:
Use the algorithm to find fragmentation events and to study their Use the algorithm to find fragmentation events and to study their topologytopology
Compare these result with a FLUKA Monte Carlo simulation Compare these result with a FLUKA Monte Carlo simulation