Information about the 2008 BSMD Calibration effort will be posted below as sub-pages.
Fig 1. BSMD-E 2D mapping of soft ID. (plot for reverse mapping is attached)
To obtain muDst w/o zero suppression I run privately the following production chain:
chain="DbV20080703 B2008a ITTF IAna ppOpt VFPPV l3onl emcDY2 fpd ftpc trgd ZDCvtx NosvtIT NossdIT analysis Corr4 OSpaceZ2 OGridLeak3D beamLine BEmcDebug"
Examples of single strip pedestal residua, based on ~80K minB events from days 47-65, 30 runs. (1223 is # of bins, ignore it).
Left is typical good spectrum, see Fig2.3. Middle is also reasonable, but peds is 8 channels wide vs. typical 4 channels.
The strip shown on the right plot is probably broken.
Detailed view on first 500 strips. X=stripID for all plots.
Broader view of ... problems in BSMD-E plane. Note, status flag was taken in to account.
Top plot is sum of 30 runs from days 47-65, 80K events. Bottom plot is just 1 run, 3K events. You can't distinguish individual channels, but scatter plot works like a sum of channels, so it is clear the slopes are there, we need just more data.
Input: 1M dAu minb events from runs: 8335112+8336019
Method : fit slopes to individual strips, as discussed 01) raw spectra
Examples of raw pedestal corrected spectra for first 9 strips, 1M dAu events
Detailed view on first 500 strips. X=stripID for all plots.
BSMDE strips cover the whole barrel and eta-phi representation is better suited to present 18K strips in one plot.
For reference spectra from 1M pp events from ~12 EmcCheck runs from days 47-51. It proves I did it and it was naive on my side to expect 1M pp events is enough.
More pp events spectra - lot of problems with DB content.
This page provides more details addressing some of Will's questions.
2) fig 2: well, 500 chns is not a very "natural" unit, but I wonder
what corresponds to 50 chns (e.g., the region of fluctuation
250-300) ... I need to check my electronics readout diagrams
again, or maybe folks more expert will comment
Zoom-in of the god-to-bad region of BSMDE
'Good' strips belong to barrel module 2, crate 2, sitting at ~1 o'cloCk on the WEST
'BAD' strips belong also to barrel module 2, crate 2, sitting at ~1 o'cloCk on the WEST
Study of pedestal correlation for BSMDE
Goal: identify source of the band below main pedestals.
Figs 1,2 show pedestals 'breathe' in correlated way for channels in the same crate, but this mode is decoupled between crates. It may be enough to use individual peds for all CAPS to reduce this correlation.
Fig3 shows CAP=123 has bi-modal pedestals. FYI, CAPS 124,125 were excluded because they also are different.
Based on Fig1 & 3 one could write an algo identifying event by event in which mode CAP=123 settled, but for now I'll discard CAP123 as well.
All plots are made based on 500K d-Au events from the run 8336052.
Fig 0
Example of pedestal residua for BSMDE strips 1-500, after CAPS 124 and 125 were excluded.
Fig 1
Correlation between pedestal residua for neighbor strips. Strip 100 is used on all plots on the X-axis
Fig 2
Correlation between pedestal residua for strips in different crates. Strip 100 is used on all plots on the X-axis
Fig 3
Squared pedestal residua for strips [1,150] were summed for every event and plotted as function of CAP ID (Y-axis).
Those strips belong to the same module #1 . X-axis shoes SQRT(sum) for convenience. CAP=123 has double pedestal.
Input: 500K d-Au events from run 8336052,
Method : drop CAPS 123,124,125, subtract single ped for all other CAPS.
Fig 1 full resolution, only 6 modules , every module contains 150 strips.
Fig 2 All 18K strips (120 modules), every module contain only 6 bins, every bin is sum of 25 strips.
h->RebinX(25), h->SetMinimum(2), h->SetMaximum(1e5)
INPUT: 3M d-AU events from day ~336 of 2007.
Method: fit slopes to ADC =ped+30,ped+100.
The spectra, fits of pedestal residuum, and slopes were QAed.
Results: slopes were found for 16,577 of 18,000 strips of BSMDE.
Fig1 Good spectrum for strip ID=1. X-axis ADC-ped, CAPs=123,124,124 excluded.
Fig2 TOP: slopes distribution (Y-axis) vs. stripID within given module ( X-axis). Physical eta=0.0 is at X=0, eta=1.0 is at X=150.
BOTTOM: status tables with marked eta-phi location excluded 1423 strips of BSMDE by multi-stage QA of the spectra. Different colors denote various failed tests.
Fig3 Mapping of known BSMDE topology on chosen by us eta-phi 2D localization. Official stripID is shown in color.
Content
The automatic procedure doing QA of spectra was set up in order to preserve only good looking spectra as shown in the fig 0 below.
Fig 0 Good spectra for random strips in module=2. X-axis shows pedestal residua. It is shown to set a scale for the bad strips shown below.
INPUT: 3M d-AU events from day ~336 of 2007.
All spectra were pedestals subtracted, using one value per strip, CAPS=123,124,125 were excluded. Below I'll use term 'ped' instead of more accurate pedestal residuum.
Method: fit slopes to ADC =ped+40,ped+90 or 5*sig(ped) if too low.
The spectra, fits of pedestal residuum, and slopes were QAed.
QA method was set up as sequential series of cuts, upon failure later cuts were not checked.
Note, BSMD rate 4 had old resistors in day 366 of 2007 and was excluded from this analysis.
This reduces # of strips from 18,000 to 15,750 .
cut# | cut code | description | # of discarded strips | figure |
1 | 1 | at least 10,000 entries in the MPV bin | 4 | - |
2 | 2 | MPV position within +/-5 ADC channels | 57 | Fig 1 |
3 | 4 | sig(ped) of gauss fit in [1.6,8] ADC ch | 335 | Fig 2 |
4 | 8 | position of mean gauss within +/- 4 ADC | 11 | Fig 3 |
5 | 16 | yield from [ped+40,ped+90] out of range | 441 | Fig 4 |
6 | 32 | chi2/dof from slop fit in [0.6,2.5] | 62 | Fig 5 |
7 | 64 | slopeError/slop >16% | 4 | Fig 6 |
8 | 128 | slop within [-0.015, -0.05] | 23 | Fig 7 |
- | sum | out of processed 15,750 strips discarded | 937 ==> 5.9% |
Fig 1 Example of strips failing QA cut #2, MPV position out of range , random strip selection
Fig 2a Distribution of width of pedestal vs. eta-bin
Fig 2b Example of strips failing QA cut #3, width of pedestal out of range , random strip selection
Fig 3a Distribution of pedestal position vs. eta-bin
Fig 3b Example of strips failing QA cut #4, pedestal position out of range , random strip selection
Fig 4a Distribution of yield from the slope fit range vs. eta-bin
Fig 4b Example of strips failing QA cut #5, yield from the slope fit range out of range , random strip selection
Fig 5a Distribution of chi2/DOF from the slope fit vs. eta-bin
Fig 5b Example of strips failing QA cut #6, chi2/DOF from the slope fit out of range , random strip selection
Fig 6a Distribution of err/slope vs. eta-bin
Fig 6b Example of strips failing QA cut #7, err/slope out of range , random strip selection
Fig 7a Distribution of slope vs. eta-bin
Fig 7b Example of strips failing QA cut #8, slope out of range , random strip selection
Fig 8a Distribution of # of bad strips per module.
BSMDE modules 10,31,68 are damaged above 50%+. Ymax was set to 150, i.e. to the # of eat strips per module. Modules 16-30 served by crate 4 were not QAed.
Fig 8b 2D Distribution of # of bad strips indexed by eta & phi strip location. Z-scale denotes error code from the 2nd column from table 1.
Fig 9 2D Distribution of slope indexed by eta & phi strip location.
TOP: slopes. There is room for gain improvement in the offline analysis. At fixed eta (vertical line) there should be no color variation.
BOTTOM error of slope/slope.
Fig 10 2D Distribution of pedestal and pedestal width indexed by eta & phi strip location.
TOP: pedestal
BOTTOM: pedestal width.
Method : find average slope per eta slice, fit gauss, determine average slope : avrSlope(iEta)
Gain correction formula is used only for extreme deviations:
Fig 1 Example of 2 eta slices
Fig 2 TOP: Slope distribution vs. eta-bin, average marked by crosses
BOTTOM: predicted gain correction. Correction=1 for strips w/ undetermined gains.
Fig 3 Predicted gain correction. Correction=1 for ~14K of 18K strips.
Fig 4 The same predicted gain correction vs. stripID.
Content
The automatic procedure doing QA of spectra was set up in order to preserve only good looking spectra as shown in the fig 0 below.
Fig 0 Good spectra for random strips in module=2. X-axis shows pedestal residua. It is shown to set a scale for the bad strips shown below.
INPUT: 3M d-AU events from day ~336 of 2007.
All spectra were pedestals subtracted, using one value per strip, CAPS=123,124,125 were excluded. Below I'll use term 'ped' instead of more accurate pedestal residuum.
Method: fit slopes to ADC =ped+40,ped+90 or 5*sig(ped) if too low.
The spectra, fits of pedestal residuum, and slopes were QAed.
QA method was set up as sequential series of cuts, upon failure later cuts were not checked.
Note, BSMD rate 4 had old resistors in day 366 of 2007 and was excluded from this analysis.
This reduces # of strips from 18,000 to 15,750 .
cut# | cut code | description | # of discarded strips | figure |
1 | 1 | at least 10,000 entries in the MPV bin | 2 | - |
2 | 2 | MPV position within +/-5 ADC channels | 10 | Fig 1 |
3 | 4 | sig(ped) of gauss fit in [0.75,8] ADC ch | 32 | Fig 2 |
4 | 8 | position of mean gauss within +/- 4 ADC | 0 | Fig 3 |
5 | 16 | yield from [ped+40,ped+90] out of range | 758 | Fig 4 |
6 | 32 | chi2/dof from slop fit in [0.55,2.5] | 23 | Fig 5 |
7 | 64 | slopeError/slop >10% | 1 | Fig 6 |
8 | 128 | slop within [-0.025, -0.055] | 6 | Fig 7 |
- | sum | out of processed 15,750 strips discarded | 831 ==> 5.2% |
Fig 1 Example of strips failing QA cut #2, MPV position out of range , random strip selection
Fig 2a Distribution of width of pedestal vs. strip # inside the module. For the East side I cout strips as -1,-2, ...,-150.
Fig 2b Example of strips failing QA cut #3, width of pedestal out of range , random strip selection
Fig 3 Distribution of pedestal position vs. strip # inside the module
Fig 4a Distribution of yield from the slope fit range vs. eta-bin
Fig 4b Example of strips failing QA cut #5, yield from the slope fit range out of range , random strip selection
Fig 5a Distribution of chi2/DOF from the slope fit vs. eta-bin
Fig 5b Example of strips failing QA cut #6, chi2/DOF from the slope fit out of range , random strip selection
Fig 6 Distribution of err/slope vs. eta-bin
Fig 7a Distribution of slope vs. eta-bin
Fig 7b Example of strips failing QA cut #8, slope out of range , random strip selection
Fig 8a Distribution of # of bad strips per module.
BSMD-P modules 1,4,59,75,85 are damaged above 50%+. Ymax was set to 150, i.e. to the # of eat strips per module. Modules 16-30 served by crate 4 were not QAed.
Fig 8b 2D Distribution of # of bad strips indexed by eta & phi strip location. Z-scale denotes error code from the 2nd column from table 1.
Fig 9 2D Distribution of slope indexed by eta & phi strip location.
TOP: slopes. At fixed eta (horizontal line) there should be no color variation. red=dead strips
BOTTOM error of slope/slope. white=dead strip
Fig 10 2D Distribution of pedestal and pedestal width indexed by eta & phi strip location.
TOP: pedestal. dead strip have 0 residuum.
BOTTOM: pedestal width. white marks dead strips
Method : find average slope per eta slice, fit gauss, determine average slope : avrSlope(iEta)
Gain correction formula is used only for extreme deviations:
Fig 1 Example of 2 eta slices
Fig 2 LEFT: Slope distribution vs. eta-bin, average marked by crosses
RIGHT: predicted gain correction. Correction=1 for strips w/ undetermined gains.
Fig 3 Predicted gain correction. Correction=1 for ~14K of 18K strips.
Fig 4 The same predicted gain correction vs. stripID.
Fig 1. West BSMD-P
Fig 2. East BSMD-P
p>
The second pass through both SMDE, SMDP was performed, learning from previous mistakes.
Main changes:
INPUT: 3M d-AU events from day ~336 of 2007.
All spectra were pedestals subtracted, using one value per strip, CAPS=123,124,125 were excluded. Below I'll use term 'ped' instead of more accurate pedestal residuum.
Method: fit slopes to ADC =ped+30,ped+100 or 5*sig(ped) if too low.
The spectra, fits of pedestal residuum, and slopes were QAed.
Note, BSMD rate 4 had old resistors in day 366 of 2007 and was excluded from this analysis.
This reduces # of strips from 18,000 to 15,750 .
cut# | cut code | description | # of discarded E strips | # of discarded P strips | figure in PDF1 |
1 | 1 | at least 10,000 entries in the MPV bin | 4 | ? | - |
2 | 2 | sig(ped) of gauss fit <~13 ADC ch | 13 | 11 | Fig 1 |
3 | 4 | position of mean gauss within +/- 4 ADC | 10 | 8 | Fig 2 |
4 | 8 | yield from [ped+30,ped+100] out of range | 513 | 766 | Fig 3 |
5 | 16 | chi2/dof<2.3 from slop fit | 6 | 1 | Fig 4 |
6 | 32 | slopeError/slop >10% | 5 | 0 | Fig 5 |
7 | 64 | slope in range | 19 | 6 | Fig 6 |
- | sum | out of processed 15,750 strips discarded | 635 ==> 4.0% | 789 ==> 5.0% |
Relative gain corrections for every eta bin
Method : find average slope per eta slice, fit gauss, determine average slope : avrSlope(iEta)
Gain correction formula is used only for extreme deviations:
Summary of BSMDE,P status tales and gains , ver 1.2
Method:
from _private_ production w/o zero BSMD suppression we look at pedestal residua for raw spectra for minb events.
chain="DbV20080703 B2008a ITTF IAna ppOpt VFPPV l3onl emcDY2 fpd ftpc trgd ZDCvtx NosvtIT NossdIT analysis Corr4 OSpaceZ2 OGridLeak3D beamLine BEmcDebug"
The only QA was to require MPV of the spectrum is below 100, one run contains ~80K events.
Good spectra look like this:
TOP: MPV value from all strips. White means 0 (zero) counts. Crate 4 was not evaluated.
BOTTOM: status table: red=bad, white means MPV>100 events
TOP: MPV value from all strips. White means 0 (zero) counts
BOTTOM: status table: red=bad, white means MPV>100 events
TOP: MPV value from all strips. White means 0 (zero) counts
BOTTOM: status table: red=bad, white means MPV>100 events
Peds from run minB 17 were used as reference
Fig1 . pedestal residua for runs 17,29,31
Fig2 . pedestal residua for run 31, full P-plane
Fig3 . pedestal residua for run 31, full E-plane
Fig4 . pedestal residua for run 31, zoom in E-plane
Fig5 . pedestal residua for run 29, West, E-plane red, P-plane black, error=ped error
On August 8, BSMD peds in the offline DB where corrected for day 47.
Runs minb 34 & 74 were used to determine and upload DB peds.
Below I evaluated pedestal residua for 2 runs : 37 & 70, both belonging to the same RHIC fill.
I have used 500 zero-bias events from runs 37 & 70, for the official production w/o zero suppression.
All strips for which mTables->getStatus(iEP, id, statPed,"pedestal"); returns !=1 and all events using CAP123,124,125 were dropped.
Fig 1,2 show big picture: all 38,000 strips.
Fig 3 is zoom in on some small & big problems.
Fig 4 & 5 illustrates improvement if run-by-run pedestal is used.
Fig 1, run=9047037
Fig 2, run=9047070
Fig 3, run=9047070, zoom in
Fig 4, run=9047001,...,83 zoom in
Fig 5, run=9047001,...,83 full range
I calculated the pedestals for every PP fill for 2008. This plot shows the pedestal per stripID and fill index. The Z-axis is the value of the pedestal. Only module 13 is shown here, but the full 2D histogram (and others) are in the attached root files.
Method: identify isolated EM shower and match BSMD cluster energy to tower energy, as exercised earlier on 4) demonstration of absolute calib algo on single particle M-C
INPUT events: 7,574 events triggered by barrel HT0,1,2 (id 220500 or 220510 or 220520) from run 9047029.
Cluster finder algo (sliding window, 1+3+1 strips), smd cluster threshold set at 5 keV, use only barrel West.
Tower cluster is defined as 3x3 patch centered on the tower pointed by the SMD peak.
Assumed BSMD calibration:
Results for ~3,8K barrel triggered events (half of 7,6K was not used)
TOP: a) Cluster (Geant) energy;
b) Cluster RMS, peak at 0.5 is from low energy pair of isolated strips with almost equal energy
c) # of cluster per event,
BOTTOM: X-axis is eta location, 20 bins span eta [-1,+1]. d) cluster ene vs. eta, e) cluster RMS vs. eta,
f) cluster yield vs. eta & phi, white bands are masked modules.
see Fig 1 for details
TOP: a) cluster loss on subsequent cuts, b) # of accepted EM cluster vs. eta location,
c) ADC distribution of 3x3 tower cluster centered at SMD cluster. In principle you should see there 3 edges from bht0, bht1, and bht2 trigger.
BOTTOM: X-axis is eta location, 20 bins span eta [-1,+1].d) Eta-cluster , e) phi-cluster energy, f) hit tower ADC .
2 eta location of 0.1, 0.5 of reco EM cluster are shown in 3 panels (2x2)
1D plots are ratios of the respective 2D plots.
The mean values of 1D fits are relative gains of BSMDP/BSMDP and BSMD/BTOW .
Goal: reco isolated gammas from bht0,1,2 -triggered events
Method: identify isolated EM shower and match BSMD cluster energy to tower energy, as exercised earlier on 4) demonstration of absolute calib algo on single particle M-C
INPUT events: 100K events triggered by barrel HT0,1,2 (id 220500 or 220510 or 220520) from day 47, runs 1..83
Cluster finder algo (sliding window, 1+4+1 strips), smd cluster threshold set at 10 keV, use only barrel West, BSMD CR=4 masked out.
Tower cluster is defined as 3x3 patch centered on the tower pointed by the SMD peak, must contain 90% of energy from 5x5 cluster.
Default pedestals from offline DB used.
Assumed BSMD calibration: see table 1 column J+K
Results for ~25K barrel triggered events (7/8 of 100K was not used)
Fig 1 is above
Fig 2, Eta strips, any cluster
Fig 3 Phi strips, any cluster
Fig 4 isolated cluster (different sort). Plot c has huge peak at 0 - X-axis is chopped. Similar but smaller peak is in fig d. Magenta are event with bht0 and bht2 trigger.
Fig 5 isolated cluster :
Left: eta & phi plane coincidence--> works,
Right: eta & phi & tower 3x3>150 fials for modules 30-60, I have mapping problem??
Fig 6 Example of Eta vs. Phi and SMD vs. Tower calibrations for eta bins 0.15, 0.5, and 0.85.
Executive summary:
The purpose of BSMD absolute calibration summarized at this drupal page is to reconstruct integrated energy deposit (dE) in BSMD based on measured ADC.
By integrated dE in BSMD I mean sum over few strips forming EM cluster, no matter what is the cluster shape.
This calibration method accounts for the varying absorber in front of BSMD and between eta & phi planes.
This calibration will NOT help in reconstruction:
- full energy of EM particle which gets absorbed in BEMC ( shower development after BSMD layer does not matter for this calibration).
- partial energy of hadrons passing or showering in BEMC
- correct for the incident angle of the particle passing through detector
- saturation of BSMD readout. I only state up to which loss (DE) the formula used in reconstruction:
dE/GeV= (rawAdc-ped) * C0 * (1 +/- C1etaBin)
- determine sampling fraction (SF) of BSMD with high accuracy
Below you will find brief description of the algo, side by side comparison of selected plots for M-C and real data, finally PDF with many more plots.
Proposed absolute calibration coefficients are show in table 2.
Input events
Raw data processing based on muDst
Cluster finder algo (seed is sliding fixed window), tuned on M-C gamma events
This cluster finder process full Barrel West, more details about clustering is in one cluster topology , definition of 'barrel cell'
Isolated EM shower has been selected as follows, tuned on gamma events,
Below is listing of all cuts used by this algo:
useDbPed=1; // 0= use my private peds par_skipSpecCAP=1; // 0 means use all BSMD caps par_strWinLen=4; (3) // length of integration window, total 1+4+1, in strips par_strEneThr=1.e-6; (0.5e-6) // GeV, energy threshold for strip to start cluster search par_cluEneThr=10.0e-6; (2.0e-6) // GeV, energy threshold for cluster in window par_kSigPed=4.; (3) // ADC threshold par_isoRms=0.2; (0.11) // minimal smd 1D cluster RMS par_isoMinT3x3adc=150; //cut off for low tower response par_isoTowerEneR=0.9; // ratio of 3x3/5x4 cluster (in red are adjusted values for MIP or ET=1GeV cluster selection)
3x3 tower ET (GeV), trigger used | MIP, BHT0,1,2 | 1.0, BHT0,1,2 |
3.4, BHT0 |
4.7, BHT1 |
5.5, BHT2 |
7, BHT2 |
3x3 tower ADC sum range | 15-30 ADC | 50-75 ADC | 170-250 ADC | 250-300 ADC | 300-380 ADC | 400-500 ADC |
3x3 energy & RMS (GeV) @ eta=[0.1,0.2] | 0.34 +/- 0.06 | 0.92 +/- 0.11 | 3.1 +/- 0.3 | 4.1 +/- 0.2 | 5.1 +/- 0.3 | 6.6 +/- 0.4 |
3x3 energy & RMS (GeV) @ eta=[0.4,0.5] | 0.37 +/- 0.07 | 1.0 +/- 0.11 | 3.4 +/- 0.4 | 4.6 +/- 0.3 | 5.6 +/- 0.4 | 7.3 +/- 0.5 |
3x3 energy & RMS (GeV) @ eta=[0.8,0.9] | 0.47 +/- 0.09 | 1.3 +/- 0.16 | 4.3 +/- 0.4 | 5.7 +/- 0.3 | 7.1 +/- 0.5 | 9.3 +/- 0.6 |
Contains relative calibration of eta vs. phi plane, different for M-C vs. data,
and single absolute DATA normalization of the ratio of SMD (Eta+Phi) cluster energy vs. 3x3 tower cluster at eta=0.5 .
Table 3 shows what comes from data & M-C analysis using calibration from table 2.
Fig 2.1 BSMD "Any cluster" properties
TOP : RMS vs. energy, only Eta-plane shown, Phi-plane looks similar
BOTTOM: eta -phi distribution of found clusters. Left is M-C - only 3 modules were 'populated'. Right is data, white bands are masked modules or whole BSMD crate 4
Fig 2.2 Crucial cuts after coincidence & isolation was required for a pair BSMD Eta & Phi clusters
TOP : 3x3 tower energy (black), hit-tower energy (green) , if 3x3 energy below 150 ADC cluster is discarded
BOTTOM: eta dependence of 3x3 cluster energy. M-C has 'funny' calibration - there is no reason for U-shape, Y-value at eta=0.5 is correct by construction.
Fig 2.3 None-essential cuts, left by inertia
TOP : ratio of 3x3 tower energy to 5x5 tower energy , rejected if below 0.9
BOTTOM: RMS of Eta & Phi cluster must be above 0.2, to exclude single strip clusters
I'm showing examples for 3 eta slices of 0.15, 0.55, 0.85 - plots for all eta bins are available as PDF, posted in Table 2 at the end.
The red vertical line marks the target calibration, first 2 columns are aligned by definition, 3rd column is independent measurement confirming calibration for data holds for ~40% lower gamma energy.
Fig 3.1 Phi-cluster vs. Eta cluster for eta range [0.1,0.2]. M-C on the left, data in the middle, right.
Fig 3.2 Phi-cluster vs. Eta cluster for eta range [0.4,0.5]. M-C on the left, data in the middle, right.
Fig 3.3 Phi-cluster vs. Eta cluster for eta range [0.8,0.9]. M-C on the left, data in the middle, right.
Fig 3.4 Phi-cluster vs. Eta cluster for eta range [0.9,1.0]. M-C on the left, data in remaining columns.
I'm showing eta slices [0.4,0.5] used to set absolute scale. The red vertical line marks the target calibration, first 2 columns are aligned by definition, 3rd column is independent measurement for gammas with ~40% lower --> BSMD response is NOT proportional to gamma energy.
Fig 4.1 Phi-cluster vs. Eta cluster for eta range [0.4,0.5]. Only data are shown.
Fig 4.2 Absolute BSMD calibration for eta range [0.0,0.1] (top) and eta range [0.1,0.2] (bottom) . Only data are shown.
Left: Y-axis is BSMD(E+P) cluster energy, y-error is error of the mean; X-axis 3x3 tower cluster energy, x-error is RMS of distribution . Fit (magenta thick) is using only to 4 middle points - I trust them more. The MIP point is too high due to necessary SMD cluster threshold, the 7GeV point has very low stat. There is no artificial point at 0,0. Dashed line is extrapolation of the fit.
Right: only slope param (P1) from the left is used to compute full BSMD Phi & Eta-plane calibration using formulas:
slope P1_Eta=P1/2./(1-C1[xCell])/C0
slope P1_Phi=P1/2./(1+C1[xCell])/C0
Using C1[xCell],C0 from table 2.
Fig 4.3 Absolute BSMD calibration for eta range [0.2,0.3] (top) and eta range [0.3,0.4] (bottom) . Only data are shown, description as above.
Fig 4.4 Absolute BSMD calibration for eta range [0.4,0.5] (top) and eta range [0.5,0.6] (bottom) . Only data are shown, description as above.
Fig 4.5 Absolute BSMD calibration for eta range [0.6,0.7] (top) and eta range [0.7,0.8] (bottom) . Only data are shown, description as above.
Fig 4.6 Absolute BSMD calibration for eta range [0.8,0.9] (top) and eta range [0.9,0.95] (bottom) . Only data are shown, description as above.
I'm showing the last eta bin because it is completely different - I do not understand it at all. It was different on all plots above - just reporting here.
Fig 4.7 Expected BSMD gain dependence on HV, from Oleg document The 2008 working HV=1430 V (same for eta & phi planes) - in the middle of the measured gain curve.
Part 5
Fig 5.1 BSMD cluster energy vs. eta of the cluster.
Fig 5.2 hit tower to 3x3 cluster energy for accepted clusters. DATA, trigger BHT2, gamma ET~5.5 GeV.
Fig 5.3 hit tower to 3x3 cluster energy for accepted clusters. M-C, single gamma ET=6 GeV, flat in eta .
The isolated BSMD cluster algo allows to select different range of tower energy cluster as shown in Fig.1
Fig 1. Tower energy spectrum, marked range [1.2,1.8] GeV.
In the analysis 5 energy tower slices were selected: MIP, 1.5 GeV, and around BHT0,1,2 thresholds.
Plots below show example of calibrated BSMD (eta+phi) cluster energy vs. tower cluster energy. (I added point at zero with error as for next point to constrain the fit)
Fig 2. BSMD vs. tower energy for eta of 0.15, 0.55, and 0.85.
I'm concern we are beyond the middle of BSMD dynamic range for ~6 GeV (energy) gammas at eta 0.5. Also one may argue we se already saturation.
If we want BSMD to work up to 40 GeV ET we need to think a lot how to accomplish that.
Below is dump of one event contributing to the last dot on the middle plot. It always help me to think if I see real raw event.
BSMDE i=526, smdE-id=6085 rawADC=87.0 ped=71.4 adc=15.6 ene/keV=0.9 i=527, smdE-id=6086 rawADC=427.0 ped=65.0 adc=362.0 ene/keV=20.0 i=528, smdE-id=6087 rawADC=814.0 ped=71.8 adc=742.2 ene/keV=41.0 i=529, smdE-id=6088 rawADC=92.0 ped=66.4 adc=25.6 ene/keV=1.4 BSMDP i=422, smdP-id=6086 rawADC=204.0 ped=99.3 adc=104.7 ene/keV=7.8 i=423, smdP-id=6096 rawADC=375.0 ped=98.5 adc=276.5 ene/keV=20.3 i=424, smdP-id=6106 rawADC=692.0 ped=100.1 adc=591.9 ene/keV=47.3 2D cluster bsmdE CL meanId=6086 rms=0.80 ene/keV=66.80 inTw 1632.or.1612 bsmdP CL meanId=6106 rms=0.68 ene/keV=75.45 inTw 1631.or.1632 BTOW id=1631 rawADC=43.0 ene=0.2 ped=30.0, adc=13.0 id=1632 rawADC=401.0 ene=6.9 ped=32.4 adc=368.6 id=1633 rawADC=43.0 ene=0.1 ped=35.5 adc=7.5 gotTwId=1632 gotTwAdc=368.6 tow3x3 sum=405.7 ADC 3x3Tene=7.3GeV