Transcript Document

Muon EF Data Quality
M. Primavera - I.N.F.N. Lecce
on behalf of
Muon EF working group
Atlas Data Quality Workshop
CERN, April 23- 25, 2007
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 Preliminary considerations and first ideas on how to
perform Muon EF DQM/DQA presented in Zeuthen in
TDAQ Data Quality Workshop:
 Online
 Offline: using physics signal,
comparing trigger/reconstruction
 For the moment efforts are focused on Online DQM/DQA
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 Since the Zeuthen Wshop until now:
 Monitoring experience collected during last technical run (March
19-23 )
 First approaches with DQMF
 Studies performed in offline with Data/SW validation tools of the
muon slice
to produce a preliminary list of histograms/parameters to be
monitored for DQ + checks to be performed on them
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Atlas Data Quality Workshop
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LVL1
LVL2 (muFast)
LVL2 ID
LVL2 (muComb)
Muon EF
Seeding Algs
Moore Algs
Hypo Alg
TrigMoore MuIdStandAlone
Algs
Hypo Alg
MuIdCombined
Algs
Offline ID
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Hypo Alg
Atlas Data Quality Workshop
FEX algorithms:
Moore Algs (rec. MS)
MuIdStandalone Algs (muon extrap.
to the inter. Region)
MuIdCombined Algs (track comb.
with ID)
( Trigger/TrigAlgorithms/TrigMoore
+”Moore”+”MuId”)
HYPO algorithms:
MooreHypo
MuIdStandaloneHypo
MuIdCombinedHypo
(Trigger/TrigHypothesis/TrigMuonHyp
o/TrigMooreHypo)
Cut variables: pt
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Existing Monitoring:
TrigMooreHisto
Monitored: muons in MS rec. by FEX Moore
( Trigger/TrigAlgorithms/TrigMoore)
Variables monitored:
 # of muon candidates
 pt,1/pt,a0,phi,cottheta,(x,y,z)
 eta,phi of LVL2 muon ROI
Histogramming based on THistSvc
Other histograms now added in private version: e.g.
# hit/track per tecnology,etc…
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However, we are now starting to migrate to the common framework for
HLT monitoring
(https://twiki.cern.ch/twiki/bin/view/Atlas/TriggerValidationHistograms)
in the next days with a “pilot “version of muon EF monitoring
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Muon EF Monitoring in March Technical run (D. Scannicchio)
SW release: Used 12.0.5-HLT with some patches
Sample: ~6000 events: mixed physics processes LVL1 pre-selected with
low thres. (di-jets,Ws,Zs,etc.)
Trigger menus: MU06 for LVL1, mu6 signature in HLT, EF finds track
in MS
e.g. muon_slice_run2346-withSFO.root/Gathered-PTs/EXPERT/TrigMoore
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A new ATLOG entry has been submitted:
Author
: Diana and Alina
System
: TDAQ
Type
: Information
Status
: closed
System Affected : TDAQ | Monitoring
TDAQ_Logbook
: Technical Runs
TDAQ_Component
: Integration
TDAQ_Case
: Combined
Logbook URL
First use of online DQMF for Muon EF:
Basic check
histograms are filled?
: http://pcatdsrv01.cern.ch:8100/ATLAS/754
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More histograms checking have been added to the DataQuality Monitoring utility.
These are 3 histograms produced by TrigMoore algorithm running in EF.
For now they are checked with a very simple algorithm that verifies if the histograms are filled or not.
To be replaced with more sophisticated analysis when Diana will find out more about this.
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Muon EF DQM/DQA
 FEX Algorithm: variables to test quality of the seeded reconstruction, acceptance and rejection
Wrt LVL2 or previous step, compare some variables (if available in the sequence step) with LVL2
or previous step
 Hypo Algorithm: cut variables on which take rejection/acceptance decision, acceptance and
rejection
 Significant histograms and plots shown here are produced by Muon EF offline validation code
(assuming a good calibration real detector/MC…)
However, to be ready to flag real data by using meaningful checks :
As much as possible realistic data samples should be used (e.g. pt distribution of muons from the
Tech. run sample looks very strange for muon ….), including pile-up and cavern background
effects
For the moment, exercises done with monochromatic single muons, muons from  decays
(dominating the EF rate at low threshold) and top, but not complete, since there are other
histograms/checks identified not yet studied, here discussed (in grey)
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Samples used
 single muons: 6 GeV and 17 GeV
 muons from  (single particle decays,properly weighted), official
production:
http://gridui02.usatlas.bnl.gov:25880/server/pandamon/query/?mode=taskquery&qDSInput=%25slice%25&
qsubmit=QuerySubmit
https://twiki.cern.ch/twiki/bin/view/Atlas/MuonsFromPiK
 top: mc11.004100.T1_McAtNLO_top.AANT.v11000201
All processed with release 12.0.6
No final decision on granularity (barrel,Ecs, …) for proposed histos/checks,
but all studies performed by looking to the different regions
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seeded (by LVL2 ROI) reconstruction in MS (Moore in EF)
 Track quality (fit 2/n.d.f.)
Top events
<pt> = 35 GeV
< > = 0.92
Muons from 
<pt> = 8 GeV
Checks: monitor <> and r.m.s.
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< > = 0.91
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seeded (by LVL2 ROI) reconstruction in MS (Moore in EF)
 Track 2 probability
Checks: compare distribution with reference histos
Top events
 Final track normalized (divided by errors) residuals distribution per
tecnology
good sensitivity to calibration and alignment
Checks: if gaussian, fit results with < > /  compatible with 0/1
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seeded (by LVL2 ROI) reconstruction in MS (Moore in EF )
 Track pt, ,
Top events
Top events
Top events
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17 GeV Muons, barrel
6 GeV Muons, all eta
17 GeV Muons, ECs
17 GeV Muons, all eta
Checks: compare distributions with reference (in realistic conditions),
all checks should be calibrated with real data
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seeded (by LVL2 ROI) reconstruction in MS (Moore in EF )
 Nhtec = Track number of hits per technology (MS) vs eta
|| < 2.4
Top ev.
MDT hits
< > =20.34
r.m.s.=6.5
Top ev.
phi hits
< > =5.7
r.m.s.=2.1
Muons from 
MDT hits
< > =19.25
r.m.s.=5.6
Checks: stability in <> and r.m.s. of number of hits
per tecnology in defined eta region
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seeded (by LVL2 ROI) reconstruction in MS (Moore in EF )
 Rhits= Nhtec/(total # of hits per tec. in ROI)
conditions
good sensitivity to background
 R = + / -
all eta
17 GeV Muons, all eta
-
+
R
MOORE
MuiCB
6 GeV
0.990.01
0.990.01
17 GeV
1.010.02
1.000.02
Top ev.
1.160.14
1.160.14
Checks: R stability within errors
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Track estrapolation to the interaction region (MuId
Standalone in EF)
 monitor match parameters of MuId Standalone track with the closest
ID track
 monitor parameterization for energy loss in the calorimeters
(ptMuIdSA-ptMoore) wrt pt
 (pt,,) after estrapolation
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check as already described
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Combined reconstruction with ID (MuId Comb. in EF)
 Final track 2,(pt, , ) at interaction point
 R = + / -
check as already described
check as already described
 PCA (a0,z0) at the interaction region
if prompt muons, distributions are also
related to the luminous region dimensions
Checks: monitor <>  and 2
of gaussian fits of MuIdCB
Z0
Top ev.,  ~ 5.4 cm
z0
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Top ev.,  ~ 50m
a0
Atlas Data Quality Workshop
a0 :distributions with non
gaussian tails could require a
fit with sum of 2 gaussians:
the ratio of integrals of the
two gaussian can be used to
monitor the relative weight
core/tails in distribution
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TrigMOORE wrt LVL2
 Comparison with LVL2 ROI (pt(?),,)

Top ev., MuId comb pt vs pt LVL2
<> ~ -44 MeV  ~ 318 MeV
Top ev., MuId comb phi vs phi LVL2
<> ~ 0  ~ 0.3 mrad
Checks: monitor <> , and 2 of the fit of the differences
(e.g. MuId CB FEX var - LVL2) : same as page before for non gaussian tails
track multiplicity per ROI
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sensitivity to background, ROI overlapping, etc.
Atlas Data Quality Workshop
M. Primavera
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“Muon EF Trigger monitoring”
 Acceptances (|| < 2.4) wrt LVL2 or wrt previous step
Acceptance
Muons from top
(%) <pt> ~ 35
GeV
6 GeV single
muons (%)
17 GeV single
muons (%)
MOORE wrt
LVL2
96.8±0.5
95.9±0.1
96.1±0.2
MuidSA
wrt LVL2
95.3±0.6
90.4±0.1
95.0±0.2
MuidCB wrt
LVL2
93.8±0.7
89.0±0.1
93.3±0.2
MuidSA wrt
MOORE
98.4±0.4
94.3±0.1
98.8±0.1
MuidCB wrt
MuiSA
96.9±0.5
98.4±0.1
98.3±0.1
Checks: acceptance stability by checking counters
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Hypo algorithms
 For the moment implemented at the end of the muon EF sequence
(MuIdCombined) and not applied in validation. Presently cut variable is pt
only, thus for monitoring:
histograms/parameters to be checked: pt spectrum before
and after cut/acceptance (= accepted # / total # of triggers )
Total # of histos to be checked for Muon EF: reasonably < 50
(considering all sequence steps and , slices), maybe
collecting experience the number of really meaningful histograms
will decrease
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Plans (short term)
 Implementing histograms inside the code by using common monitoring
tools for trigger
 continue studies on realistic data samples in order:
• to individuate other meaningful variables for DQ
• to evaluate reliability of the proposed checks
• to understand sensitivity to different run conditions/data deteriorations
 Getting familiar with DQMF algorithms in the Workbench and online
Plans (middle term)
 Start thinking to the implementation of a higher level Muon slice DQ in
“quasi-online”/offline environments for deeper DQM/DQA
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Backup slides
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New HLT Sequence:
LVL2::muFast
LVL2::muComb
Hypo Test
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L2_muX
EF_muX
EF::TrigMoore
EF:TrigMuidSA
EF::TrigMuidCB
Atlas Data Quality Workshop
Hypo Test
EF_muX
EF::ID
EF_muX
M. Primavera
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