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Muon Event Filter Status Report

Muon Event Filter Status Report. Sergio Grancagnolo for the muon EF working group INFN Lecce & Salento University. Outline. Performance in releases 12, 13, 14 Robustness to misalignments Muon EF wrappers for offline supertools Converters Menus Muon trigger CSC note status.

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Muon Event Filter Status Report

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  1. Muon Event FilterStatus Report Sergio Grancagnolo for the muon EF working group INFN Lecce & Salento University

  2. Outline • Performance in releases 12, 13, 14 • Robustness to misalignments • Muon EF wrappers for offline supertools • Converters • Menus • Muon trigger CSC note status

  3. Muon Slice performance From CSC Note – Muon Rates - Convolution method12.0.6 trigger sw LVL1 emulation muFast+hypo muComb+hypo TrigMooreMS TrigMooreSA TrigMooreCB+hypo Pythia 6.4 for b,c DPMJET for p/K (conservative choice) large theoretical uncertainties at pT below 6 GeV must focus onp/K rejection at low pT mu6 needs prescaling mu20/40 need isolation or prescaling at 1034

  4. EFId w.r.t. muComb single muons 13.0.40.2 14.0.0 nightly TrigMooreCB w.r.t. muComb single muons 12.0.6 13.0.40.2 14.0.0 nightly Single muons mc12.*.RDO.* • ATLAS-CSC-01-02-00 • 12.0.6 • 13.0.40.2 • 14.X.0 devval, rel_3 (12 Mar 2008) Efficiencies • a drop of the CB trigger eff. at low pT has been observed in 13.0.30 – recovered in 14.x.0 nightlies – appears related to EFID rather than Muon Algos • Stable eff. at high pT 12.0.6 13.0.30.3 Z

  5. Resolution 1/pT MuIdSA MuIdCB 12.0.6 13.0.40.2 14.X.0 MuIdSA performance is more or less constant for all releases MuIdCB shows slight deterioration in 14.X.0 wrt previously

  6. 12.0.6 13.0.40.2 14.X.0 Resolution h and f MuIdSA MuIdCB h h MuIdSA MuIdCB f f h and f resolution stable with releases

  7. p/K rejection From the CSC note present cuts • Inner Detector d0 ≤ 0.15 • ID n. of pixel hits ≥ 3 • ID n. of B layer hits ≥ 1 • ID n. of SCT hits ≥ 6 • pT (ID) / pT (SA) ≤ 1.25 • Combined match c2 ≤ 26 single m single p min.bias p/K min.bias p/K to be implemented in a new hypo algorithm for 14.x.x with current set of cuts (not extensively optimized) • 75% eff. @ 4GeV for (1-effBG)=35% • 90% eff. @ 20GeV for (1-effBG)=25%

  8. Robustness against misalignments • RDO reconstruction and AANT/AOD production performed with Athena 13.0.40.2 • Four reconstruction scenarios considered with different knowledge of ID and/or MS alignment: • Aligned ID and aligned MS (perfect correction of misalignments) • Aligned ID and misaligned MS(crude MS misalignments ~1mm) • Misaligned ID and misaligned MS (ID as in FDR1 + MS as above) • Misaligned ID and aligned MS(ID as in FDR1 + perfectly known MS) Efficiencies Dramatic loss of EF algos’ efficiency with misal ID. Misal MS even worse at high pT EF_MuidCB wrt LVL2 EF_InDet wrt LVL2 Event-based efficiencies applying lowest muon threshold

  9. Resolution 1/pT IDal-MSal •IDal-MSmisal • IDmisal-MSal• IDmisal-MSmisal EF InDet EF InDet pT reso 2-3 times larger with misal ID MuidCB pT reso below 10% with misal ID, out of control at >100 GeV with Misal MS 5% 3% EF MuidCB EF MuidSA 5% 3% 5% 2% 3% Standard deviation of pT(Reco) / pT(Gen)

  10. Resolution h IDal-MSal •IDal-MSmisal • IDmisal-MSal• IDmisal-MSmisal 3x10-3 EF InDet EF_ID h resolution constant with misal ID MuidCB h resolution 2-3 times larger with misal ID/MS MuidSA h performance unchanged 5x10-4 EF MuidCB EF MuidSA 2x10-3 5% 3% 2% 5x10-4 3x10-4 5x10-3 2x10-4 3x10-3 Standard deviation of h(Reco) – h(Gen)

  11. Standard deviation of f(Reco) – f(Gen) Resolution: f IDal-MSal •IDal-MSmisal • IDmisal-MSal• IDmisal-MSmisal EF_ID f resolution constant with misal ID 2x10-3 5x10-4 MuidCB f worse at high pT with misal MS, resolution ~ mrad with misal ID 3x10-4 2x10-4 MuidSA h performance unchanged EF InDet 2x10-3 3% 2% 5x10-4 3x10-4 2x10-4 5x10-3 EF MuidCB EF MuidSA 3x10-3

  12. Robustness considerations • Tests on muon trigger robustness performed on (mis)aligned data, running the full Muon Slice shows that • With crude non-realistic (~mm) MS misalignments + realistic ID misalignments (FDR1): • EF efficiencies deteriorate significantly • EF spatial resolution under control, but pT gets worse above 50-100 GeV (below 10% with ID misal. only)

  13. Converters – state as today • MuonCnv/MuonByteStream • bytestream Converter to RDO for Mdt, Rpc, Tgc, Csc • bytestream Converter to Mdt PrepData • bytestream Converter to Rpc PrepData but no ambiguity/redundancies solving • For trigger technologies online data format very different wrt offline • no bytestream to PrepData Converter for Tgc, Csc today • MuonCnv/MuonRdoToPrepData • Conversion Algorithms from RDO to PrepData for all technologies • uniform in general structure among technologies • implemented for the MC: input is the RDO ! • can be run on bytestream: when the algorithm retrieve the RDO, the bytestream to RDO Converters are activated and the RDO become available in memory for further conversion (as in M5) • converting full event even when working in a region of interest !! • for RPC the reason is having clean RIO collections – no redundancies/ambiguities • NEED to preserve the RoI driven data access

  14. New data access schema for RPC (I) • @ the EF, the algorithm (FeX) requests RPC PRD in a h x f region (RoI) • get from the region selector a list of data collection hash id (offline) in the RoI • get from cabling service the corresponding list of pad identifiers • Retrieve from StoreGate the pad container and find (i.e. decode into RDO) each pad in the selected list  output is the RDO for the RoI • i.e. just use the byte-stream to RDO converter • convert the RDO into PRD by applying the redundancy and ambiguity removal currently implemented in the offline algorithm for RDO  PRD • First implementation of the schema proposed for RPC offline / Event Filter is ready / under test • in the offline (re-use not duplicate code) MC and DATA • RDO to PRD delegate all the work to the new AlgTool used over the whole event  allow to use the StatusCode + an attached string describing the kind and severity of the problem in data preparation  robustness • The schema can be adopted for all muon technologies • uniform way of accessing the data embed all that into an AlgTool

  15. TrigMoore implementation LVL1 • Seeding Algorithms assume the seed from LVL1 or LVL2, barrel or endcap • Reconstruction only in the geometrical regions provided by the RoIs of previous levels • 3 instances of TrigMoore are called by the steering for: • Reconstruction in MS • Extrapolation to the IP • Combination with ID tracks • Each TrigMooreFeature is accessed by TrigMooreHypo to test hypotheses LVL2 (muFast) LVL2 (muComb) Seeding Algs Moore Algs Hypo Alg TrigMoore MuIdStandAlone Algs Hypo Alg Inner Detector Algs MuIdCombined Algs Hypo Alg

  16. Follow up with the new Moore style for 14.0.0 • A new package: Trigger/TrigAlgorithms/TrigMuonEFhosts 4 HLTalgorithms: • TrigMuonEFSegmentFinderwrapper for MooSegmentCombinationFinder (offline tool invoqued with vector of pointers to prd collections) DONE • TrigMuonEFTrackBuilderwrapper for the offline tool MuonCombiTrackMaker (invoqued with vector of pointers to segment combination) DONE • TrigMuonEFExtrapolator wrapper forMuidBackTracker DONE • TrigMuonEFCombiner wrapper TO BE DONE for the main tool of MuidCB (COMING SOON ?) • Running with release 14.0.0 - producing standalone EF muons propagated to the interaction point • Most work is just in configuration • requires dedicated configuration of the tools for running in trigger • The new chain (up to the available implementation) will be in 14.1.0 • defined temporary extra muon trigger sequences to be run concurrently with the standard EF (TrigMoore) • needs to revise the trigger AOD for the EF

  17. New EF wrappers New implementation schema of muon EF code (to be implemented for 14.1.0) With wrappers for offline tools LVL1 LVL2 (muFast) The slow particle trigger TrigMuGirl will be also included in 14.1.0 or 14.2.0 LVL2 (muComb) TrigMuonEFSegmentFinder MooSegmentCombinationFinder Hypo Alg TrigMuonEFTrackBuilder MuonCombiTrackMaker Hypo Alg TrigMuonEF TrigMuonEFExtrapolator MuidBackTracker Hypo Alg Inner Detector Algs TrigMuonEFCombiner Combination tool Hypo Alg In red: to be implemented

  18. Revision of muon EF trigger AOD • The separate step of segment finding allow for another early hypothesis algo • As an example if the number of segments in inner/middle/outer MS layers is stored • Fit c2 could be saved at different track building steps • To implement hypo algos for p/K rejection • At least combined match c2 fit must be stored • Link to the ID track used in combination • Use of ElementLink if ID info is already stored in AOD • Store ID info if missing (21 bytes) • Proposal made @ last Muon Slice Trigger Software (3 Apr) for a new schema • Possibility under study

  19. Muon Trigger Menus • A lot of effort has been put in cross checking the trigger rate estimated with the convolution method and with the counting method (on min. bias Pythia 6.4 samples) • a basic agreement is observed taking into account the different theory input for p/K rates • full details can be found in reports at Nov. Trigger and Physics week and at Dec.2007 TDAQ week • Based on estimated trigger rates the muon trigger menus have been defined for 1031 and 1032 assuming standard muon slice algorithms (no isolation yet, no p/K rejection strategies) • first though for 1033 based on extrapolation of 1032 • Need to account for minimum bias pile-up • Reliable samples needed • implications of 1033 luminosity at 75 ns bunch crossing spacing

  20. Menus (13.0.40.4) & Rates for of 1032 (13th February)

  21. PROPOSAL FOR OPTIMIZATION OF 1032 new Very fast estimate of the cumulative rate gives : ~50 Hz (against 112 as before)

  22. Not yet inside the menu definition

  23. Status of Muon Trigger CSC Note • Comments received from referees before Easter • Almost all comments have been implemented and the remaining ones are going to be finalized • Mainly editorial work • Figures to be uniformed in style • New draft sent to referees for further comments

  24. Conclusions • Muon EF performs satisfactory in releases 13 and 14 • Several studies of robustness against misalignment • Need to better understand how much realistic are the considered scenarios • effort on-going for having realistic (day 0) MS misalignments for FDR2 (~100 microns) • Muon EF wrappers for offline supertools planned to enter in release 14.1.0 • Muon EF AOD under study • Reenginering of Converters: common effort for different technologies • Muon trigger menus @ 1032 under optimization • first thoughs for 1033 • Muon trigger CSC note in final shape

  25. Backup

  26. pT(Reco) / pT(Gen) distributions 6 GeV Single Muons Resolution : pT MuIdCB 13.0.40.2 12.0.6 14.X.0

  27. pT(Reco) / pT(Gen) distributions 19 GeV Single Muons Resolution : pT MuIdCB 12.0.6 13.0.40.2 Systematic underestimate for release 12.0.6 . This problem seems overcome in the subsequent releases 14.X.0

  28. pT(Reco) / pT(Gen) distributions 100 GeV Single Muons Resolution : pT MuIdCB 13.0.40.2 12.0.6 pT resolution looks stable wrt releases at high transverse momentum 14.X.0

  29. 12.0.6 13.0.40.2 14.X.0 Mean of pT(Reco) / pT(Gen) gaussian fit Mean 1/pT : EF MuidSA & MuidCB MuIdSA MuIdCB No offset appear in reconstructed EF pT

  30. Beam halo • Samples by A. Stradling: • /castor/cern.ch/user/s/stradlin/PileupNM/misal1_mc12.007499.singlepart_empty/halo h gen pT gen (MeV) f gen (rad) pT gen (MeV)  The Muon Trigger seems unaffected by muons in beam halo(statistical significance to be evaluated according to the luminosity of the simulated sample) 54294 generated events 0 at LVL1 & HLT

  31. RPC Raw Data and Prep Raw Data Offline: PrepRawData On-line: RDO • on-line hits different from off-line hits • h.w. duplicated hits due to cabling overlap • s.w duplicated hits due to wired-or and logical-or • 3 types of trigger hits in the readout • We have to deal with a very different structure of the online and offline data model

  32. Current path to RPC PrepData @ EF • RPC bytestreamRDOprep data i.e. running the offline algorithm for RDOPRD conversion which, as first step, activates the converter bytestreamRDO • run before the steering (not trigger driven!!!) • converting full event even when working in a region of interest • inefficient • the reason is having clean PRD collections • no redundancies /ambiguities • current byte-stream to PRD converter does not solve overlaps/ambiguities because it scans sequentially the byte-stream and output a PRD for each relevant CM hit • data clean-up requires to apply some logic on top of raw hits (which must necessarily be organized and stored in some format) • the most natural and well tested format for that is the RDO

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