1. D0 Level 3 filters Dan Claes Moacyr Souza U. of Nebraska Fermilab / Lafex - Rio de Janeiro Dzero Collaboration Meeting November 9th, 2001

2. status of ScriptRunner status of Filters/Tools status of L3 Monitoring

3. Build/append/delete pieces of the execution tree, on demand. status: working properly Do the Filter Dispatching -Execution tree implemented as a linked list pattern -Intended behavior : never hear about it! 1) No logic involved 2) There is only one way to go : otherwise -> crash This is how robustness was insured status: No complaints ! (never heard about!) Gather status & statistics and send Monitoring data to servers : I will be taking about at the end Digest the coor commands and act according status: working properly after some re-arrangements with L3 Frame

4. L3TJet Tool seeks 95% rejection of L2-accepts, relying on the high precision calorimeter readout available in L3 and the improved energy and position resolution this makes possible identify (and reject) low-E T events passing L2 trigger sharpen the turn-on curve may need to introduce additional kinematic cuts dijet mass, jet-lepton angular separations Resolutions obtained by comparing L3 jets to MC jets 1/ E dependence with best fit constant term of 0.87 (central calorimeter) 1.16 (forward calorimeter)

5. L3TJet Tool leading jet p T for JT_HI failed and passed events JT_HI CJT(1,10) JET_15(MinEt=15) 18.5 JT_LO CJT(1,5) JET_10(MinEt=10) 8.77 Rejection:

6. For development studies Electron Tool currently implemented by filtering on highly electromagnetic jets applies cut on emfrac calculated within the calorimeter cluster tool EM_LOW: CEM(1,5) P T >7 GeV emfrac>0.9 EM_HIGH: CEM(1,10) P T >11 GeVemfrac>0.9 final runs (132947-133014) before shutdown 375K events included a substantial subset of Mark & Pass’ed events offline studies by Ia Iashvili (UC-Riverside)

7. efficiency as a function of P T recalculated w.r.t. Z=0 P T EM (GeV) CEM(1,10) P T >11 GeV emfrac>0.9 Rejection = 5.5 sharpens the turn-on (emfrac alone = 3.6) from 32117 Mark&Passed events

8. efficiency as a function of P T recalculated w.r.t. Z=0 P T EM (GeV) from 32117 Mark&Passed events CEM(1,10) P T >11 GeV emfrac>0.9 with the added OFFLINE Good EM Requirements: EM fraction > 0.9 Isolation<0.2 HM41<200 |  |<0.8

9. ISO HM9HM41 Emf All events Passed events No bias observed between filtered and M&P data

10. efficiency as a function of P T recalculated w.r.t. Z=0 P T EM (GeV) from 525 Mark&Passed events CEM(1,5) P T >7 GeV emfrac>0.9 Rejection = 15 (emfrac alone = 2.7)

11. L3 EM Certification Ulla Blumenschein (Mainz) Single electron efficiency in CC fiducial region vs electron p T L3 EM object with EMFR>0.9 with track match with CPS match

12. proposed L3TEle Electron Tool applying a cut only on emfrac should duplicate the conditions we ran under at shutdown possibly more rejection available with isolation cut offline (and parallel Mark&Pass filters) will study harder shower shape cuts preshower calls will be implemented when CPS available Plan to come up running a fully functional tool with the following available functionality:

13. L3TCPS Central PreShower Clustering Tool authors: Andre Turcot (BNL),Chunhui Han (MICH) Combine contiguous strips above threshold into single-layer- clusters (SLCs) for each layer and hemisphere. Apply a SLC energy threshold cut Search for geometrically allowed combinations (of one SLC from each layer) matched within position errors and with a reasonable energy correlation Implements L3Region and localized clustering. (with either  or  from electron or photon tool) Once CPS readout is commissioned ~2 weeks to implement into L3Ele

14. L3TCPS Tool PERFORMANCE Efficiency defined as clusters matched within 20 mm divided by number of pT>5 GeV e  within CPS fiducial Z 0  e + e  with 6 Min Bias events Efficiency=293/296 = 99% t t events with 7 Min Bias Efficiency = 76/93 = 82% J/  (low P T ) study (for events passing L1/L2) Efficiency = 76/93 = 86% QCD20 sample passing L1/L2 Rejection=17 ( track/CPS/cal match ) Timing Regional clustering =2ms Unpacking = 5 ms

15. l3fCalMEt Missing Et Tool author: Lee Sawyer (Louisiana Tech) calorimeter cell-based tool L3TCalUnpTool provides unpacked cell information assumed to include ICD/MG sampling corrections CAL energy stored (assuming nominal (0,0,0) vertex) Missing E t calculated through intermediate  ring sums L3TPrVtxTool returns the most probable primary vertex recalculate ring sums using primary vertex currently uses the nominal (0,0) calculates Missing E T,,  , scalar E T, and Missing E T significance no muon correction included yet Ready to run pending certification studies

16. SMT Unpacking & Clustering Scales with the number of clusters avg time avg #clusters

17. CFT Unpacking & Clustering Scales with the number of clusters avg time avg #clusters spread here due to sorting fibres into order

18. CFT Tracking Algorithm - L3TCFTTracker Initialization x,y,  positions of every fiber calculated stored in arrays for fast lookup Track-finding in selected L3Regions or across entire detector Adjacent hits merged into clusters and average x,y,  position stored Single track may physically cross no more than 3 adjacent fibers in any doublet layer. Clusters longer than 3 not used. Tracking proceeds in 2 stages:axial followed by stereo. Separation permits axial tracking alone. A fast circle fit (axial layers) identifies candidates as arcs thru the origin. A straight line fit in the Sz-plane determines the track helix parameters S is the arc length traversed in the xy-plane Principal author: Ray Beuselink ( IMPERIAL ) Daniela Bauer, Robert Illingworth  00 (x c,y c ) S xy R x y 00 d0d0

19. CFT Tracking Algorithm - L3TCFTTracker “Link-and-tree” Algorithm - developed for TASSO, used by ALEPH Links join clustered hits from different layers radius calculated of the circle thru both clusters and the origin must exceed radius corresponding to selected P T cut even a 0.5 GeV/c cut reduces combinatorics dramatically Links across a missing layer allowed (up to two total missing layers) Starting from a link in the outer layer, candidate track paths built by adding links from adjacent layers to extend path length if curvature consistent with preceding link continues recursively. The longest extended path found starting from the initial link is kept as a track candidate

20. See DØ note 3779 for performance studies. L3TCFTTracker Example Resolution plots for Z->μμ

22. L3TCFTTracker Status Some final coding to complete and test followed by Certification L3TVertexFinder First version of a Primary Vertex tool in test release designed to run from CFT tracks, but being expanded to include the global tracker (requires minor mods) Certification Ready for online testing~January, 2002

23. L3TSMTTracker - Silicon Microstrip Tracker author: Daniel Whiteson ( BERKELEY ) modified “link-and-tree” method - segments connect neighboring hits between points within  =0.4 (tunable parameter) segment paths are linked if z-slope within 0.2 and  within 0.015 (both tunable parameters) of previous segment without seed info, begin with outermost SMT layer, Look for longest paths toward center Longest paths fitted to a helix. Path with smallest   2 selected - its hits marked as in use. Paths are to have 4 hits, and not > 2 consecutive missed layers. SMT divided into 24 15 O sections. Track segments may cross boundaries, but not skip sections. Hits on disks ignored.

24. Event sample Efficiency Purity Hits per track msec/evt correct/incorrect Single 5-GeV .788 1.0 4.55/.005 7.44 (1000 events) Z .784 0.929 4.45/.111 51.3 (100 events) Z .740 0.930 4.51/.131 50.2 (100 events) Efficiency:  2 1.0 GeV cuts applied to all tracks “missed” tracks lack full 3D info - z position placed at strip center L3TSMTTracker - Efficiency & Purity Studies

25. Level 3 Global Track Finding author: Daniel Whiteson ( BERKELEY ) preliminary results on a global (SMT plus CFT) stiff track finder Find axial CFT tracks Track “stubs” - CFT axial hit pairs in outer two layers (X7 and X8) having d  /dr < maximum value determined by Pt_min Linear extrapolation of each stub predicts crossing at next CFT layer hits within d  /dr added if do not increase  2 by more than 35.0 Axial tracks required to have 7 hits. Match stereo clusters For a given axial track stereo clusters reconstructing z within CFT hit pairs on outer layers U4 and V4 linearly extrapolated sequential least-squares estimate updated w/hits at each radius CFT track requires at least 7 axial hits matched with stereo hits Extend into SMT A fully fit CFT track can be propogated into SMT (see preceding description of SMT Track Extension)

26. Level 3 Global Track Finding author: Daniel Whiteson ( BERKELEY ) Uses raw data from CFT Uses 1-dimensional raw data from SMT to avoid cluster ghosts Combines CFT and SMT information in a globally rather than simply extending tracks from CFT SMT information helps improve resolution and reject fakes Employs an adaptive histogramming technique for stereo tracking Time depends on P T min threshold & number of tracks in event

27. Efficiency Studies Event sample P t cut Efficiency Purity Hits per track correct/incorrect Single 5-GeV  0.0 GeV 1.00 1.00 10.8/ 0.03 Z  +0 minbias 2.0 GeV 0.97 1.00 9.95/ 0.34 3.0 GeV 0.96 1.00 10.4/ 0.24 5.0 GeV 0.99 1.00 10.6/ 0.17 10. GeV 1.00 1.00 10.6/ 0.17 Z  +2 minbias 2.0 GeV 0.94 0.99 9.92/ 0.43 3.0 GeV 0.97 0.99 10.2/ 0.38 5.0 GeV 0.97 0.99 10.7/ 0.39 10. GeV 0.98 1.00 10.5/ 0.31 Z  +0 minbias 2.0 GeV 0.96 1.00 9.93/ 0.43 5.0 GeV 0.97 1.00 10.3/ 0.38 10. GeV 0.97 1.00 10.3/ 0.43 Z  +2 minbias 2.0 GeV 0.90 1.00 9.44/ 0.72 5.0 GeV 0.96 1.00 9.75/ 0.74 10. GeV 0.98 1.00 9.69/ 0.77

28. Proposed Level 3 SMT-only Tracker author: Daniel Whiteson ( BERKELEY ) single track (SMT-only) filter now under study using data to provide additional rejection to current muon, jet filters

29. Runs 132167-8:SMT (4 hits) tracks 13000 evts (magnet on) #tracks vs  trk at DCA DCA(cm) vs  sine wave also seen offline (vertex not centered) straight bands show noise DCA (sine wave subtracted out) tracks within Gaussian are highly pure

30. Runs 132167-8:SMT ( 5 hits) tracks 13000 evts (magnet on) #tracks vs  trk at DCA DCA(cm) vs  sine wave also seen offline (vertex not centered) straight bands show noise DCA (sine wave subtracted out) tracks within Gaussian are highly pure

31. Filtering data with a simple SMT track Vertexer SMT tracks examined for 2 or more with close z-positions at DCA Maximal Z-distance between tracks in a given vertex Z  MC QCD (PT>20) Data

32. vertex filtered SMT-only efficiencies QCD, pt>20, 2.5mb Z  2.5 mb data runs 130167-8 Z-distance (cm)Min pT (GeV)

33. L3 Primary Vertex Algorithm author: Guilherme Lima (UERJ/Brazil) D0Note # 3592 - J. Zhou, J. Hauptman, and M. Narain Sort SMT barrel hits in  Define  -slices up to 50 hits or  = 0.2 maximum discard slices with < 10 hits De-ghost by defining roads using 2 o stereo hits and then use 90 o hits only when within the road Pair hits with  1 cm Histogram z-axis projections (with 1 cm bin width) of all hit pairs in each slice Threshold selects vertex candidate peaks for each  -slice Sum slices counting number of slices contributing to, and total # of entries in, each candidate peak. Discard candidates with <3 contributing  -slices Assign probabilities of (#entries) x (#slices) Merge candidates with separation < 0.5 cm

34. Efficiency Studies t-tbar 5000 eventsX to b-bbar 250 events B to  Ks,  to  1000 events Prompt  to e+e- 1000 events W to  1000 events W to e 1000 events Z to  1000 events Z to ee 1000 events Z to  1000 events  + jet 1000 events Generated hits Reconstructed hits Eff(%) Resol(  m) Eff(%) Resol(  m) t-tbar93620792000 B  K94510431100 QCD95500661500 L3TPrVtxTool Dependent on event topology Has yet to be tested on REAL DATA

35. L3TMuon, skeleton version of full global muon tool calls: L3TMCT, the calorimeter confirmation tool L3TMuoCentralMatch (calls a central track tool) Provides Tracker with region to look for tracks. Tracks matched at muon A layer using a  2 based on  and  extensively studied w/ 1000 -event 5 GeV p T single muon sample but not yet with real data Performance studies and certification of these features underway L3TMuon author: Paul Balm (NIKHEF) Martin Wegner, Martin Grunewald (Aachen) L3TMuoUnpack (unpacking tool) run successfully in ONLINE tests but not yet independent of rapidly changing configuration files fix provided by Scott Snyder to be implemented & checked

36. interim L3TMuon functionality collect Mark & Pass data filtering on local muon track reconstruction only: L3TMuoLocal (RunI-style segment finder) Fast reconstruction of the local muon track reconstructs track segments using the space points (hits) within a single module links segments before and after toroid to make full track narrowing down  and P T adapts OFFLINE segment and local track algorithms, introduces FAST segment finder pending the unpacker’s independence of configuration files and confirmation of a memory leak fix

37. Continue development and testing to stage additional Muon Tool functionality January, 2002? L3TMuoCentralMatch calling L3TCFT fast central track tool when track readout available studies completed with single muon and B  J/  K s MC samples, but performance tests and certification w/real data still to be completed L3TScint author: Victor Koreshev (IHEP,Russia) constraining track parameters with narrow scintillator time window L3TMTC verifying MIP trace thru the calorimeter

38. timing Paul Balm (NIKHEF) L3TMuon 1000 B  J/  K s MC sample L3MuoUnpacker/calibration 3 msec/event (unpacking of SMT+CFT+Muon 21 msec/event) GlobalTracker 7 msec/event SMTTracker 10 msec/event CFTTracker >133 msec/event (~15 overflows) L3Tmuon tracking 66 msec/event L3TMuoCentralMatch 4 msec/event ~70 ms/evt for local muons only ~95 ms/evt with GlobalTracker match 1 GHz Clued0

39. L3FTauHadronic Level3 TauTool author: Gustaaf Brooijmans (FNAL) pursuing two approaches Calorimeter-driven search: Starts with L3TCalCluster p T >1 GeV providing cluster widths and profiles E T >3GeV width 0.25 L3TCFTTracker provides p T >1 GeV tracks, collect those:  <0.25  <0.4 Track-based search: Starts from L3TCFTTracker providing p T >1GeV CFT (cluster tracks w/  R<0.3), order in , match with L3TCalCluster clusters Certifying code, plan to get non-optimized filter into triggerlist, gather information online for tuning under online conditions

40. Some Timing Estimates Tool Timing Estimate CalUnp 10 msec/eventCalCluster <1 msec L3jet <1 msec CPS unpack <1 msecCPS clustering <1 msec SMTunpack 10 ms (~1/2 spent clustering) SMT Tracking 10 msec Global Tracking 10 msec CFTunpacking 2 msec (~1/3 spent clustering) PrimVtx(SMT) 2 msec MuoUnp 3 msec MuoSegment <1 msec MuoTrackFitting 66 msec (J/  study) on typical (QCD) events to cluster calorimeter cells and get a primary vertex ~40msec. muon events ~70msec with Global trackmatch ~90msec.

41. Last Run: medium luminosity (6E30) -no software vertexing was run 120-150 msec avg, but with LONG tails (most often due to muon) FILTERING time broke down as At 145 Hz into Level 2, the nominal budget was = N nodes / Hz In = 45/145 =.31 sec = 310 msec. Queuing theory warns of deadtime within 0.7 to 0.8 of this number. This was the "wall" hit at around a 220-250 msec processing rate. mu 55 % jet 16 electron 13 Missing E T 11 Mu confirmation 2 Sum E T 2

42. SR duties (other than make the filters dispatching) Fill the L3Chunk For each filter, record - status : passed/failed (and called) - Unbiased : L3Unbiased L2Unbiased “forced_unbiased” - L3prescaled - others Fill the Debug Chunk (on demand) - can vary Fill the Event_Header For each event, record : - L1 active && fired bit mask - L2 active && fired bit mask - L3 active && fired bit mask - Streaming information - run #, event #, Luminosity Block, data_size,... L3 Monitoring

43. Send monitoring information at a given heart beat For each filter, record - Rates : # called, # passed - Special events : # L3Unbiased # prescaled - Others : Histogram of the overall filtering time/per event … and time to time, send the Tools’ monitoring data (l3fstatmanager): per Tool : # of candidates Timing Correlations, others … Send monitoring information per Luminosity block For each L2 bit: - # events received - corresponding L2 bit number - L3 bit names (l3scripts) - L3 prescale factors - # events passed, per filter - # events failed, per filter - # events L3Unbiased L3 Monitoring

44. All this is already implemented in the SR side All monitoring information are grouped in the L3MonChunk and SR currently gathers all this information and inserts it into (L3MonChunk) There is only one heart beat: whenever the luminosity block index changes Any other persistent data can be added!

45. For the L3 Monitoring Server : In the SR / l3fchunk side : L3MonChunk methods (together they allow the implementation of the monitoring server) L3MonChunk operator + (L3Monchunk &c1, L3MonChunk &c2) implement the sum of all elements belonging to the L3MonChunk private members. This is, of course, crucial to the monitoring server implementation. Void makeMonString( std::string &) : information for the Daq_Monitor server This method produces a string with all the monitoring information in a format readable by the L3 monitor server. void makeString( std::stringt &) : information for the Luminosity server This method produces a string with all the monitoring information per luminosity block and all other information, in a format readable by the luminosity monitor server.

46. L3 Monitor Server : Main ingredients : Register nodes at start of run time Receive data from the Linux nodes and store them on node’s ( or process ) boxes Set up an alarm to time out nodes that overflow the time slice allotted Sum up information from all active nodes ( processes ) when either all nodes are done or if the alarm fires Produce (string) messages with all the information assembled according, to be sent to - Daq_Monitor_Display server - Luminosity server At the end of run time ( for all or for some nodes ) send information to the Run Summary server AND clear all boxes for those nodes ( processes ) that ended.

47. L3 Monitor Server L3 Nodes Run Summary Server DAQ Monitor Display Luminosity Server Information (L3MonChunk as a d0omStream object) is sent, as ITC messages, each time that the luminosity index changes Here the information from all actives (not timed out) nodes are summed up L3 Monitoring Rates, timing,... so far Statistics, rates,…, for this luminosity index value To be implemented Alarm

48. The L3 Monitoring Server Progress/Problems in the last (NT) run Progress: During the past beam run with NT nodes, we were able to run the Monitor Server and send information to the Daq Monitor. Also we were able to receive the luminosity monitoring information. Normally, 4 to 8 NT nodes were active. Problems: We had several problems, mostly related to ITC messages framework. One major problem was that: A certain number of nodes (2 to 4) always timed out - different ones, though. That made the monitoring display hard to understand for people not aware of this. That also made the luminosity information more or less useless, because time outs must be very exceptional for this (and any other) scheme to make sense. Hard to debug code in the SR side, because of other higher priorities during beam time

49. The L3 Monitoring Server: Progress/Problems with Linux nodes We had, so far, none of the problems seen with NT nodes : - no time outs - no corrupted data We have implemented the feature that the server can deal with several processes per node. So far, we had no problems. But we have not yet tested the system at full load, with : - Lots of nodes >> 10 (expected ~100 nodes, 2 processes per node) - Lot of information travelling

50. L3 Nodes Master L3 Monitor Server Run Summary Server DAQ Monitor Display Luminosity Server L3 Nodes L3 Monitor Server L3 Monitor Server L3 Monitor Server Taking advantage of the modular design, we may consider the possibilty of :

51. private area : map > _map; // L3ChunkStatMap vector _time; // Time Histogram map _clientData // holds all client information per run #: //L1 L2 map. L2 active bits mask // and L3 # name) map _l2map; // L2 # name map (all) map _tool; // ToolStatMap map[ _filter; //FilterStatMap map > _lum_old; // L3LumStatMap map > _lum_old_save; // L3LumStatMap L3MonChunk:

52. diem_cal L3FJet (Jet10) L3TEle (Ele_Loose) L3TJet (Jet_10) L3FMEt (calmet_) Ele1 el_jet_met Execution tree L2 bits L3 scripts L3 filters Tools L3FEle (ele2) L3FInvMass (inv_1).................. (ele1) L3FEle (ele1)

53. Conclusion Tools ready post-shutdown LTJet LTEle w/emfrac & isolation cuts available w/shower shape being tuned L3TMuoLocal pending certification MET pending certification SMT-only Tracker pending certification Additional tools ready by New Year L3TMuon w/ trackmatch, SCINT, MTC CPS available with hardware GlobalTracker for L3TCFTTrackeronline testing