1. 1 Michela Biglietti (Universita’ di Napoli-Federico II) Gabriella Cataldi (INFN Lecce) and the HLT

2. 2 MooMakePhiSegments RPC/TGC digits PhiSegments MooMakeRZSegments MDT digits MooMakeRoads CrudeRZSegments MooMakeiPatTracks MooRoads MooiPatTracks MooMakeNtuples Ntuples MooAlgs MooStatistics Each step is driven by an Athena top- algorithm Transient objects are passed via TDS/StoreGate Independent algorithms, the only coupling is through the transient objects Standard Moore flow

3. 3 Reconstruction Strategy Searches for  regions of activity From the RPC/TGC  measurements “  - Segments” are created Searches for R-Z regions of activity For each “  -Segment”, the associated MDTs is found and a “crude” RZ Segments is built (essentially collections of z hits).

4. 4 Reconstruction Strategy  Pattern recognition and outer Roads –Inside MDTs the drift distance is calculated from the drift time, by applying various corrections on it (TOF, second coordinate, propagation along the wire, Lorenz effect). From the 4 tangential lines the best one is found. –All the “MDT segments” of the O station are combined with those of the M layer. The MDT hits of each combination are added to the phi- hits of the “Phi Segment”, forming “outer” track candidates. All the successfully fitted candidates are kept for further processing.  Final tracks  associate inner station MDT hits. A “final” track is defined  The successful “outer” track is subsequently used to  as a successfully fitted collection of trigger hits and of MDT hits from at least two layers. MDT mutilayer

5. 5 Moore is a container MooAlgs MooEvent MooAlgs_n Events for reconstruction Athena algorithms with different features/goals MooLVL2Algs Moore structure run-time plug in differents algos in order to build the reconstruction chain. MooStatistics MooAlgs contains the standard sequence of Algorithms: MooMakePhiSegments MooMakeRZSegments MooMakeRoads MooMakeTracks MooLVL2Algs contain a possible seeding approach MooMakePhiSegmentLVL2 MooMakeRZSegmentLVL2

6. 6 RPC digits PhiSegment MDT digits RZSegmentMap MooMakePhiSegmentLVL2 MooMakeRZSegmentLVL2 trigout10GeV.txt trigout20GeV.txt ….. run athena with the appropriate jobOptions.txt MooLVL2Algs strategy Set-up the logic link: TestRelease/… /run/Persint.out  … /… /trigoutxxx.txt How to run Moore and MooLVL2Algs Documentation in: http://people.na.infn.it/~bigliett/moore/MooreDoc/MooreDoc/ run atrig ASCI files only on barrel

7. 7 MooLVL2Algs outputs are: PhiSegments RZSegments In order to perform a fit the standard Algorithms MooAlgs must be plugged in the sequence MooMakePhiSegmentLVL2 MooMakeRZSegmentLVL2 MooMakeRoads MooMakeTracks

8. 8 First need: If we want to have the seeded Moore in the HLT environment we need: MooAlgs MooLVL2Algs in HLT MooAlgs in HLT assuming that the sequence is always valid, and accessing to all the event, i.e Standard Moore running. No use of TriggerElements. First step:

9. 9 MooTopAlg.h... private: // Pointers to sub-algoritms MooMakePhiSegments * m_MooMakePhiSegmentsAlgs; MooMakeCrudeRZSegments * m_MooMakeCrudeRZSegmentsAlgs; MooMakeRoads * m_MooMakeRoadsAlgs; MooMakeiPatTracks * m_MooMakeiPatTracksAlgs; // initialize and execute methods for subalgs template StatusCode initializeAlgs(std::string, T* ); template void executeAlgs(T*);... First step: MooAlgs in HLT Creation of a new subpackage In MuonSpectrometer/Moore ( Is this the right place ?) MooEFAlgs MooTopAlg.cxx bool MooTopAlg::execHLTAlgorithm(TriggerElement* TEout){ executeAlgs(&m_MooMakePhiSegmentsAlgs); executeAlgs(&m_MooMakeCrudeRZSegmentsAlgs); executeAlgs(&m_MooMakeRoadsAlgs); executeAlgs(&m_MooMakeiPatTracksAlgs); //Let's suppose Moore always validates the sequence... log label() << endreq; TEout->SetActive(true); return true; } In MooEFAlgs the selection/seeding algorithms will also be included

10. 10 How to proceed ? Our understanding is that NOW we can access the Offline Identifiers of RPC selected by LVL1 Trigger. Keeping in mind that in future we will use LVL2 output, can we access RoI in terms of Offline Identifiers from the LVL1 ? If yes, how?

11. 11 As it is now MooLVL2Algs are seeded with the list of HitsOnTrack from LVL2. MooLVL2Algs work with Old EDM layout M geometry. In the future (personal opinion) MooLVL2Algs for HLT should use as input the RoI (eta, phi) and the pt from LVL2 (in order to confirm or reject their estimate), opening a Region of Interest around the track, and performing the PhiSegment, RZSegment search, as for standard Moore, in a limited region. MooLVL2Algs seeded with list of HitsOnTrack will be useful for comparison of results. How to seed MooLVL2Algs. RPC hitsMDT hits

12. 12 Hits comparison 10GeV  - N associated (MDT hits) counts MooAlgs MooLVL2Algs 10GeV  - N associated (RPC hits) counts MooLVL2Algs MooAlgs  Same dataset used for MooAlgs MooLVL2Algs  The 2 different sets of algos are chained together  Fit results from the same sample of events are directly compared Plans for testing a more general hit addition procedure

13. 13 22 22 MooLVL2Algs MooAlgs 10GeV  - counts   MooLVL2Algs 1TeV  - counts

14. 14 1/p T pull 10GeV  - 1/p T pull counts MooAlgs 1/p T pull 10GeV  - counts MooLVL2Algs

15. 15 p T resolution MooLVL2Algs 10GeV  - counts 10GeV  - counts p T resolution MooAlgs

16. 16