Background rejection

1. The ZEUS Trigger 107 Hz STT Front End CTD Front End e± 27 Gev p 920 Gev Other Components STT FLT CTD FLT ~0.7 s Barrel MVD Forward MVD 5s pipeline Global First Level Trigger 5s pipeline GFLT Accept/Reject 500Hz Other Components STT SLT CTD SLT Event Buffers Event Buffers ~10 ms Global Second Level Trigger GSLT Accept/Reject 80Hz STT CTD Event Builder Third Level Trigger cpu cpu cpu cpu cpu cpu 8Hz Offline Storage MVD data preprocessing MVD Data MVD data preprocessing MVD Data Track Finding Functional building CTD Data STT Data STT1 sector STT2 sector Pattern Recognition And Seed Production Primary Vertex Finding Track Fitting (Next step) Secondary Vertex Finding (future step) Summary ZEUS The ZEUS Global Tracking Trigger. HERA D.Gladkov on behalf of the ZEUS GTT group HERA after upgrade: Ep = 920 GeV Ee = 27 GeV LDesigned=1.5*10 31 cm-2s-1 • ZEUS Components: • CTD • MVD • STT • F/R TD • F/B/R CAL • F/B/R Muon System • BAC • SRTD • VETO The current design, implementation and performance of the ZEUS Global Tracking Trigger (GTT) Barrel Algorithm are described.  The ZEUS GTT integrates track information from the ZEUS central tracking chamber (CTD) and micro vertex detector (MVD) to obtain a global picture of the track topology in the barrel region (─1.5 < η < 1.5) of the ZEUS detector at the Second Level Trigger (SLT) stage.  Algorithm processing is performed on a farm of Linux PCs and, to avoid unacceptable deadtime in the ZEUS readout system, must be completed within the strict requirements of the ZEUS trigger system. The GTT plays a vital role in the selection of good physics events and the rejection of non─physics background within the very harsh trigger environment provided by the upgraded HERA collider.  The GTT Barrel Algorithm greatly improves the vertex resolution and the track finding efficiency of the ZEUS SLT while the mean event processing latency and throughput are well within the trigger requirements. Recent running experience with HERA production luminosity is briefly discussed. The design, implementation and performance of the ZEUS Global Tracking Trigger (GTT) Barrel and Forward Algorithms are described.  The ZEUS GTT Forward Algorithm integrates track information  from the ZEUS Micro Vertex Detector (MVD) and forward Straw Tube Tracker (STT) to provide a picture of the event topology in the forward  direction (1.5 < η < 3) of the ZEUS detector at the SLT stage. This region is particularly challenging because of inhomegenieties in the solenoid magnetic field, and the high occupancies in the forward direction from beam gas interactions and secondary scatters with the ZEUS beampipe.  The Forward Algorithm is distinct from the GTT Barrel Algorithm,  but runs in parallel on the GTT CPU farm. To avoid unacceptable  deadtime in the  ZEUS readout system, the Forward Algorithm processing  must be compliant with the strict requirements of the  ZEUS trigger system. The current status of the integration with the ZEUS DAQ and trigger systems is also reviewed. ZEUS Three experiments are running: ZEUS, H1, HERMES Results GTT components: CTD, MVD and STT Central Tracking Detector Micro Vertex Detector DAQ Compliance Straw Tube Tracker Three level ZEUS Trigger System : ► First Level Trigger (FLT) based on deadtime free hardware pipeline clocked every 96ns by bunch crossing signal. ► Second Level Trigger (SLT) based on a distributed transputer network. First intercomponent trigger evaluation. ► Third Level Trigger (TLT) based on a PC farm performing event reconstruction using ~offline code. CTD is a large cylindrical drift chamber. ► CTD ● 4608 sense wires in 9 superlayers ● odd numbered layer provides rφinformation ● even numbered layer provides rz information ● radii: inner 170 mm, outer 850 mm, length 2050 mm ● field 1.43 T, resolution ~ 200 μm ● ideally 72 hits per track ►GTT latency at SLT within CTD─SLT envelope. ► Mean GTT latency less than CTD─SLT. ► GTT Latency stable at 500Hz FLT rate. ► The silicon MVD was installed,inside CTD, during 2001 upgrade. ► Forward MVD (provides rφ information) ● 4 wheels of 28 silicon sensors ● 480 strips per sensor with ~30 μm resolution ● 7º–20º polar coverage ● radii inner 70 mm, outer 160 mm, length 410 mm ● ideally 8 hits per track ► Barrel MVD (provides rφ and rz information) ● 3 layers of silicon sensor ladders ● rφ and rz planes connect to the same readout channel ● 512 strips per sensor with ~30μm resolution ● radii inner 60mm, outer 160 mm, length 622 mm ● ideally 6 hits per track ► The STT was installed, in a forward endplug, during 2001 upgrade. ► STT (provides rφ information) ● 11000 straw tube connected ● 48 trapezoidal sectors ● three layer of straws per sector ● resolution ~ 200 μm ● 6º–25º polar coverage ● radii inner 120 mm, outer 800 mm, length 600 mm ● ideally 24 hits per track Z Vertex Trigger Efficiency => run by run GTT ─ OFFLINE Real Data Why a Global Tracking Trigger ? ► New tracking detectors, STT and MVD, added. ► Pre upgrade: SLT tracking from CTD only. Vertex resolution ~ 9 cm. ► MVD cannot contribute to FLT; SLT possible. ► Combining MVD , CTD and STT information at hit level improves track finding, vertex resolution, etc. at SLT. ► Data size cut made, but needs tuning ► Data size cut made, algorithm under development ► No data size cuts are required to control latency Background rejection Ref.: S. Goers ” The StrawTube Tracker of the ZEUS-Detector at HERA“ at IEEE IMTC 18-24/05/2004 Ref.: E. N. Koffeman et al., NIM A473, 26 (2001) Ref.: B. Foster et al., NIM A338, 254 (1994) GTT Barrel and Forward Algorithms Forward Algorithm Barrel Algorithm Reconstruction Steps: Reconstruction Steps: Decode MVD data: cluster information. ► “2D” cluster location: wafer geometry and orientation. ► Decode MVD data: cluster information. ► “2D” hit construction: forward wheel module geometry. GTT Architecture ► Segment finding in CTD. Using drift time data to break hit ambiguity, take segment candidates pointing to the beam line. ► Axial track finding in rφ plane. Seed segment from outer CTD superlayer. Matching internal segments with beam line constrain and fit track with fast circle fit in rφ plane. Match hits from MVD to the track and refit track, using MVD hits. ► Stereo track finding in sz plane ( s: path length in rφ plane). Using information from stereo layers to define z positions of hits. Match hits to found track in rφ plane and refit the track with matched hits. ►MVD hit matching. Match hits from MVD to the track and refit track, using MVD hits. ►Pair parallel STT sectors with same azimuthal angle and straw position. ► Within straw size window construct max and min slope straight lines trough all fired straw. ► Build single projection envelope. ► Collect information from all single projection envelopes to a functional. ► Maximum of functional gives vertex prediction from STT Physics ─ J/Ψ J/Ψ→ μ+ + μ- ( e+ + e-) 3000 events ► Hough transformation of fired straws, using vertex prediction. ► Find spikes in 2D phase space. ►Usage of binning algorithm with overlapping bins. ► Next steps: add BMVD information to the Algorithm and develop track fit. • GTT Hardware: • ► MVD readout: • 3 Motorola MVME2400 450MHz • ► CTD, CTDZ and STT interface • NIKHEF-2TP VME-Transputer • Motorola MVME2400 450MHz • ► PC farm: • 12 DELL PowerEdge 4400 Dual 1GHz • ► GTT/GSLT result interface: • Motorola MVME2700 367MHz • ► GSLT/EVB trigger result interface: • DELL PowerEdge 4400 Dual 1GHz • DELL PowerEdge 6450 Quad 700 MHz • ► Network switches: • 3 Intel Express 480T Fast/Giga 16 port • MVME = Fast and PC = GigaEthernet • PC and switch hardware provided by Intel Corp. CTD/CTDZ/STT interface MVD readout ► The Forward Algorithm in being development. First results are presented. ► Next steps: add FMVD information to the Algorithm and develop track fit. PC farm and switches Real data: vertex Real data: Latency ~ 1ms MC data: Latency ~ 4ms D* MC data: Vertex sigma ~8cm ► GTT latency at SLT within CTD─SLT envelope. ► Mean GTT latency ~ 10 msec. ► GTT now in use with physics triggers (GTT performance superior to CTD─SLT). ► Barrel Algorithm stable development. ► Forward Algorithm first results seen. ► Next steps: include MVD into Barrel and Forward Algorithms . GTT/GSLT interface EVB/GSLT result interface ► Single electron track reconstruction efficiency ~80% ► Next step: improve reconstruction for low pT tracks ► D* MC sample: sigma ~ 8 cm., latency ~ 1ms. ► First results from Forward Algorithm running online ► Next step: Forward GTT vertex efficiency study Dmitri.Gladkov@desy.de http://mvddaq.desy.de/~mvddaq/GTT/