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Triggering at LHC and SLHC

Triggering at LHC and SLHC

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Triggering at LHC and SLHC

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  1. Triggering at LHC and SLHC HEP2006 Ioannina 2006 Overview • First Level Trigger at LHC • Jet and Electron finding at LHC • First level Tracking Trigger at SLHC Costas Foudas, Imperial College London

  2. Triggering at LHC 22 70 mb deep inelastic component • At full LHC Luminosity we have 22 events superimposed on any discovery signal. • First Level Event Selection requires considerable sophistication to limit the enormous data rate. • Typical event size: 1-2 Mbytes. Costas Foudas, Imperial College London

  3. Trigger Challenge at LHC +30 MinBias Higgs ->4m • We want to select this type of event (for example Higgs to 4 muons) which are superimposed by this…… Costas Foudas, Imperial College London

  4. Jets at LHC • At LHC we want to select events that have: Isolated leptons and photons,high ET, -, central- and forward-jets as well as events with missing ET. • The QCD- are orders of magnitude larger than any exotic channel  . • QCD events must be rejected early in the DAQ chain and selecting them using high ET cuts in the trigger will simply not work. Costas Foudas, Imperial College London

  5. The CMS First Level Trigger RCT GCT TPG FE GT P Y/N • Detector data stored in Front End Pipelines. • Trigger decision derived from Trigger Primitives generated on the detector. • Regional Triggers search for Isolated e/ and  and compute the transverse, missing energy of the event. • Event Selection Algorithms run on the Global Triggers • FE: Front End • P: Pipeline • RCT: Regional Calorimeter Trigger • GCT: Global Calorimeter Trigger • GT: Global Trigger 128x25ns=3.2 µsec later i.e. 128 bunch- crossings latency Costas Foudas, Imperial College London

  6. The CMS Trigger System • 40 MHz input • 100 KHz FLT rate • 100 Hz written at the output • Event Size 1-2 Mbytes • The requirements on the Level-1 Trigger are demanding. • Level-1 Trigger: Custom made hardware processor. • High Level Trigger: PC Farm using reconstruction software and event filters similar to the offline analysis. Costas Foudas, Imperial College London

  7. The CMS First Level Trigger Detector Frontend Level-1 Trigger Readout Systems Event Run Builder Networks Manager Control Filter Systems Computing Services • The First Level decision is distributed to the Front-end as well as the readout units. • Front-end and readout buffers take care of Poisson fluctuations in the trigger rate. • Hand-shaking using back-pressure guarantes synchronization Costas Foudas, Imperial College London

  8. Strategy • Selecting events with high ET at the High Level Trigger level (HLT CPU farms) is not good enough. The rate must be cut earlier before the HLT is overwhelmed by many KHz of background QCD jet events. • It follows that the first level of selection, the First Level Trigger,should include algorithms of considerable sophistication which can find Isolated Electrons, Jets and detect specific event topologies. • This is a challenging task because we only have 15x25 ns = 375 ns to accomplish it for all sub-triggers. Jets take longer: 24x25 nsec = 600 nsec; which is many orders of magnitude faster than offline. • An example of this is CMS Global Calorimeter Trigger (GCT) Costas Foudas, Imperial College London

  9. Global Calorimeter Trigger • The GCT receives all the Calorimeter Trigger data, processes them and sends the data to the CMS GT 128 CC 24 CC Costas Foudas, Imperial College London

  10. The GCT Task • Jet Triggers: Central, Tau and Forward jet finding and sorting. • Jet Counters: Count Jets in 12 different regions of the detector or 12 different thresholds within the detector. • Electron/ triggers: Select and Sort the e/ candidates from Regional Calorimeter Trigger • Total Transverse, Total Missing Transverse and Total Jet Transverse Energy Calculation • Receive the Muon data and send them to the Global Muon Trigger. • Luminosity Monitoring and readout all the RCT and GCT data for every L1A. Costas Foudas, Imperial College London

  11. Jet Finders: A summary jet=(-1)ln(tan(jet/2))  • Particles strike the detectors and deposit their energy in the calorimeters. • Energy deposits in the calorimeters need to be recombined to reconstruct the transverse energy and direction of the original parton. • This is done using tools that are called Jet finders. Costas Foudas, Imperial College London

  12. Cone Jet Finders R0 • Searches for high transverse energy seeds and a cone in the - space is drawn around each seed. • Energy depositions within a cone are combined and the Et weighted  is calculated: • The new cone is drawn and the process is repeated until the cone transverse energy does not change Costas Foudas, Imperial College London

  13. CMS Calorimeter Trigger Assignments Costas Foudas, Imperial College London

  14. Basic Algorithm Ideas • Electron (Hit Tower + Max) • 2-tower ET + Hit tower H/E • Hit tower 2x5-crystal strips >90% ET in 5x5 (Fine Grain) • Isolated Electron (3x3 Tower) • Quiet neighbors: all towerspass Fine Grain & H/E • One group of 5 EM ET < Thr. • Jet or t ET • 12x12 trig. tower ET sliding in 4x4 steps w/central 4x4 ET > others • t: isolated narrow energy deposits • Energy spread outside t veto pattern sets veto • Jet  t if all 9 4x4 region t vetoes off Costas Foudas, Imperial College London

  15. The GCT Design Concentrator Card (1/1) Leaf Card (1/8) Wheel Card (1/2) Costas Foudas, Imperial College London

  16. The Leaf Card (e±, Jets, ET) • Main processing devices: Xilinx Virtex II Pro • 32 x 10 Gbit/sec Links with Serializers/Deserializers • Each serves 1/6 of the detector in Jet finding mode. Virtex-II Pro-P70 3x12 Channel 10 Gbit/s Optical Links (eventually) Costas Foudas, Imperial College London

  17. Data Sharing Scheme • Each Jet Leaf Card Serves 3 Regional calorimeter crates or 1/3 of half Barrel calorimeter (forward calorimeters have been included as edges of the barrel). • Each Leaf Searches for Jets using a 3x3 region sliding window and then passes the data to the next one in the circle. Costas Foudas, Imperial College London

  18. Data Concentration Scheme Regional Calorimeter Trigger • Key Decision: Convert the data to optical format so that they can be easily concentrated in one place for processing. 54 Source Cards Convert copper to optical Costas Foudas, Imperial College London

  19. The Source Card 4 7 4 2 8 3 6 5 • 1. 10-layer 6U VME form factor 2. USB 2.0 (Cypress SX2) 3. TTCrx & QPLL 4. 2xVHDCI SCSI for RCT input 5. 4 x Optical SFP output & SERDES • TLK2501 & Agilent HFBR-5720AL 6. LT1963 low-noise analogue supplies • SERDES driver, QPLL & SFPs 7. PTH05050 switch-mode supplies • Digital logic, FPGA core & aux 8. XC3S1000-5FG676C 1 Costas Foudas, Imperial College London

  20. LHC Trigger Overview • Most of the LHC Trigger Electronics are on the commissioning phase conducting integration test at CERN. • CMS benefits from recent advances in the field of FPGAs and optical link technology to design very compact and powerful triggers. • Similar technologies are required for the LHC upgrade which is the next topic of this talk. Costas Foudas, Imperial College London

  21. LHC Upgrade: Super LHC From a talk by Jim Strait to a DOE Meeting 18 April 2003 • The benefit from running LHC past ~2013 is limited. • A luminosity upgrade will be needed at that point. • Energy Upgrade is more expensive…... Costas Foudas, Imperial College London

  22. The LHC Upgrade: Super LHC LHCSLHC • CM Energy at 14 TeV (same) • Luminosity: 1035cm-2sec-1 (x10) - This means that the minimum bias background will go up by x10 • Bunch crossing frequency = 80 MHz - Reduces the minimum bias by ½ ~100 minimum bias events superimposed with discovery signals. F. Gainotti, M. Mangano, J. Virdee, Physics potential and experimental challenges of the LHC luminosity upgrade, hep-ph/0204087, April 1, 2002. Costas Foudas, Imperial College London

  23. LHC vs SLHC Events • ~550tracks per rapidity unit  2500 tracks/event within detector acceptance. • Detectors subject to High Radiation Environment. • Consequences on the design of the LHC detectors and Trigger. • Benefit 500 fb-1 (LHC)  2500 fb-1 Costas Foudas, Imperial College London

  24. Example of Physics at SLHC • Obviously with factors of 5-10 more Luminosity one can improve all the LHC measurements. • But there are questions from the SM Physics that we can only ask at the SLHC: Trilinear self-coupling terms proportional to HHH SM Arrows correspond to variations of HHH from 1/2 to 3/2 of its SM value HHHSM = 3m2H/v Costas Foudas, Imperial College London

  25. Radiation Levels and Detectors • R<20 cm need new technologies. • 20<R<60 cm pixels. • R>60cm push existing micro-strip technologies. • For an integrated Luminosity of 2500 fb-1 the inner detectors must withstand a fluences ~ 1016 part/cm2 Costas Foudas, Imperial College London

  26. Changes on LHC Detectors • Inner trackers must be replaced due to radiation hardness and higher clock frequency. • The data volume goes up drastically both due to the higher multiplicity of the SLHC events (100 min. bias) and due to the introduction of pixels at higher radius. Need either good ideas to reduce the data volume or faster optical links to transfer the data (probably both) • First Level Triggers will also change to accommodate the faster clock and improve algorithms • Pipeline Length will increase to 6.4 µsec 512 bunch crossings • Target output rate at 100 KHz as in LHC. Costas Foudas, Imperial College London

  27. Triggering at SLHC • All Triggers will suffer from higher backgrounds. • First Level Triggers have a challenging task because no further gain can come from the calorimeter and muon data which are already used at LHC to derive the first level trigger decision. • Gain cannot come from simply raising thresholds even if one is willing to compromise on cutting discovery channels. • Hence, the inner tracking data has to be included in the First Level decision (CMS). Costas Foudas, Imperial College London

  28. Get ideas from LHC design • The isolated electron rate can be reduced by a factor of 10 by correlating the hits of the inner tracker with the EM depositions in the calorimeter (G. Daskalakis). Another factor of 3 can be gained using the outer tracker. • The -trigger rate is also reduced by a factor of 10 if one correlates a jet found in the calorimeter with high Pt stubs found in the inner tracker. • Muon triggers follow similar trends. • Bottom Line:The benefit comes by including the inner tracker data in the trigger decision. • Need a device that correlates inner tracker track stubs with calorimeter or muon system objects Costas Foudas, Imperial College London

  29. Inner Tracker Occupancy 0-FF • Inner Tracker occupancy is dominated by low momentum (p<1 GeV) tracks not seen by the readout but seen by the trigger. • Consider a 1.28 cm x 1.28 cm sensor with 256x256 (64Kp) 50mx50m pixels at R=10cm from the interaction point. • Occupancy is 4 hits per 12.5 nsec per sensor. • Hit data rate: 5 Gbit/sec; Adding charge sharing and optical link overheads (Hamming code, 8b/10b) requires a 10 Gbit/sec optical link • Power ? Need to reduce this data rate if we want to have a realistic solution. Occupancy = 8.75, 3.75, 2.25 at R = 4 7 10 cm Costas Foudas, Imperial College London

  30. Considerations • We need a device that finds high Pt track stubs in the inner tracker which can be correlated with calorimeter trigger quantities. • The data should be processed and reduced on the detector to save on data volume, optical link speed and power. • Data reduction algorithms will run on radiation hard ASICs (.13 µm ?) • Complex Trigger Algorithms should run on off detector electronics using the reduced data sets. • Large FPGAs with fast 10 Gbit/sec links is the obvious technology solution for off detector electronics. Costas Foudas, Imperial College London

  31. Design Idea α 3-1 = 2 > +-1, fail 1 2 3 4 5 6 7 8 9 1 2 3 4 5 6 7 8 9 y 8-8 = 0 ≤ +-1, pass 8-9 = 1 ≤ +-1, pass • Consider a double layer pixel detector with pixels in stacked architecture: A Tracking Trigger Detector • If one assumes that the tracks come from the interaction point a cut on the angle α amounts to Pt cut i.e. High Pt tracks are radial in the x,y plane. • How do we make this cut ? 5-5 = 0 <= +-1, pass On detector electronics rejects hits that do not satisfy a next neighbour algorithm with programmable cuts. x Costas Foudas, Imperial College London

  32. Pixel Architecture vdd IN-PIXEL irst reset pipeline cell row address vthresh ibias vss • Comparator draws most of the pixel power • Optical link power needs investigation but • depends upon the data rate Costas Foudas, Imperial College London

  33. Correlator Architecture Inner Sensor Outer Sensor • If c2 > c1 + 1, discard c1 • If c2 < c1 – 1, discard c2 • Else copy c2 & c1 into L1 pipeline, next c1 c1 c2 Column compare L1T Pipeline L1A Pipeline This determines your search window In this case, nearest-neighbour At low luminosity, all hits could be read out Put a ‘bypass’ switch in correlator L1A pipeline: 512 BX @ 80MHz x 4 hits / (1.28cm)2  ~10kByte event buffer Costas Foudas, Imperial College London

  34. How Good of a pT Cut ? 20x200 µm pitch, r=10cm, Nearest-neighbour • How low is the cut depends upon the stack radial separation and the next-neighbour algorithm. • The sharpness of the threshold curves depends upon the pitch. • Charge sharing causes further smearing not included here. Costas Foudas, Imperial College London

  35. Rapidity resolution 20µm x 50µm x 10µm pixels • The Calorimeter Trigger granularity is  = 0.0870.087 • At stack separations between 1-2 mm we can do better than that • Hence, we can correlate Track Stubs with Calorimeter Electromagnetic objects (Jets are much larger ~ 0.5) Costas Foudas, Imperial College London

  36.  resolution • 4T Magnetic Field dependent. • Sufficient for electrons above 20 GeV. Costas Foudas, Imperial College London

  37. Z-Vertex Resolution • Can be done on FPGA off-detector • Considering on detector ASIC Solutions Costas Foudas, Imperial College London

  38. Data Reduction • Data Reduction versus radius: • Only the stub data are send to the off detector electronics. Costas Foudas, Imperial College London

  39. Detector Overview x y y z x y z Costas Foudas, Imperial College London

  40. Sensor Technologies • Monolithic Active Pixels • Active element is epitaxial layer of Si (few µm thick) + Cheap + (Almost)-Standard Process - Radiation Tolerance - Fill-factor of in-pixel electronics - Slow charge-collection (thermal diffusion) • New idea coming for MAPS: 1µm grouped pixels  Fast CC, tiny capacticance, high radiation tolerance, 200:1 SNR • Thin Film on ASIC (TFA) – a-Si:H, HgI, CdZnTe • Use PCVD to deposit sensing layer on top of standard ASIC + Can control active region thickness and material + 100% fill factor + Looks to be VERY rad-hard (1.8x1016p/cm2) + Fast charge collection (for e-) + Separates ASIC design from sensor element - Non-standard step for sensing element - Very small signals (requires v. low noise electronics) Costas Foudas, Imperial College London

  41. Summary and Overview • Triggering at LHC and SLHC is a challenging but very interesting task. • The Micro-electronics and Optical link technology is on our side to take advantage. • We believe we have a workable design that can be used for a First Level Tracking Trigger at the SLHC. • Need to try it now by making some prototype detectors for testing these ideas Costas Foudas, Imperial College London

  42. Support Slides • LHC 60 fb-1 SLHC 1000 fb-1 Costas Foudas, Imperial College London