1. 1 FastTrack: Real Time Silicon Tracking for LHC Alessandro Cerri (borrowing from several talks…)

2. 2 Outline What are we talking about? –ATLAS trigger (quick!) overview –What’s missing? Does it work? How? –CDFII experience –Evolving towards LHC Why would one want to use it? –Selected physics cases Think outside the box!

3. 3 The ATLAS Trigger High rate pp collisions force us to throw away events: 40MHz  ~100Hz You want to throw away uninteresting* stuff How? Combine trigger primitives: “crude” approximations of analysis objects, like: –Jets –e/  –Tracks –E t (and lack thereof) –EM Where is the 3 rd generation???

4. 4 FastTrack L2 is designed to be basically a commercial CPU farm …not enough time to reconstruct tracks at full resolution Why would I want to do that? –b tagging –  –… but keep your mind open: you can do a lot more with a little fantasy! Is there money (physics reach) to gain? 3 rd generation is the closest to new physics!

5. 5  30 minimum bias events + H->ZZ->4  Tracks with P t >2 GeV Where is the Higgs?   FTK  FastTrack to the rescue! Where is the Higgs? Help!

6. 6 ATL-DAQ-2000-033 with Fast-Track offline b-tag performances early in LVL2. You can do things 1 order of magnitude better ATLAS TDR-016 0.6 100 10 1000 bb RuRu Calibration sample bbH/A bbbb tt qqqq-bb ttH qqqq-bbbb H/A tt qqqq-bb H hh bbbb H +- tb qqbb Z 0 bb The case for offline-like b-tagging

7. 7 FastTrack/LHC: access to the 3 rd generation ATLAS + FTK 4  E T 200 + j70 + j50 + j15 (|  |<2.5) ““ ““ 2.6  6 + j25 + j10 (|  |<2.5) ATL-COM-DAQ-2002-022 F. Gianotti, LHCC, 01/07/2002 CMS TDR 6 & Scenario: L= 2 x 10 33 deferral ATLAS CMS 5b-jet 237Inclusive b-jet 50 mini ev. 2 b-jets + M bb > 50 160 mini ev. 2 b-tags + M bb > 50 0.2 j200 3j90 4j65 40  20 2  10 0.8 0.2  20 2  6 HLT rate (Hz) HLT selection LVL1 rate (KHz) LVL1 selection 25 j400 3j165 4j110 13b leading 43 b-tags Even better strategies: see ‘physics cases’

8. 8 Is it feasible? We are talking about something capable of digesting 100000 evts/second and identifying tracks in the silicon What on earth would be able to do that?  ~ 48  m Single Hit Superstrip Road Detector Layers … it turns out CDFII has been doing something similar since day 0 The recipe uses specialized hardware: 1)Clustering Find clusters (hits) from detector ‘strips’ at full detector resolution 2)Template matching Identify roads: pre-defined track templates with coarser detector bins (superstrips) 3)Linearized track fitting Fit tracks, with combinatorial limited to clusters within roads

9. 9 Is it effective? 2 b-jets (Z  bb) MET + disp. tracks (ZH) lepton + disp. track (SUSY) gamma + disp. track (SUSY) Many high-pt triggers based on SVT are taking data. SVT SVT rejection: 3 orders of magnitude

10. 10 Can we scale to the ATLAS complexity? Not easy: –500K channels  O(100M) –20  s  2  s But feasible: –SVT has been designed in ~1990 with (at the time) state of the art technology –We have been thinking a lot on how to improve the technology –The SVT ‘upgrade’ (2005) is in fact partly done with hardware capable of LHC-class performance! 1998: Full custom VLSI “Associative Memory” chip: 128 patterns 2004: Standard Cell “Associative Memory” chip: ~5000 patterns

11. 11 1/2  AM Divide into  sectors 6 buses 40MHz/bus ATLAS Pixels + SCT Feeding FTK @ 50KHz event rate Pixel barrelSCT barrelPixel disks 6 Logical Layers: full  coverage 2  sectors ~70MHz cluster/layer (Low Luminosity, 50KHz ev.) ATLAS-TDR-11 Allow a small overlap for full efficiency

12. 12 How to pick the ATLAS data? Fast Track + few (Road Finder) CPUs Fast Track + few (Road Finder) CPUs ROB offline quality tracks: Pt >1 GeV Ev/sec = 50~100 kHz ~NO impact on DAQ PIPELINE LVL1 Fast network connection CPU FARM (L2 Algorithms) CALO MUON TRACKER Buffer Memory ROD Buffer Memory ROB FE S-link Two outputs! ~40 9U VME boards

13. 13 Selected Physics Cases

14. 14 Lots of ideas, limited energy: Z  bbBetter acceptance (calibration samples) bbH/A H  bb,  Low Pt b-jets H  hh  bb bb ll Lower thresholds (calibration sample) W  Multi-prong  triggersImproved acceptance B  Lower thresholds

15. 15 Example 1: Z  bb Important calibration tool to measure jet response/resolution (  -jet and z-jet balance have theo/exp issues) Standard trigger: Large L1 rate  higher Et threshold  high Mjj turn-on With FastTrack: qg  Zq  bbq (3jet + btag) advantages: Better Mjj acceptance, improved rejection Highest Et jet needs not be tagged! LVL1LVL2 S/  B MU6  + 2J2.6 KHzM bb > 50160 Hz  60 (@20 fb -1 ) 3J + SE2004 KHzM bb > 5050 Hz  20 (@20 fb -1 ) J1905 KHz1 non-b, 2b10 Hz  21 (@30 fb -1 )

16. 16 Example 2: bbH/A  bbbb ATLAS-TDR-15 (1999) M A (Gev) tan  200 Optimized Analysis (not very recent though): 4 b-jets |  j |<2.5 P T j > 70, 50, 30, 30 GeV efficiency 10% Effect of trigger thresholds (70,50,30,30)->4x110 !!! ATLAS + FTK triggers 13%3b leading3j +  E T 200 8%3 b-tagSoft 6  + 2j Effic.LVL2LVL1 As efficient as offline selection: full Higgs sensitivity ATL-COM-DAQ-2002-022 Standard trigger limits tan  reach at low M A !!!

17. 17 Example 3:  @ CMS L=2x10 33 cm -2 sec - 1 0.4 0.5 0.6 0.7 0.8 0.9 1. 0 0.02 0.06 0.1 0.14  (QCD 50-170 GeV)  (H(200,500 GeV)   1,3h+X) m H =500 m H =200 TRK tau on first calo jets Pix tau on first calo jet Staged-Pix tau on first calo jet TRK tau on both calo jets Calo tau on first jet 0.0070.004 Efficiency & jet rejection could be enhanced by using tracks before calorimeters. L 2 /L 1 Default algorithm: calorimetric search first, then tracking Isol: R~0.2-0.45 Tag tracks: R~0.07 Lead. Track: R~0.1

18. 18 Q: Which of these represents an actual trigger rate vs luminosity?

19. 19 Be careful! CDF misunderestimated(  GWB) the background rates by large (~2x) factors. Not for ingenuity but for lack of better ways of extrapolating to the High Energy Frontier! Expect something similar! Rates and rejections must be understood at our best NOW: Anything too loose will be cut out/removed Trigger rates are *not* dominated by physics:

20. 20 Where would I put effort Simulating background requires HUGE resources: billions of MC events @ 5 minutes/event ?!?? Revert to fast simulation Calibrate (e.g. jet response and trigger efficiencies) from full simulation Parameterize in AtlFast! Need to strengthen the physics case: Ideas Other physics cases Applications Tools Fast simulation is basically there (but still not 100%) There is a substantial setup time: the sooner the better Brainstorming!

21. 21 Beyond b tagging? FastTrack is extremely modular With little interfacing, any detector can in principle be used as seed for FastTrack objects: –Muons –Calorimetry –TRT What would you be able to do with those at trigger level? Any other wild dream of yours? Mine: FastTrack can do more complicated pattern recognition than just tracks –Vertices? –Topological triggers?

22. 22 perform b tagging. ol that allows good trigger Some References: http://www.pi.infn.it/~orso/ftk/ http://www.pi.infn.it/~annovi/ http://hep.uchicago.edu/cdf/shochet/ (under ftkxxx) http://www-cdfonline.fnal.gov/svt/ physics

23. 23 IEEE Trans. Nucl. Sci. 51, 391 (2004)