The FastTracker real time processor and its impact on Muon isolation, Tau and b-jet online selections at ATLAS

A. Andreani, A. Andreazza, A. Annovi, M. Beretta, V. Bevacqua, G. Blazey, M. Bogdan, E. Bossini, A. Boveia, V. Cavaliere, F. Canelli, F. Cervigni, Y. Cheng, M. Citterio, F. Crescioli, M. Dell'Orso, G. Drake, M. Dunford, P. Giannetti, F. Giorgi & 36 others J. Hoff, A. Kapliy, M. Kasten, Y. K. Kim, N. Kimura, A. Lanza, H. L. Li, V. Liberali, T. Liu, D. Magalotti, A. McCarn, C. Melachrinos, C. Meroni, A. Negri, M. Neubauer, J. Olsen, B. Penning, M. Piendibene, J. Proudfoot, M. Riva, C. Roda, F. Sabatini, I. Sacco, M. Shochet, A. Stabile, F. Tang, J. Tang, R. Tripiccione, J. Tuggle, V. Vercesi, M. Villa, R. A. Vitillo, G. Volpi, J. Webster, Kohei Yorita, J. Zhang

Research output: Contribution to journalArticle

32 Citations (Scopus)

Abstract

As the LHC luminosity is ramped up to 3 × 10 34 cm 22s 1 and beyond, the high rates, multiplicities, and energies of particles seen by the detectors will pose a unique challenge. Only a tiny fraction of the produced collisions can be stored offline and immense real-time data reduction is needed. An effective trigger system must maintain high trigger efficiencies for the physics we are most interested in while suppressing the enormous QCD backgrounds. This requires massive computing power to minimize the online execution time of complex algorithms. A multi-level trigger is an effective solution to meet this challenge. The Fast Tracker (FTK) is an upgrade to the current ATLAS trigger system that will operate at full Level-1 output rates and provide high-quality tracks reconstructed over the entire inner detector by the start of processing in the Level-2 Trigger. FTK solves the combinatorial challenge inherent to tracking by exploiting the massive parallelism of associative memories that can compare inner detector hits to millions of pre-calculated patterns simultaneously. The tracking problem within matched patterns is further simplified by using pre-computed linearized fitting constants and relying on fast DSPs in modern commercial FPGAs. Overall, FTK is able to compute the helix parameters for all tracks in an event and apply quality cuts in less than 100 μs. The system design is defined and the performance presented with respect to high transverse momentum (high-p T) Level-2 objects: b jets, tau jets, and isolated leptons. We test FTK algorithms using the full ATLAS simulation with WH events up to 3×10 34cm 2s 1 luminosity and compare the FTK results with the offline tracking capability. We present the architecture and the reconstruction performance for the mentioned high-p T Level-2 objects.

Original languageEnglish
Article number6140940
Pages (from-to)348-357
Number of pages10
JournalIEEE Transactions on Nuclear Science
Volume59
Issue number2
DOIs
Publication statusPublished - 2012 Apr
Externally publishedYes

Fingerprint

central processing units
muons
isolation
actuators
Detectors
Luminance
detectors
luminosity
Field programmable gate arrays (FPGA)
Data reduction
tracking problem
Momentum
Physics
associative memory
Systems analysis
data reduction
Data storage equipment
transverse momentum
systems engineering
helices

Keywords

  • Associative memory
  • FPGAS
  • particle tracking
  • pattern recognition

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Nuclear Energy and Engineering
  • Nuclear and High Energy Physics

Cite this

Andreani, A., Andreazza, A., Annovi, A., Beretta, M., Bevacqua, V., Blazey, G., ... Zhang, J. (2012). The FastTracker real time processor and its impact on Muon isolation, Tau and b-jet online selections at ATLAS. IEEE Transactions on Nuclear Science, 59(2), 348-357. [6140940]. https://doi.org/10.1109/TNS.2011.2179670

The FastTracker real time processor and its impact on Muon isolation, Tau and b-jet online selections at ATLAS. / Andreani, A.; Andreazza, A.; Annovi, A.; Beretta, M.; Bevacqua, V.; Blazey, G.; Bogdan, M.; Bossini, E.; Boveia, A.; Cavaliere, V.; Canelli, F.; Cervigni, F.; Cheng, Y.; Citterio, M.; Crescioli, F.; Dell'Orso, M.; Drake, G.; Dunford, M.; Giannetti, P.; Giorgi, F.; Hoff, J.; Kapliy, A.; Kasten, M.; Kim, Y. K.; Kimura, N.; Lanza, A.; Li, H. L.; Liberali, V.; Liu, T.; Magalotti, D.; McCarn, A.; Melachrinos, C.; Meroni, C.; Negri, A.; Neubauer, M.; Olsen, J.; Penning, B.; Piendibene, M.; Proudfoot, J.; Riva, M.; Roda, C.; Sabatini, F.; Sacco, I.; Shochet, M.; Stabile, A.; Tang, F.; Tang, J.; Tripiccione, R.; Tuggle, J.; Vercesi, V.; Villa, M.; Vitillo, R. A.; Volpi, G.; Webster, J.; Yorita, Kohei; Zhang, J.

In: IEEE Transactions on Nuclear Science, Vol. 59, No. 2, 6140940, 04.2012, p. 348-357.

Research output: Contribution to journalArticle

Andreani, A, Andreazza, A, Annovi, A, Beretta, M, Bevacqua, V, Blazey, G, Bogdan, M, Bossini, E, Boveia, A, Cavaliere, V, Canelli, F, Cervigni, F, Cheng, Y, Citterio, M, Crescioli, F, Dell'Orso, M, Drake, G, Dunford, M, Giannetti, P, Giorgi, F, Hoff, J, Kapliy, A, Kasten, M, Kim, YK, Kimura, N, Lanza, A, Li, HL, Liberali, V, Liu, T, Magalotti, D, McCarn, A, Melachrinos, C, Meroni, C, Negri, A, Neubauer, M, Olsen, J, Penning, B, Piendibene, M, Proudfoot, J, Riva, M, Roda, C, Sabatini, F, Sacco, I, Shochet, M, Stabile, A, Tang, F, Tang, J, Tripiccione, R, Tuggle, J, Vercesi, V, Villa, M, Vitillo, RA, Volpi, G, Webster, J, Yorita, K & Zhang, J 2012, 'The FastTracker real time processor and its impact on Muon isolation, Tau and b-jet online selections at ATLAS', IEEE Transactions on Nuclear Science, vol. 59, no. 2, 6140940, pp. 348-357. https://doi.org/10.1109/TNS.2011.2179670
Andreani, A. ; Andreazza, A. ; Annovi, A. ; Beretta, M. ; Bevacqua, V. ; Blazey, G. ; Bogdan, M. ; Bossini, E. ; Boveia, A. ; Cavaliere, V. ; Canelli, F. ; Cervigni, F. ; Cheng, Y. ; Citterio, M. ; Crescioli, F. ; Dell'Orso, M. ; Drake, G. ; Dunford, M. ; Giannetti, P. ; Giorgi, F. ; Hoff, J. ; Kapliy, A. ; Kasten, M. ; Kim, Y. K. ; Kimura, N. ; Lanza, A. ; Li, H. L. ; Liberali, V. ; Liu, T. ; Magalotti, D. ; McCarn, A. ; Melachrinos, C. ; Meroni, C. ; Negri, A. ; Neubauer, M. ; Olsen, J. ; Penning, B. ; Piendibene, M. ; Proudfoot, J. ; Riva, M. ; Roda, C. ; Sabatini, F. ; Sacco, I. ; Shochet, M. ; Stabile, A. ; Tang, F. ; Tang, J. ; Tripiccione, R. ; Tuggle, J. ; Vercesi, V. ; Villa, M. ; Vitillo, R. A. ; Volpi, G. ; Webster, J. ; Yorita, Kohei ; Zhang, J. / The FastTracker real time processor and its impact on Muon isolation, Tau and b-jet online selections at ATLAS. In: IEEE Transactions on Nuclear Science. 2012 ; Vol. 59, No. 2. pp. 348-357.
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AU - Andreani, A.

AU - Andreazza, A.

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AU - Bevacqua, V.

AU - Blazey, G.

AU - Bogdan, M.

AU - Bossini, E.

AU - Boveia, A.

AU - Cavaliere, V.

AU - Canelli, F.

AU - Cervigni, F.

AU - Cheng, Y.

AU - Citterio, M.

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AU - Dunford, M.

AU - Giannetti, P.

AU - Giorgi, F.

AU - Hoff, J.

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AU - Lanza, A.

AU - Li, H. L.

AU - Liberali, V.

AU - Liu, T.

AU - Magalotti, D.

AU - McCarn, A.

AU - Melachrinos, C.

AU - Meroni, C.

AU - Negri, A.

AU - Neubauer, M.

AU - Olsen, J.

AU - Penning, B.

AU - Piendibene, M.

AU - Proudfoot, J.

AU - Riva, M.

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AU - Tripiccione, R.

AU - Tuggle, J.

AU - Vercesi, V.

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N2 - As the LHC luminosity is ramped up to 3 × 10 34 cm 22s 1 and beyond, the high rates, multiplicities, and energies of particles seen by the detectors will pose a unique challenge. Only a tiny fraction of the produced collisions can be stored offline and immense real-time data reduction is needed. An effective trigger system must maintain high trigger efficiencies for the physics we are most interested in while suppressing the enormous QCD backgrounds. This requires massive computing power to minimize the online execution time of complex algorithms. A multi-level trigger is an effective solution to meet this challenge. The Fast Tracker (FTK) is an upgrade to the current ATLAS trigger system that will operate at full Level-1 output rates and provide high-quality tracks reconstructed over the entire inner detector by the start of processing in the Level-2 Trigger. FTK solves the combinatorial challenge inherent to tracking by exploiting the massive parallelism of associative memories that can compare inner detector hits to millions of pre-calculated patterns simultaneously. The tracking problem within matched patterns is further simplified by using pre-computed linearized fitting constants and relying on fast DSPs in modern commercial FPGAs. Overall, FTK is able to compute the helix parameters for all tracks in an event and apply quality cuts in less than 100 μs. The system design is defined and the performance presented with respect to high transverse momentum (high-p T) Level-2 objects: b jets, tau jets, and isolated leptons. We test FTK algorithms using the full ATLAS simulation with WH events up to 3×10 34cm 2s 1 luminosity and compare the FTK results with the offline tracking capability. We present the architecture and the reconstruction performance for the mentioned high-p T Level-2 objects.

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KW - Associative memory

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KW - particle tracking

KW - pattern recognition

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