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Artificial Neural Networks as a Level-2 Trigger for the H1 Experiment: Status of the Hardware Implementation

Author

Listed:
  • D. Goldner

    (Institut für Physik, Universität Dortmund, Dortmund, Germany)

  • H. Getta

    (Institut für Physik, Universität Dortmund, Dortmund, Germany)

  • M. Kolander

    (Institut für Physik, Universität Dortmund, Dortmund, Germany)

  • T. Krämerkämper

    (Institut für Physik, Universität Dortmund, Dortmund, Germany)

  • H. Kolanoski

    (Institut für Physik, Humboldt-Universität zu Berlin, Berlin, Germany)

  • J. Fent

    (Max-Planck-Institut für Physik, Munich, Germany)

  • W. Fröchtenicht

    (Max-Planck-Institut für Physik, Munich, Germany)

  • F. Gaede

    (Max-Planck-Institut für Physik, Munich, Germany)

  • A. Gruber

    (Max-Planck-Institut für Physik, Munich, Germany)

  • J. Huber

    (Max-Planck-Institut für Physik, Munich, Germany)

  • C. Kiesling

    (Max-Planck-Institut für Physik, Munich, Germany)

  • T. Kobler

    (Max-Planck-Institut für Physik, Munich, Germany)

  • J. Köhne

    (Max-Planck-Institut für Physik, Munich, Germany)

  • J. Möck

    (Max-Planck-Institut für Physik, Munich, Germany)

  • P. Ribarics

    (Max-Planck-Institut für Physik, Munich, Germany)

  • S. Udluft

    (Max-Planck-Institut für Physik, Munich, Germany)

  • D. Westner

    (Max-Planck-Institut für Physik, Munich, Germany)

  • T. Zobel

    (Max-Planck-Institut für Physik, Munich, Germany)

Abstract

Triggering at the HERA ep collider is challenging because of the high bunch crossing rate and an expected large background. In the H1 experiment, a trigger decision is made in four steps (level 1–4), stepwise decreasing the event rate and allowing for more sophisticated trigger decisions. The time available for L2 is about 20 μs. We have proposed to use an artificial neural network (ANN) for the L2 trigger based on the CNAPS-1064 chip available from Adaptive Solutions, (Oregon, USA). The intrinsic parallelism of the ANN algorithm together with the dedicated hardware offers fast processing of the trigger informations. The trigger system uses up to 10 decision units, each consisting of a Pattern Recognition Module (PRM) and a Data Distribution Board (DDB). A DDB receives the L2 data stream and generates the network inputs used by the algorithms on the PRM. A PRM is a commercial VME board carrying the CNAPS processors.

Suggested Citation

  • D. Goldner & H. Getta & M. Kolander & T. Krämerkämper & H. Kolanoski & J. Fent & W. Fröchtenicht & F. Gaede & A. Gruber & J. Huber & C. Kiesling & T. Kobler & J. Köhne & J. Möck & P. Ribarics & S. Udl, 1995. "Artificial Neural Networks as a Level-2 Trigger for the H1 Experiment: Status of the Hardware Implementation," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 6(04), pages 541-548.
    • Handle: RePEc:wsi:ijmpcx:v:06:y:1995:i:04:n:s012918319500040x
    DOI: 10.1142/S012918319500040X
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