Speaker
Dr
N. Konstantinidis
(UNIVERSITY COLLEGE LONDON)
Description
We present a set of algorithms for fast pattern recognition and track
reconstruction using 3D space points aimed for the High Level
Triggers (HLT) of multi-collision hadron collider environments. At
the LHC there are several interactions per bunch crossing separated
along the beam direction, z. The strategy we follow is to (a)
identify the z-position of the interesting interaction prior to any
track reconstruction; (b) select groups of space points pointing
back to this z-position, using a histogramming technique which
avoids performing any combinatorics; and (c) proceed to the
combinatorial tracking only within the individual groups of space
points. The validity of this strategy will be demonstrated with
results in terms of timing and physics performance for the LVL2
trigger of ATLAS at the LHC, although the strategy is generic and
can be applied to any multi-collision hadron collider experiment.
In addition, the algorithms are conceptually simple, flexible and
robust and hence appropriate for use in demanding, online
environments. We will also make qualitative comparisons with an
alternative, complimentary strategy, based on the use of look-up
tables for handling combinatorics, that has been developed for the
ATLAS LVL2 trigger. These algorithms have been used for the results
that appear in the ATLAS HLT, DAQ and Controls Technical Design
Report, which was recently approved by the LHC Committee.
Primary authors
Dr
D. Emeliyanov
(RAL)
F. PARODI
(INFN Genova, Italy)
Dr
H. Drevermann
(CERN)
Dr
J. Baines
(RAL)
Dr
M. Sutton
(UCL)
Dr
N. Konstantinidis
(UNIVERSITY COLLEGE LONDON)
