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A novel in situ trigger combination method

By A Buzatu, A Warburton, N Krumnack and WM Yao


Searches for rare physics processes using particle detectors in high-luminosity colliding hadronic beam environments require the use of multi-level trigger systems to reject colossal background rates in real time. In analyses like the search for the Higgs boson, there is a need to maximize the signal acceptance by combining multiple different trigger chains when forming the offline data sample. In such statistically limited searches, datasets are often amassed over periods of several years, during which the trigger characteristics evolve and system performance can vary significantly. Reliable production cross-section measurements and upper limits must take into account a detailed understanding of the effective trigger inefficiency for every selected candidate event. We present as an example the complex situation of three trigger chains, based on missing energy and jet energy, that were combined in the context of the search for the Higgs (H) boson produced in association with a W boson at the Collider Detector at Fermilab (CDF). We briefly review the existing techniques for combining triggers, namely the inclusion, division, and exclusion methods. We introduce and describe a novel fourth in situ method whereby, for each candidate event, only the trigger chain with the highest a priori probability of selecting the event is considered. We compare the inclusion and novel in situ methods for signal event yields in the CDF WH search. This new combination method, by virtue of its scalability to large numbers of differing trigger chains and insensitivity to correlations between triggers, will benefit future long-running collider experiments, including those currently operating on the Large Hadron Collider. © 2013 Elsevier B.V

Topics: Nuclear & Particles Physics, Atomic, Molecular, Nuclear, Particle and Plasma Physics, Other Physical Sciences, Astronomical and Space Sciences, Atomic, Molecular, Nuclear, Particle and Plasma Physics
Publisher: eScholarship, University of California
Year: 2013
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