Minimum length Pb/SCIN detector for efficient cosmic ray identification

Details Minimum length Pb/SCIN detector for efficient cosmic ray identification Minimum length Pb/SCIN detector for efficient cosmic ray identification

Sep 1989

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1989asee.nasa...26s&link_type=abstract

In Maryland Univ., The 1989 NASA-ASEE Summer Faculty Fellowship Program in Aeronautics and Research p 26 (SEE N91-25914 17-82)

Computer Science

Performance

Aerospace Environments, Cosmic Ray Showers, Cosmic Rays, Mathematical Models, Monte Carlo Method, Muons, Particle Interactions, Pions, Positrons, Protons, Statistical Analysis, Calorimeters, Halos, Libraries

Scientific paper

A study was made of the performance of a minimal length cosmic ray shower detector that would be light enough for space flight and would provide efficient identification of positions and protons. Cosmic ray positions are mainly produced in the decay chain of: Pion yields Muon yields Positron and they provide a measure of the matter density traversed by primary protons. Present positron flux measurements are consistent with the Leaky Box and Halo models for sources of cosmic rays. Abundant protons in the space environment are a significant source of background that would wash out the positron signal. Protons and positrons produced very distictive showers of particles when they enter matter; many studies have been published on their behavior on large calorimeter detectors. The challenge is to determine the minimal material necessary (minimal calorimeter depth) for positive particles identification. The primary instrument for the investigation is the Monte Carlo code GEANT, a library of programs from CERN that can be used to model experimental geometry, detector responses and particle interaction processes. The use of the Monte Carlo approach is crucial since statistical fluctuations in shower shape are significant. Studies conducted during the 1988 summer program showed that straightforward approaches to the problem achieved 85 to 90 percent correct identification, but left a residue of 10 to 15 percent misidentified particles. This percentage improved to a few percent when multiple shower-cut criteria were applied to the data. This summer, the same study was extended to employ several physical and statistical methods of identifying response of the calorimeter and the efficiency of the optimal shower cuts to off-normal incidence particle was determined.

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