Monte Carlo modeling for gamma rays bursts detection monitoring algorithms

Itzhak Orion, Jon Feldman, Yehuda Drorri

Research output: Contribution to journalArticlepeer-review


In this study an efficiency comparison was made for three different monitoring algorithms in order to simulate the response of rotating monitoring systems. Burst-events counting on a spherical surface were simulated as a system, with a one or more detectors located on the center of a sphere. The burst-events direction was randomly changed at steps analogous to the monitoring period and the monitoring was simulated in Monte Carlo calculations for three separate models: In the first model, the random direction, the detection vector was randomly changed after each step using two isotropic distributed random variables. In the second model, the sphere stripping the detection vector was pointed to the upper latitude. The whole sphere was scanned through a full monitoring period. In the second model, the quadrantic stripping, four quadrants were defined for each hemisphere, in the step-by-step completion of the whole segment angular detection vector ranges. This method was set to present an equivalent of a bundled detectors array and has an enhancing monitoring ability. It may be applied on galactic oriented objects, distributed along the galactic sphere Equator. The 106 steps scored events from each of the three algorithms in very similar probabilities. Only after increasing the number of events from 106 to 107, the random model showed an improved scoring algorithm compared to the other two patterned monitoring algorithms. The sphere-stripping algorithm was proven to be 25% more efficient compared to the quadrantic algorithm, and is therefore the preferred patterned monitoring algorithm.

Original languageEnglish
Pages (from-to)1631-1634
Number of pages4
JournalJournal of Applied Sciences
Issue number8
StatePublished - 17 Jul 2006


  • Detectors
  • GRB
  • Gamma rays
  • Modeling
  • Monte Carlo
  • Random
  • X-rays

ASJC Scopus subject areas

  • General


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