Monte Carlo simulations of the timing structure of Cherenkov wavefronts of sub-100 GeV gamma ray air showers
- DePauw University, Greencastle, Indiana 46135 (United States)
- Purdue University, W.Lafayette, Indiana 47907 (United States)
We present a Monte-Carlo study of the phenomenology of Cherenkov light wavefronts from low energy gamma ray induced air showers. Experimentally the measurements of the spatially distributed arrival times of the wavefronts of the Cherenkov light of gamma ray air showers have been used to extract the directions of the showers. This has mainly been done for >500 GeV showers using a conical fit to the timing structure of the wavefront. This directionality is then used to contribute to the rejection of background showers (mainly hadron induced showers) which arrive isotropically. Investigation of the arrival times of simulated Cherenkov photons from gamma ray induced air showers of energies 100 GeV and below reveals that there is greater variation in the morphology of the wavefronts than at the higher energies and that the fitting of simple conical functions to determine arrival directions may no longer be appropriate. We demonstrate that the detailed structure of the wavefront of these low energy gamma ray showers is primarily determined by the height distribution of the emitting cascade particles. Preliminary work suggests a correlation between the shape of the wavefront and the height of shower-maximum.
- OSTI ID:
- 21172427
- Journal Information:
- AIP Conference Proceedings, Vol. 410, Issue 1; Conference: 4. Compton symposium, Williamsburg, VA (United States), 27-30 Apr 1997; Other Information: DOI: 10.1063/1.54021; (c) 1997 American Institute of Physics; Country of input: International Atomic Energy Agency (IAEA); ISSN 0094-243X
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
CHERENKOV RADIATION
COMPUTERIZED SIMULATION
CORRELATIONS
COSMIC GAMMA SOURCES
COSMIC PHOTONS
EXTENSIVE AIR SHOWERS
GAMMA DETECTION
GAMMA RADIATION
GAMMA SPECTRA
GEV RANGE
HADRONS
MONTE CARLO METHOD
PARTICLE DISCRIMINATION
SPATIAL DISTRIBUTION
TIME DEPENDENCE
VARIATIONS