U. Bravar

Measurement of the positron to electron ratio in the cosmic rays above 5-GeV

As part of a series of experiments to search for antimatter in cosmic rays, the New Mexico State University balloon-borne magnet spectrometer was configured for a flight to study positrons. Two completely new instruments, a transition radiation detector and a silicon-tungsten imaging calorimeter, were added to the magnet spectrometer. These two detectors provided a proton rejection factor better than 3 × 104. This instrument was flown from Fort Sumner, New Mexico, at an average depth of 4.5 g cm-2 of residual atmosphere for a period of 25 hr. We report here the measured fraction of positrons e+/(e+ + e-) from ~5 to 60 GeV at the top of the atmosphere. Our measurements do not show any compelling evidence for an increase in this ratio with energy, and our results are consistent with a constant fraction of 0.078 ± 0.016 over the entire energy region.

WiZard SiW imaging calorimeter: a preliminary study on its particle identification capability during a balloon flight in 1993

Abstract The WiZard Collaboration is engaged in a program to study the antimatter components of the cosmic rays. A silicon-tungsten (Wiue5f8W) imaging calorimeter has been developed as part of this program. We present its performance and preliminary results, obtained during a balloon flight on September 8, 1993. The flight was dedicated to the measurement of the positron spectrum in the energy range 4–50 GeV and took place from Ft. Sumner, New Mexico.

Identification of cosmic ray electrons and positrons by neural networks

Abstract A data analysis based on artificial neural network classifiers has been done to identify cosmic ray electrons and positrons detected with the balloon-borne NMSU/Wizard-TS93 experiment. The information is provided by two ancillary and independent particle detectors: a transition radiation detector and a silicon-tungsten imaging calorimeter. Electrons and positrons measured during the flight have been identified with background rejection factors of 80 ± 3 and 500 ± 37 at signal efficiencies of 72 ± 3% and 86 ± 2% for the transition radiation detector and silicon-tungsten imaging calorimeter, respectively. The ability of the artificial neural network classifiers to perform a careful multidimensional analysis surpasses the results achieved by conventional methods.