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We estimate the hardness factors and the equivalent 1 MeV neutron fluences for hadrons fluences expected at the GaAs positions wheels in the ATLAS Inner Detector. On this basis the degradation of the GaAs particle detectors made from different substrates as a function of years LHC operation is predicted.

To investigate the trapping and detrapping in SI-GaAs particle detectors we analyzed the signals caused by 5.48 MeV alpha particles with a charge sensitive preamplifier. From the bias and temperature dependence of these signals we determine the activation energies of two electron traps. Additional simulation and measurements of the lifetime as a function of resistivity have shown that the EL2 + is the dominant electron trap in semi-insulating GaAs.

We develop a genetic algorithm (GA) optimization method and use it in the design of a refractive-beam profile-shaping system. In this application, we employ the GA to determine the shape of one surface of the primary beam profile-shaping element in our system. The GA is instructed to vary the shape of this surface such that the output intensity profile is flat on a spherical surface some distance away. The GA does this while insuring that only a specified area of the output surface is illuminated. The calculation of the intensity profile is based on geometrical optics and is accomplished exclusively through ray tracing, giving this method broad applicability.

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