Abstract
A soft computing tool, Genetic Algorithm, is employed here to determine the optimized system parameters of GaAs quantum wells for better high-frequency performance under hot electron condition. For a particular DC biasing field, it is possible to predict the optimum values of the system parameters, like electron temperature, channel width, carrier concentration, for realizing a particular high-frequency response characterized by a cutoff frequency, a frequency at which AC mobility falls to 0.707 of its low-frequency value. The cutoff frequency decreases with the rise of both the channel width and the carrier concentration, whereas it enhances with the increase of lattice temperature and is found to be higher at higher DC biasing fields.
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