Determination of Semiconductor Diode Parameters Using Multi-Objective Quantum-Inspired Particle Swarm Optimization Algorithm

In this paper, we present an innovative approach to accurately extract the device parameters of a semiconductor p-n junction diode using a Multi-Objective Quantum-Inspired Particle Swarm Optimization (MOQIPSO) algorithm. Semiconductor diodes are integral to modern electronics, and their accurate modeling is critical for device performance prediction and simulation. We propose a multi-objective optimization framework that leverages both the quantum-inspired principles and the swarm intelligence of PSO to extract parameters such as the reverse saturation current and the diode ideality factor. The effectiveness of our proposed methodology is validated through experimental simulations performed using MATLAB and python on several diode models, where the MOQIPSO algorithm demonstrated excellent performance and convergence at low number of iterations.