A parameter reconstruction method for the physical parameters of fiber Bragg grating (FBG) based on quantum particle swarm optimization (QPSO) is proposed. In the proposed method, the objective function is constructed according to the transfer matrix theory, the physical parameters of fiber gratings are represented in the form of particle, and the optimized parameters are obtained by the particles′ searching in the solution space according to the quantum behavior. When compared with genetic algorithm (GA) and particle swarm optimization (PSO), the proposed QPSO-based method simulates the quantum behavior, which leads to a better convergence performance and a better static-state performance. The simulation results show that, for both uniform and nonuniform fiber grating evolving 100 or 200 times, the proposed method has the reconstruction parameter error of less than 0.5% when the swarm population is 40.