Based on platform of three-dimensional particle-in-cell (PIC), CHIPIC, modules of particle swarm optimization (PSO) and genetic algorithm (GA) are designed to optimize a relativistic backward wave oscillator (RBWO), respectively. Comparisons of PSO and GA are implemented in three kinds of parameters of RBWO:Continuous parameter, discrete parameter, and mix parameters. It shows that performances of PSO are better than that of GA. PSO has higher optimization accuracy and convergence rate than GA.

We study photocathode of linear induction accelerator.A photoemission model was implemented which takes into account details such as photocathode material and laser source.A relationship between photocathode and macro particle initial condition is established.We achieved this model in LIAPIC code.A photocathode injector model was set up to simulate photoemission.At last,the model is verified.Simulation results are concordant with experiment.

Mechanism of high-frequency noise in particle-in-cell(PIC) simulation is analysed.An effective finite-difference time-domain(FDTD) method called High_Q FDTD method is developed in which high-frequency noise is filtrated and high quality factor device is calculated with PIC simulation.Formulation of the method is derived on the basis of time-biased and centered-difference FDTD method.Stability and convergence of this method are well analysed.Filter efficiency and calculation precion of this method are compared with those of the time-biased and centered-difference FDTD method in computation of a relativistic backward wave oscillator(RBWO).