在分析系统和环境的相互作用的基础上,首先研究了主方程模型描述的开放量子系统的随机动力学特征,得到了表征系统消相干因素的Lindblad算符和描述系统量子态演化规律的量子随机微分方程;然后根据微分方程的形式,采用了一种迭代算法,实现了表征系统演化特征的约化密度算符的数值模拟,并给出一个卖例,与经典Runge-Kutta迭代算法的比较,验证了其实用性和优越性;最后分析了仿真算法的收敛性.
The quantum stochastic differential equation derived from the Lindblad form quantum master equation was investigated. The general formulation in terms of environment operators representing the quantum state diffusion was given. The constructive decoherenee Lindblads' compact on the evolution ant the dynamics of the system including drift and dissipation was analyzed separately. The numerical simulation algorithm of stochastic process of direct photodetection of a driven two-level system on a high performance computer for the predictions of the dynamical behavior is provided and compared with the classical Runge-Kutta algorithm to verify its effectiveness, followed by further discussions on the convergence of the algorithm.