Improving Parameter Optimization in Decoy-State Quantum Key Distribution

Quantum key distribution (QKD) enables two remote users to share a string of bits with information-theoretical security. Parameter optimization is crucial step in achieving optimal performance practical QKD systems. In general, such implemented using local search algorithm (LSA). However, LSAs inevitably fail find out the values when searched rate function nonconvex or has discontinuity first-order derivatives and narrow parameter space. This paper proposes genetic algorithm-based method overcome limitations for optimization. We tested proposed various types common protocols found that it very high time consumption comparable standard LSA. expect our be valuable tool quantum information processing tasks.