Distributed quantum computing (DQC) offers a pathway for scaling up quantum computing architectures beyond the confines of a single chip. Entanglement is a crucial resource for implementing nonlocal operations in DQC, and it is required to allow teleportation of quantum states and gates. Remote entanglement generation in practical systems is probabilistic, has longer duration than that of local operations, and is nondeterministic. Therefore, optimizing the performance of probabilistic remote entanglement generation is critically important for the performance of DQC architectures. In this paper we propose and study a new DQC architecture that combines (1) buffering of successfully generated entanglement, (2) asynchronously attempted entanglement generation, and (3) adaptive scheduling of remote gates based on the entanglement generation pattern. We show that our hardware-software co-design improves both the runtime and the output fidelity under a realistic model of DQC.

In view of epidemic prevention costs and social benefits, an evolutionary game model of epidemic prevention and control strategies between government departments and local people was constructed based on evolutionary game theory to explore the influence of strategic behaviors between government departments and local people, and MATLAB was used to conduct systematic simulation of the game model. Studies have shown that local people will cooperate with government departments when they implement surveillance strategies. Reducing the cost of emergency epidemic prevention, and improving the social benefits of epidemic prevention are conducive to the development of government departments towards the direction of supervision strategy, and local people towards the direction of active epidemic prevention strategy, so as to achieve effective epidemic prevention and control.