Recently, Tavakoli et al.proposed a self-testing scheme in the prepare-and-measure scenario, showing that self-testing is not necessarily based on entanglement and violation of a Bell inequality [Phys.Rev.A 98 062307(...Recently, Tavakoli et al.proposed a self-testing scheme in the prepare-and-measure scenario, showing that self-testing is not necessarily based on entanglement and violation of a Bell inequality [Phys.Rev.A 98 062307(2018)].They realized the self-testing of preparations and measurements in an N → 1(N ≥ 2) random access code(RAC), and provided robustness bounds in a 2 → 1 RAC.Since all N → 1 RACs with shared randomness are combinations of 2 → 1 and 3 → 1 RACs, the3 → 1 RAC is just as important as the 2 → 1 RAC.In this paper, we find a set of preparations and measurements in the3 → 1 RAC, and use them to complete the robustness self-testing analysis in the prepare-and-measure scenario.The method is robust to small but inevitable experimental errors.展开更多
为实现可用输电能力和电压稳定的双重改善,提出一种考虑风电和负荷随机性的灵活交流输电系统(flexible AC transmission system,FACTS)多目标优化配置方法。首先推导基于拉丁超立方、k-means聚类和蒙特卡洛抽样三者相结合的系统场景生...为实现可用输电能力和电压稳定的双重改善,提出一种考虑风电和负荷随机性的灵活交流输电系统(flexible AC transmission system,FACTS)多目标优化配置方法。首先推导基于拉丁超立方、k-means聚类和蒙特卡洛抽样三者相结合的系统场景生成技术。然后以区域间可用输电能力和电压稳定指标L为目标,建立晶闸管控制串联电容器(thyristor-controlled series capacitor,TCSC)多目标优化配置模型。最后通过增加混沌初始化和变惯性权重设置改进多目标粒子群算法以求解所建模型。基于改进的IEEE30节点系统,对比了最可能发生的系统场景配置TCSC前后的非劣解集和模糊最优解,分析了极端系统场景配置TCSC前后的优化结果。仿真结果表明,所提场景处理方法、多目标优化模型和改进算法在解决相关问题上具有有效性。展开更多
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61572081,61672110,and 61671082)
文摘Recently, Tavakoli et al.proposed a self-testing scheme in the prepare-and-measure scenario, showing that self-testing is not necessarily based on entanglement and violation of a Bell inequality [Phys.Rev.A 98 062307(2018)].They realized the self-testing of preparations and measurements in an N → 1(N ≥ 2) random access code(RAC), and provided robustness bounds in a 2 → 1 RAC.Since all N → 1 RACs with shared randomness are combinations of 2 → 1 and 3 → 1 RACs, the3 → 1 RAC is just as important as the 2 → 1 RAC.In this paper, we find a set of preparations and measurements in the3 → 1 RAC, and use them to complete the robustness self-testing analysis in the prepare-and-measure scenario.The method is robust to small but inevitable experimental errors.
文摘为实现可用输电能力和电压稳定的双重改善,提出一种考虑风电和负荷随机性的灵活交流输电系统(flexible AC transmission system,FACTS)多目标优化配置方法。首先推导基于拉丁超立方、k-means聚类和蒙特卡洛抽样三者相结合的系统场景生成技术。然后以区域间可用输电能力和电压稳定指标L为目标,建立晶闸管控制串联电容器(thyristor-controlled series capacitor,TCSC)多目标优化配置模型。最后通过增加混沌初始化和变惯性权重设置改进多目标粒子群算法以求解所建模型。基于改进的IEEE30节点系统,对比了最可能发生的系统场景配置TCSC前后的非劣解集和模糊最优解,分析了极端系统场景配置TCSC前后的优化结果。仿真结果表明,所提场景处理方法、多目标优化模型和改进算法在解决相关问题上具有有效性。
