本文主要研究了在非马尔可夫环境下在时变磁场中具有各种参数的交互作用非常丰富的两个比特的海森堡XYZ模型的量子稠密编码的性质。通过量子态扩散方法Quantum State Diffusion Method(QSD)模拟了信道容量χ随时间的演化关系。经过数值...本文主要研究了在非马尔可夫环境下在时变磁场中具有各种参数的交互作用非常丰富的两个比特的海森堡XYZ模型的量子稠密编码的性质。通过量子态扩散方法Quantum State Diffusion Method(QSD)模拟了信道容量χ随时间的演化关系。经过数值模拟显示:量子稠密编码对环境关联系数γ、耦合系数J和Jz以及余弦磁场的强度B都有依赖。当环境关联系数γ变小时也就是非马尔科夫特性增加时,量子稠密编码的信道容量χ明显呈现上升趋势。在这里值得提出的是较小的耦合系数Jz、较大的耦合系数J、和较强的时变磁场强度B对于在本系统下进行有效的量子稠密编码是非常有用的,其中在非马尔科夫情形下非常明显,这对能够有效地进行信息传输非常的重要。展开更多
A quantum key distribution protocol, based on the quantum dense encoding in entangled states, is presented. In this protocol, we introduce an encoding process to encode two classical bits information into one of the f...A quantum key distribution protocol, based on the quantum dense encoding in entangled states, is presented. In this protocol, we introduce an encoding process to encode two classical bits information into one of the four one-qubit unitary operations implemented by Alice and the Bell states measurement implemented by Bob in stead of direct measuring the previously shared Einstein-Podolsky-Rosen pairs by both of the distant parties, Alice and Bob.Considering the practical application we can get the conclusion that our protocol has some advantages. It not only simplifies the measurement which may induce potential errors, but also improves the effectively transmitted rate of the generated qubits by the raw key. Here we also discuss eavesdropping attacks against the scheme and the channel loss.展开更多
A new method for interaction recognition based on sparse representation of feature covariance matrices was presented.Firstly,the dense trajectories(DT)extracted from the video were clustered into different groups to e...A new method for interaction recognition based on sparse representation of feature covariance matrices was presented.Firstly,the dense trajectories(DT)extracted from the video were clustered into different groups to eliminate the irrelevant trajectories,which could greatly reduce the noise influence on feature extraction.Then,the trajectory tunnels were characterized by means of feature covariance matrices.In this way,the discriminative descriptors could be extracted,which was also an effective solution to the problem that the description of the feature second-order statistics is insufficient.After that,an over-complete dictionary was learned with the descriptors and all the descriptors were encoded using sparse coding(SC).Classification was achieved using multiple instance learning(MIL),which was more suitable for complex environments.The proposed method was tested and evaluated on the WEB Interaction dataset and the UT interaction dataset.The experimental results demonstrated the superior efficiency.展开更多
文摘本文主要研究了在非马尔可夫环境下在时变磁场中具有各种参数的交互作用非常丰富的两个比特的海森堡XYZ模型的量子稠密编码的性质。通过量子态扩散方法Quantum State Diffusion Method(QSD)模拟了信道容量χ随时间的演化关系。经过数值模拟显示:量子稠密编码对环境关联系数γ、耦合系数J和Jz以及余弦磁场的强度B都有依赖。当环境关联系数γ变小时也就是非马尔科夫特性增加时,量子稠密编码的信道容量χ明显呈现上升趋势。在这里值得提出的是较小的耦合系数Jz、较大的耦合系数J、和较强的时变磁场强度B对于在本系统下进行有效的量子稠密编码是非常有用的,其中在非马尔科夫情形下非常明显,这对能够有效地进行信息传输非常的重要。
文摘A quantum key distribution protocol, based on the quantum dense encoding in entangled states, is presented. In this protocol, we introduce an encoding process to encode two classical bits information into one of the four one-qubit unitary operations implemented by Alice and the Bell states measurement implemented by Bob in stead of direct measuring the previously shared Einstein-Podolsky-Rosen pairs by both of the distant parties, Alice and Bob.Considering the practical application we can get the conclusion that our protocol has some advantages. It not only simplifies the measurement which may induce potential errors, but also improves the effectively transmitted rate of the generated qubits by the raw key. Here we also discuss eavesdropping attacks against the scheme and the channel loss.
基金Project(51678075) supported by the National Natural Science Foundation of ChinaProject(2017GK2271) supported by the Science and Technology Project of Hunan Province,China
文摘A new method for interaction recognition based on sparse representation of feature covariance matrices was presented.Firstly,the dense trajectories(DT)extracted from the video were clustered into different groups to eliminate the irrelevant trajectories,which could greatly reduce the noise influence on feature extraction.Then,the trajectory tunnels were characterized by means of feature covariance matrices.In this way,the discriminative descriptors could be extracted,which was also an effective solution to the problem that the description of the feature second-order statistics is insufficient.After that,an over-complete dictionary was learned with the descriptors and all the descriptors were encoded using sparse coding(SC).Classification was achieved using multiple instance learning(MIL),which was more suitable for complex environments.The proposed method was tested and evaluated on the WEB Interaction dataset and the UT interaction dataset.The experimental results demonstrated the superior efficiency.
