The non-Gaussianity of quantum states incarnates an important resource for improving the performance of continuous-variable quantum information protocols.We propose a novel criterion of non-Gaussianity for single-mode...The non-Gaussianity of quantum states incarnates an important resource for improving the performance of continuous-variable quantum information protocols.We propose a novel criterion of non-Gaussianity for single-mode rotationally symmetric quantum states via the squared Frobenius norm of higher-order cumulant matrix for the quadrature distribution function.As an application,we study the non-Gaussianities of three classes of single-mode symmetric non-Gaussian states:a mixture of vacuum and Fock states,single-photon added thermal states,and even/odd Schr¨odinger cat states.It is shown that such a criterion is faithful and effective for revealing non-Gaussianity.We further extend this criterion to two cases of symmetric multi-mode non-Gaussian states and non-symmetric single-mode non-Gaussian states.展开更多
Dominance is an underlying concept in decision making that is used to develop a method to obtain the derived weight. The eigenvector method (EM) [3] is favored because it captures dominance at the level of toler...Dominance is an underlying concept in decision making that is used to develop a method to obtain the derived weight. The eigenvector method (EM) [3] is favored because it captures dominance at the level of tolerated inconsistency, the least included angles method (LAM) [1] minimizes error without an explict attempt to capture dominance, but with simplicity and practicality. This paper puts forward a new priority method——the least included angles method with mean cumulative dominance (DLAM) combining the good characteristics of EM and LAM. Compared with the EM, the LAM, the GMDM and the AMDM, the DLAM is a simpler, practical and more rational method in calculating the weight vectors of judgement matrices. The results of the numerical example also show that the DLAM and the EM always derive the same rankings, the other methods such as the LAM, the logarithmic least squares method (LLSM), the GMDM and the AMDM are possible to obtain the rankings, which are different from those derived by the DLAM and the EM.展开更多
It is a pioneering work to use a Markov chain model to study the pedestrian escape route without visibility.In this paper,based on the Markov chain probability transition matrix,the algorithms with random numbers and ...It is a pioneering work to use a Markov chain model to study the pedestrian escape route without visibility.In this paper,based on the Markov chain probability transition matrix,the algorithms with random numbers and the spatial-grid,an escape route in a limited invisible space is obtained.Six pace states(standing,crawling,walking,leaping,jogging,and running)are applied to describe the characteristics of pedestrian behaviors.Besides,eight main direction changes are used to describe the transition characteristic of a pedestrian.At the same time,this paper analyzes the escape route from two views,i.e.,pedestrian pace states and directions.The research results show that the Markov chain model is more realistic as a means of studying pedestrian escape routes.展开更多
基金Project supported by the Natural Science Foundation of Hunan Province of China(Grant No.2021JJ30535)。
文摘The non-Gaussianity of quantum states incarnates an important resource for improving the performance of continuous-variable quantum information protocols.We propose a novel criterion of non-Gaussianity for single-mode rotationally symmetric quantum states via the squared Frobenius norm of higher-order cumulant matrix for the quadrature distribution function.As an application,we study the non-Gaussianities of three classes of single-mode symmetric non-Gaussian states:a mixture of vacuum and Fock states,single-photon added thermal states,and even/odd Schr¨odinger cat states.It is shown that such a criterion is faithful and effective for revealing non-Gaussianity.We further extend this criterion to two cases of symmetric multi-mode non-Gaussian states and non-symmetric single-mode non-Gaussian states.
基金Research supported by National Science Foundation of China
文摘Dominance is an underlying concept in decision making that is used to develop a method to obtain the derived weight. The eigenvector method (EM) [3] is favored because it captures dominance at the level of tolerated inconsistency, the least included angles method (LAM) [1] minimizes error without an explict attempt to capture dominance, but with simplicity and practicality. This paper puts forward a new priority method——the least included angles method with mean cumulative dominance (DLAM) combining the good characteristics of EM and LAM. Compared with the EM, the LAM, the GMDM and the AMDM, the DLAM is a simpler, practical and more rational method in calculating the weight vectors of judgement matrices. The results of the numerical example also show that the DLAM and the EM always derive the same rankings, the other methods such as the LAM, the logarithmic least squares method (LLSM), the GMDM and the AMDM are possible to obtain the rankings, which are different from those derived by the DLAM and the EM.
基金supported by the National Natural Science Foundation of China(Grant No.70502006)the Program for a New Century of Excellent University Talents,Ministry of Education of the People’s Republic of China(No.NCET-07-0056).
文摘It is a pioneering work to use a Markov chain model to study the pedestrian escape route without visibility.In this paper,based on the Markov chain probability transition matrix,the algorithms with random numbers and the spatial-grid,an escape route in a limited invisible space is obtained.Six pace states(standing,crawling,walking,leaping,jogging,and running)are applied to describe the characteristics of pedestrian behaviors.Besides,eight main direction changes are used to describe the transition characteristic of a pedestrian.At the same time,this paper analyzes the escape route from two views,i.e.,pedestrian pace states and directions.The research results show that the Markov chain model is more realistic as a means of studying pedestrian escape routes.
