We investigate the teleportation of an entangled state via a couple of quantum channels, which are composed of a spin-1/2 Heisenberg dimer in two infinite Ising–Heisenberg chains. The heterotrimetallic coordination p...We investigate the teleportation of an entangled state via a couple of quantum channels, which are composed of a spin-1/2 Heisenberg dimer in two infinite Ising–Heisenberg chains. The heterotrimetallic coordination polymer CuⅡMnⅡ(L1)][FeⅢ(bpb)(CN)2]·ClO4·H2O(abbreviated as Fe–Mn–Cu) can be regarded as an actual material for this chain.We apply the transfer-matrix approach to obtain the density operator for the Heisenberg dimer and use the standard teleportation protocol to derive the analytical expression of the density matrix of the output state and the average fidelity of the entanglement teleportation. We study the effects of the temperature T, anisotropy coupling parameter △, Heisenberg coupling parameter J2 and external magnetic field h on the quantum channels. The results show that anisotropy coupling? and Heisenberg coupling J2 can favor the generation of the output concurrence and expand the scope of the successful average fidelity.展开更多
We investigate the effect of impurities on the thermal entanglement in a spin-1/2 Ising-Heisenberg butterfly-shaped chain,where four interstitial Heisenberg spins are localized on the vertices of a rectangular plaquet...We investigate the effect of impurities on the thermal entanglement in a spin-1/2 Ising-Heisenberg butterfly-shaped chain,where four interstitial Heisenberg spins are localized on the vertices of a rectangular plaquette in a unit block.By using the transfer-matrix approach,we numerically calculate the partition function and the reduced density matrix of this model.The bipartite thermal entanglement between different Heisenberg spin pairs is quantified by the concurrence.We also discuss the fluctuations caused by the impurities through the uniform distribution and the Gaussian distribution.Considering the effects of the external magnetic field,temperature,Heisenberg and Ising interactions as well as the parameter of anisotropy on the thermal entanglement,our results show that comparing with the case of the clean model,in both the twoimpurity model and the impurity fluctuation model the entanglement is more robust within a certain range of anisotropic parameters and the region of the magnetic field where the entanglement occurred is also larger.展开更多
With the assistance of the identified/associated sources in the second Fermi Large Area Telescope （LAT） catalog, we analyze and resolve the spatial distribution and the distributions of the gamma-ray spectral and va...With the assistance of the identified/associated sources in the second Fermi Large Area Telescope （LAT） catalog, we analyze and resolve the spatial distribution and the distributions of the gamma-ray spectral and variability indices of the remaining 575 unassociated Fermi LAT sources. Consequently, it is suggested that the unassociated sources could statistically consist of Galactic supernova remnants/pulsar wind nebulae, BL Lacertae objects, fiat spectrum radio quasars and other types of active galaxies with fractions of 25%, 29%, 41% and 5%, respectively.展开更多
Prognosis of bearing is critical to improve the safety,reliability,and availability of machinery systems,which provides the health condition assessment and determines how long the machine would work before failure occ...Prognosis of bearing is critical to improve the safety,reliability,and availability of machinery systems,which provides the health condition assessment and determines how long the machine would work before failure occurs by predicting the remaining useful life(RUL).In order to overcome the drawback of pure data-driven methods and predict RUL accurately,a novel physics-informed deep neural network,named degradation consistency recurrent neural network,is proposed for RUL prediction by integrating the natural degradation knowledge of mechanical components.The degradation is monotonic over the whole life of bearings,which is characterized by temperature signals.To incorporate the knowledge of monotonic degradation,a positive increment recurrence relationship is introduced to keep the monotonicity.Thus,the proposed model is relatively well understood and capable to keep the learning process consistent with physical degradation.The effectiveness and merit of the RUL prediction using the proposed method are demonstrated through vibration signals collected from a set of run-to-failure tests.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.11274102)the New Century Excellent Talents in University of Ministry of Education of China(Grant No.NCET-11-0960)the Specialized Research Fund for the Doctoral Program of Higher Education of China(Grant No.20134208110001)
文摘We investigate the teleportation of an entangled state via a couple of quantum channels, which are composed of a spin-1/2 Heisenberg dimer in two infinite Ising–Heisenberg chains. The heterotrimetallic coordination polymer CuⅡMnⅡ(L1)][FeⅢ(bpb)(CN)2]·ClO4·H2O(abbreviated as Fe–Mn–Cu) can be regarded as an actual material for this chain.We apply the transfer-matrix approach to obtain the density operator for the Heisenberg dimer and use the standard teleportation protocol to derive the analytical expression of the density matrix of the output state and the average fidelity of the entanglement teleportation. We study the effects of the temperature T, anisotropy coupling parameter △, Heisenberg coupling parameter J2 and external magnetic field h on the quantum channels. The results show that anisotropy coupling? and Heisenberg coupling J2 can favor the generation of the output concurrence and expand the scope of the successful average fidelity.
基金Project supported by the National Natural Science Foundation of China(Grant No.12074101)the Science Fund for the New Century Excellent Talents in University of the Ministry of Education of China(Grant No.NCET-11-0960)the Specialized Research Fund for the Doctoral Program of Higher Education of China(Grant No.20134208110001).
文摘We investigate the effect of impurities on the thermal entanglement in a spin-1/2 Ising-Heisenberg butterfly-shaped chain,where four interstitial Heisenberg spins are localized on the vertices of a rectangular plaquette in a unit block.By using the transfer-matrix approach,we numerically calculate the partition function and the reduced density matrix of this model.The bipartite thermal entanglement between different Heisenberg spin pairs is quantified by the concurrence.We also discuss the fluctuations caused by the impurities through the uniform distribution and the Gaussian distribution.Considering the effects of the external magnetic field,temperature,Heisenberg and Ising interactions as well as the parameter of anisotropy on the thermal entanglement,our results show that comparing with the case of the clean model,in both the twoimpurity model and the impurity fluctuation model the entanglement is more robust within a certain range of anisotropic parameters and the region of the magnetic field where the entanglement occurred is also larger.
基金supported by the National Natural Science Foundation of China (Grant No. 11103004)the Foundation for the Authors of National Excellent Doctoral Dissertations of China (Grant No. 201225)
文摘With the assistance of the identified/associated sources in the second Fermi Large Area Telescope （LAT） catalog, we analyze and resolve the spatial distribution and the distributions of the gamma-ray spectral and variability indices of the remaining 575 unassociated Fermi LAT sources. Consequently, it is suggested that the unassociated sources could statistically consist of Galactic supernova remnants/pulsar wind nebulae, BL Lacertae objects, fiat spectrum radio quasars and other types of active galaxies with fractions of 25%, 29%, 41% and 5%, respectively.
基金support in part by China Postdoctoral Science Foundation (No.2021M702634)National Science Foundation of China (No.52175116).
文摘Prognosis of bearing is critical to improve the safety,reliability,and availability of machinery systems,which provides the health condition assessment and determines how long the machine would work before failure occurs by predicting the remaining useful life(RUL).In order to overcome the drawback of pure data-driven methods and predict RUL accurately,a novel physics-informed deep neural network,named degradation consistency recurrent neural network,is proposed for RUL prediction by integrating the natural degradation knowledge of mechanical components.The degradation is monotonic over the whole life of bearings,which is characterized by temperature signals.To incorporate the knowledge of monotonic degradation,a positive increment recurrence relationship is introduced to keep the monotonicity.Thus,the proposed model is relatively well understood and capable to keep the learning process consistent with physical degradation.The effectiveness and merit of the RUL prediction using the proposed method are demonstrated through vibration signals collected from a set of run-to-failure tests.
