Taking the decoherence effect into account, the entanglement evolution of a two-qubit anisotropic Heisenberg XYZ chain in the presence of inhomogeneous magnetic field is investigated. The time evolution of concurrence...Taking the decoherence effect into account, the entanglement evolution of a two-qubit anisotropic Heisenberg XYZ chain in the presence of inhomogeneous magnetic field is investigated. The time evolution of concurrence is studied for the initial state cos θ|01) + sin θ|10) at zero temperature. The influences of inhomogeneous magnetic field, anisotropic parameter and decoherence on entanglement dynamic are addressed in detail, and a concurrence formula of the steady state is found. It is shown that the entanglement sudden death (ESD) and entanglement sudden birth (ESB) appear with the decoherence effect, and the stable concurrence depends on the uniform magnetic field B, anisotropic parameter △ and environment coupling strength γ, which is independent of different initial states and nonuniform magnetic field b.展开更多
The paper considers the problem of representing non-Markovian systems that evolve stochastically over time. It is often necessary to use approximations in the case the system is non-Markovian. Phase type distribution ...The paper considers the problem of representing non-Markovian systems that evolve stochastically over time. It is often necessary to use approximations in the case the system is non-Markovian. Phase type distribution is by now indispensable tool in creation of stochastic system models. The paper suggests a method and software for evaluating stochastic systems approximations by Markov chains with continuous time and countable state space. The performance of a system is described in the event language used for generating the set of states and transition matrix between them. The example of a numerical model is presented.展开更多
To combat the well-known state-space explosion problem in Prop ositional Linear T emp o- ral Logic (PLTL) model checking, a novel algo- rithm capable of translating PLTL formulas into Nondeterministic Automata (NA...To combat the well-known state-space explosion problem in Prop ositional Linear T emp o- ral Logic (PLTL) model checking, a novel algo- rithm capable of translating PLTL formulas into Nondeterministic Automata (NA) in an efficient way is proposed. The algorithm firstly transforms PLTL formulas into their non-free forms, then it further translates the non-free formulas into their Normal Forms (NFs), next constructs Normal Form Graphs (NFGs) for NF formulas, and it fi- nally transforms NFGs into the NA which ac- cepts both finite words and int-mite words. The experimental data show that the new algorithm re- duces the average number of nodes of target NA for a benchmark formula set and selected formulas in the literature, respectively. These results indi- cate that the PLTL model checking technique em- ploying the new algorithm generates a smaller state space in verification of concurrent systems.展开更多
We investigate the identification problems of a class of linear stochastic time-delay systems with unknown delayed states in this study. A time-delay system is expressed as a delay differential equation with a single ...We investigate the identification problems of a class of linear stochastic time-delay systems with unknown delayed states in this study. A time-delay system is expressed as a delay differential equation with a single delay in the state vector. We first derive an equivalent linear time-invariant(LTI) system for the time-delay system using a state augmentation technique. Then a conventional subspace identification method is used to estimate augmented system matrices and Kalman state sequences up to a similarity transformation. To obtain a state-space model for the time-delay system, an alternate convex search(ACS) algorithm is presented to find a similarity transformation that takes the identified augmented system back to a form so that the time-delay system can be recovered. Finally, we reconstruct the Kalman state sequences based on the similarity transformation. The time-delay system matrices under the same state-space basis can be recovered from the Kalman state sequences and input-output data by solving two least squares problems. Numerical examples are to show the effectiveness of the proposed method.展开更多
基金Supported by National Natural Science Foundation of China under Grant No.10904033Natural Science Foundation of Hubei Province under Grant No.2009CDA145+1 种基金Educational Commission of Hubei Province under Grant No.D20092204Natural Science Foundation of Hubei Normal University under Grant No.2007D21
文摘Taking the decoherence effect into account, the entanglement evolution of a two-qubit anisotropic Heisenberg XYZ chain in the presence of inhomogeneous magnetic field is investigated. The time evolution of concurrence is studied for the initial state cos θ|01) + sin θ|10) at zero temperature. The influences of inhomogeneous magnetic field, anisotropic parameter and decoherence on entanglement dynamic are addressed in detail, and a concurrence formula of the steady state is found. It is shown that the entanglement sudden death (ESD) and entanglement sudden birth (ESB) appear with the decoherence effect, and the stable concurrence depends on the uniform magnetic field B, anisotropic parameter △ and environment coupling strength γ, which is independent of different initial states and nonuniform magnetic field b.
文摘The paper considers the problem of representing non-Markovian systems that evolve stochastically over time. It is often necessary to use approximations in the case the system is non-Markovian. Phase type distribution is by now indispensable tool in creation of stochastic system models. The paper suggests a method and software for evaluating stochastic systems approximations by Markov chains with continuous time and countable state space. The performance of a system is described in the event language used for generating the set of states and transition matrix between them. The example of a numerical model is presented.
基金The first author of this paper would like to thank the follow- ing scholars, Prof. Joseph Sifakis, 2007 Turing Award Winner, for his invaluable help with my research and Dr. Kevin Lu at Brunel University, UK for his excellent suggestions on this paper. This work was supported by the National Natural Sci- ence Foundation of China under Grant No.61003079 the Chi- na Postdoctoral Science Foundation under Grant No. 2012M511588.
文摘To combat the well-known state-space explosion problem in Prop ositional Linear T emp o- ral Logic (PLTL) model checking, a novel algo- rithm capable of translating PLTL formulas into Nondeterministic Automata (NA) in an efficient way is proposed. The algorithm firstly transforms PLTL formulas into their non-free forms, then it further translates the non-free formulas into their Normal Forms (NFs), next constructs Normal Form Graphs (NFGs) for NF formulas, and it fi- nally transforms NFGs into the NA which ac- cepts both finite words and int-mite words. The experimental data show that the new algorithm re- duces the average number of nodes of target NA for a benchmark formula set and selected formulas in the literature, respectively. These results indi- cate that the PLTL model checking technique em- ploying the new algorithm generates a smaller state space in verification of concurrent systems.
文摘We investigate the identification problems of a class of linear stochastic time-delay systems with unknown delayed states in this study. A time-delay system is expressed as a delay differential equation with a single delay in the state vector. We first derive an equivalent linear time-invariant(LTI) system for the time-delay system using a state augmentation technique. Then a conventional subspace identification method is used to estimate augmented system matrices and Kalman state sequences up to a similarity transformation. To obtain a state-space model for the time-delay system, an alternate convex search(ACS) algorithm is presented to find a similarity transformation that takes the identified augmented system back to a form so that the time-delay system can be recovered. Finally, we reconstruct the Kalman state sequences based on the similarity transformation. The time-delay system matrices under the same state-space basis can be recovered from the Kalman state sequences and input-output data by solving two least squares problems. Numerical examples are to show the effectiveness of the proposed method.