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Stationary Measures of Three-State Quantum Walks with Defect on the One-Dimension Lattice
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作者 Jinling Gao Mingjun Zhang 《Open Journal of Applied Sciences》 CAS 2023年第4期473-482,共10页
In this paper, we focus on the space-inhomogeneous three-state on the one-dimension lattice, a one-phase model and a two-phase model include. By using the transfer matrices method by Endo et al., we calculate the stat... In this paper, we focus on the space-inhomogeneous three-state on the one-dimension lattice, a one-phase model and a two-phase model include. By using the transfer matrices method by Endo et al., we calculate the stationary measure for initial state concrete eigenvalue. Finally we found the transfer matrices method is more effective for the three-state quantum walks than the method obtained by Kawai et al. 展开更多
关键词 Three-State Quantum Walks Stationary Measure One-Phase TWO-PHASE transfer matrices
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EIGENFREQUENCY ANALYSIS OF CABLE STRUCTURES WITH INCLINED CABLES 被引量:1
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作者 William Paulsen Greg Slayton 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 2006年第1期37-49,共13页
The approximate eigenfrequencies for the in-plane vibrations of a cable structure consisting of inclined cables, together with point masses at various points were computed. It was discovered that the classical transfe... The approximate eigenfrequencies for the in-plane vibrations of a cable structure consisting of inclined cables, together with point masses at various points were computed. It was discovered that the classical transfer matrix method was inadequate for this task, and hence the larger exterior matrices were used to determine the eigenfrequency equation. Then predictions of the dynamics of the general cable structure based on the asymptotic estimates of the exterior matrices were made. 展开更多
关键词 EIGENFREQUENCIES transfer matrices exterior matrices cable structures
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Carleman Linearization and Systems of Arbitrary Depth Polynomial Recursions
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作者 Mikołaj Myszkowski 《Advances in Linear Algebra & Matrix Theory》 2022年第1期1-23,共23页
New approach to systems of polynomial recursions is developed based on the Carleman linearization procedure. The article is divided into two main sections: firstly, we focus on the case of uni-variable depth-one polyn... New approach to systems of polynomial recursions is developed based on the Carleman linearization procedure. The article is divided into two main sections: firstly, we focus on the case of uni-variable depth-one polynomial recurrences. Subsequently, the systems of depth-one polynomial recurrence relations are discussed. The corresponding transition matrix is constructed and upper triangularized. Furthermore, the powers of the transition matrix are calculated using the back substitution procedure. The explicit expression for a solution to a broad family of recurrence relations is obtained. We investigate to which recurrences the framework can be applied and construct sufficient conditions for the method to work. It is shown how introduction of auxiliary variables can be used to reduce arbitrary depth systems to the depth-one system of recurrences dealt with earlier. Finally, the limitations of the method are discussed, outlining possible directions for future research. 展开更多
关键词 Polynomial Recursion Carleman Linearization transfer matrices
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Design of ILIDS configurations for droplet characterization 被引量:2
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作者 Marc Brunel Huanhuan Shen 《Particuology》 SCIE EI CAS CSCD 2013年第2期148-157,共10页
Using an original numerical simulator of ILIDS images, we propose and discuss the performances of dif-ferent ILIDS configurations for microscopy, volumic 3D droplet characterization, and fringe frequency calibrations.... Using an original numerical simulator of ILIDS images, we propose and discuss the performances of dif-ferent ILIDS configurations for microscopy, volumic 3D droplet characterization, and fringe frequency calibrations. This exact simulator offers important perspectives in the realization of complete ILIDS instruments and for in situ measurements. 展开更多
关键词 lnterferometric laser imaging for droplet SIZING ABCD transfer matrices
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