Efficient scheme for the preparation of symmetric Dicke states via cross-Kerr nonlinearity

A scheme is proposed for generating maximally entangled Dicke states among four modes. The scheme only uses Kerr medium and homodyne measurements on coherent light fields, which can be efficiently made in quantum optical laboratories. The scheme can be generalized to produce maximally entangled 2k-qubit states.     

Fissility effects on evaporation residue spin distributions

Based on a dynamical Langevin equation coupled with a statistical decay model, we calculate the spin distribution of evaporation residue cross sections of nuclei ¹⁹⁰Os and ²¹⁰Po which have the same neutron-to-proton ratio N/Z$N/Z$ but have a difference in fissility. We find that a large fissility enhances the sensitivity of the residue spin distribution to pre-saddle friction substantially. The results suggest that on the experimental side, to obtain accurate information of pre-saddle dissipation strength by measuring the evaporation residue spin distribution it is optimal to populate among various compound systems with equal N/Z$N/Z$ those with high fissility.     

Quantum game interpretation for a special case of Parrondo’s paradox

By using the discrete Markov chain method, Parrondo’s paradox is studied by means of theoretical analysis and computer simulation, built on the case of game AB played in alternation with modulus M=4. We find that such a case does not have a definite stationary probability distribution and that payoffs of the game depend on the parity of the initial capital. Besides, this paper reveals the phenomenon that “processing in order produces non-deterministic results, while a random process produces deterministic results”. The quantum game method is used in a further study. The results show that the explanation of the game corresponding to a stationary probability distribution is that the probability of the initial capital has reached parity.     

Enhanced Karush–Kuhn–Tucker Conditions for Mathematical Programs with Equilibrium Constraints

In this paper, we study necessary optimality conditions for nonsmooth mathematical programs with equilibrium constraints. We first show that, unlike the smooth case, the mathematical program with equilibrium constraints linear independent constraint qualification is not a constraint qualification for the strong stationary condition when the objective function is nonsmooth. We then focus on the study of the enhanced version of the Mordukhovich stationary condition, which is a weaker optimality condition than the strong stationary condition. We introduce the quasi-normality and several other new constraint qualifications and show that the enhanced Mordukhovich stationary condition holds under them. Finally, we prove that quasi-normality with regularity implies the existence of a local error bound.     

关于整函数超级的进一步结果

运用正规族理论研究了整函数与其高阶导数分担无穷级函数增长级与超级的相关结果.从亚纯函数超级大于零而使球面导数无界的角度出发,然后综合运用Pang-Zaclman引理,数学归纳法和Nevanlinna理论等方法证明了该结果,推广和改进了已有的结果.     

The solution of problems of the stability of three-dimensional convective flows in a closed rectangular cavity by the collocation method

The use of the collocation method, with collocation points at the zeroes of a Chebyshev polynomial, to solve spatial problems of the stability of convective flows, is described. The fluid occupies a closed rectangular cavity on the boundaries of which conditions of the first, second and third kind can be specified. Using a differential matrix constructed at the collocation points, the spectral problem is transformed into an extended eigenvector problem that is solved numerically. The Rayleigh problem in a closed layer is solved for different values of the ratio of the sides of the rectangular cavity. The calculations presented are compared with the results of the solution of non-linear equations and also with the experimental and theoretical data of other authors.     

Global classical solution of the Cauchy problem to 1D compressible Navier–Stokes equations with large initial data

In this paper, we prove that the 1D Cauchy problem of the compressible Navier–Stokes equations admits a unique global classical solution (ρ,u)$(\rho ,\mathrm{u})$ if the viscosity μ(ρ)=1+ρ^β$\mu (\rho )=1+{\rho }^{\beta }$ with β?0$\beta ?0$. The initial data can be arbitrarily large and may contain vacuum. Some new weighted estimates of the density and velocity are obtained when deriving higher order estimates of the solution.     

A Levenberg-Marquardt method with approximate projections

The projected Levenberg-Marquardt method for the solution of a system of equations with convex constraints is known to converge locally quadratically to a possibly nonisolated solution if a certain error bound condition holds. This condition turns out to be quite strong since it implies that the solution sets of the constrained and of the unconstrained system are locally the same. Under a pair of more reasonable error bound conditions this paper proves R-linear convergence of a Levenberg-Marquardt method with approximate projections. In this way, computationally expensive projections can be avoided. The new method is also applicable if there are nonsmooth constraints having subgradients. Moreover, the projected Levenberg-Marquardt method is a special case of the new method and shares its R-linear convergence.     

Solving semi-infinite programs by smoothing projected gradient method

In this paper, we study a semi-infinite programming (SIP) problem with a convex set constraint. Using the value function of the lower level problem, we reformulate SIP problem as a nonsmooth optimization problem. Using the theory of nonsmooth Lagrange multiplier rules and Danskin’s theorem, we present constraint qualifications and necessary optimality conditions. We propose a new numerical method for solving the problem. The novelty of our numerical method is to use the integral entropy function to approximate the value function and then solve SIP by the smoothing projected gradient method. Moreover we study the relationships between the approximating problems and the original SIP problem. We derive error bounds between the integral entropy function and the value function, and between locally optimal solutions of the smoothing problem and those for the original problem. Using certain second order sufficient conditions, we derive some estimates for locally optimal solutions of problem. Numerical experiments show that the algorithm is efficient for solving SIP.