Magnetic field configurations of radio jets in the double source of radio galaxy

As an improvement of resolution of observations, more and more radio galaxies with radiojets have been identified and many fine structures in the radio jets yielded. In the presentpaper, the two-dimensional magnetohydrodynamical theory is applied to the analysis of themagnetic field configurations in the radio jefs. Two-dimensional results not only are con-sistent theoretically, but also explain the fine structures of observations. One of the theo-retical models is discussed in detail, and is in good agreement as compared with the observedradio jets of NGC6251. The results of the present paper also show that the magneticfields in the radio jets are mainly longitudinal ones and associate with the double sources ofQSOs if the magnetic field of the central object is stronger; the fields in the radio jets aremainly transverse ones and associate with the double sources of radio galaxies if the fieldof the central object is weaker. The magnetic field has great influence on the morphol-ogy and dynamic process.

The magnetic jet theory of double source in radio galaxy

The two-dimensional accelerating theory about solar wind is applied to the study of theaccelerating process of jet beam in the radio galaxy. The flowing features are given with theanalytic method, and the basic flow is along the direction of the jet beam. The mechanism ofacceleration from subsonic to supersonic flow is discussed. At the same time, some fine struc-tures about the double sources in the radio galaxy are explained.

Scenario Cluster Lagrangian Decomposition in two stage stochastic mixed 0-1 optimization

In this paper we introduce four scenario Cluster based Lagrangian Decomposition (CLD) procedures for obtaining strong lower bounds to the (optimal) solution value of two-stage stochastic mixed 0-1 problems. At each iteration of the Lagrangian based procedures, the traditional aim consists of obtaining the solution value of the corresponding Lagrangian dual via solving scenario submodels once the nonanticipativity constraints have been dualized. Instead of considering a splitting variable representation over the set of scenarios, we propose to decompose the model into a set of scenario clusters. We compare the computational performance of the four Lagrange multiplier updating procedures, namely the Subgradient Method, the Volume Algorithm, the Progressive Hedging Algorithm and the Dynamic Constrained Cutting Plane scheme for different numbers of scenario clusters and different dimensions of the original problem. Our computational experience shows that the CLD bound and its computational effort depend on the number of scenario clusters to consider. In any case, our results show that the CLD procedures outperform the traditional LD scheme for single scenarios both in the quality of the bounds and computational effort. All the procedures have been implemented in a C++ experimental code. A broad computational experience is reported on a test of randomly generated instances by using the MIP solvers COIN-OR and CPLEX for the auxiliary mixed 0-1 cluster submodels, this last solver within the open source engine COIN-OR. We also give computational evidence of the model tightening effect that the preprocessing techniques, cut generation and appending and parallel computing tools have in stochastic integer optimization. Finally, we have observed that the plain use of both solvers does not provide the optimal solution of the instances included in the testbed with which we have experimented but for two toy instances in affordable elapsed time. On the other hand the proposed procedures provide strong lower bounds (or the same solution value) in a considerably shorter elapsed time for the quasi-optimal solution obtained by other means for the original stochastic problem.