Analysis of (K^-,K^+) inclusive spectrum with semiclassical distorted wave model

The inclusive K^+ momentum spectrum in the 12C(K^-,K^+) reaction is calculated by the semiclassical distorted wave (SCDW) model, including the transition to the \Xi^- bound state. The calculated spectra with the strength of the \Xi^--nucleus potential -50, -20, and +10 MeV are compared with the experimental data measured at KEK with p_{K^-}=1.65 GeV/c. The shape of the spectrum is reproduced by the calculation. Though the inclusive spectrum changes systematically depending on the potential strength, it is not possible to obtain a constraint on the potential from the present data. The calculated spectrum is found to have strong emission-angle dependence. We also investigate the incident K^- momentum dependence of the spectrum to see the effect of the Fermi motion of the target nucleons which is explicitly treated in the SCDW method.Comment: 7 pages, 5 figure

New Approach for Evaluating Incomplete and Complete Fusion Cross Sections with Continuum-Discretized Coupled-Channels Method

We propose a new method for evaluating incomplete and complete fusion cross sections separately using the Continuum-Discretized Coupled-Channels method. This method is applied to analysis of the deuteron induced reaction on a 7Li target up to 50 MeV of the deuteron incident energy. Effects of deuteron breakup on this reaction are explicitly taken into account. Results of the method are compared with those of the Glauber model, and the difference between the two is discussed. It is found that the energy dependence of the incomplete fusion cross sections obtained by the present calculation is almost the same as that obtained by the Glauber model, while for the complete fusion cross section, the two models give markedly different energy dependence. We show also that a prescription for evaluating incomplete fusion cross sections proposed in a previous study gives much smaller result than an experimental value.Comment: 10 pages, 5 figure

Discussion on the progress and future of satellite communication (Japan)

The current status of communications satellite development in Japan is presented. It is shown that beginning with research on satellite communucations in the late 1950's, progress was made in the areas of communications, remote sensing, and technology experimentation. The current status of communication satellites is presented, stressing development in the areas of CFRP construction elements, the use of LSI and MIC circuits, advanced multibeam antenna systems, Ku and Ka band transmission systems, and the shift to small-scale earth stations. Methods for reducing costs and increasing transmission efficiency are shown. The technical specifications of all satellite projects currently under development are given. Users of Japanese communications satellite are presented

Description of Four-Body Breakup Reaction with the Method of Continuum-Discretized Coupled-Channels

We present a method for smoothing discrete breakup $S$-matrix elements calculated by the method of continuum-discretized coupled-channels (CDCC). This smoothing method makes it possible to apply CDCC to four-body breakup reactions. The reliability of the smoothing method is confirmed for two cases, $^{58}$Ni($d$, $p n$) at 80 MeV and the $E1$ transition of $^6$He. We apply CDCC with the smoothing method to $^6$He breakup reaction at 22.5 MeV. Multi-step breakup processes are found to be important.Comment: 19 pages, 7 figures, published in Progress of Theoretical Physic

Nonparametric Markovian Learning of Triggering Kernels for Mutually Exciting and Mutually Inhibiting Multivariate Hawkes Processes

In this paper, we address the problem of fitting multivariate Hawkes processes to potentially large-scale data in a setting where series of events are not only mutually-exciting but can also exhibit inhibitive patterns. We focus on nonparametric learning and propose a novel algorithm called MEMIP (Markovian Estimation of Mutually Interacting Processes) that makes use of polynomial approximation theory and self-concordant analysis in order to learn both triggering kernels and base intensities of events. Moreover, considering that N historical observations are available, the algorithm performs log-likelihood maximization in $O(N)$ operations, while the complexity of non-Markovian methods is in $O(N^{2})$. Numerical experiments on simulated data, as well as real-world data, show that our method enjoys improved prediction performance when compared to state-of-the art methods like MMEL and exponential kernels