Naoko Nose-Togawa

Residual interaction effects on deeply bound pionic states in Sn and Pb isotopes

We have studied the residual interaction effects theoretically on the deeply bound pionic states in Pb and Sn isotopes. We need to evaluate the residual interaction effects carefully to deduce the nuclear medium effects for pion properties, which are believed to provide valuable information on nuclear chiral dynamics. The s- and p-wave {pi}N interactions are used for the pion-nucleon residual interactions. We show that the complex energy shifts are around [(10-20) + i(2-7)] keV for 1s states in Sn, which should be taken into account in the analyses of the high precision data of deeply bound pionic 1s states in Sn isotopes.

MULTIDIMENSIONAL EXTENSION OF SINGULAR SPECTRUM ANALYSIS BASED ON FILTERING INTERPRETATION

Singular spectrum analysis is a nonparametric spectral decomposition of a time series. The singular spectrum analysis can be viewed as the two-step filtering with the complete set of eigenfilter adaptively constructed from the original time series. Based on this viewpoint, we present a flexible and quite simple algorithm for the singular spectrum analysis which can be applied to the multidimensional data series with arbitrary dimension. We have carried out the decomposition of two-dimensional image data, and the optimally constructed filters are found to be the smoothing or the edge enhancement filters of various type. We have also examined a simple example for the decomposition of 3D data.

An Adaptive Orthogonal SSA Decomposition Algorithm for a Time Series

Singular spectrum analysis (SSA) is a nonparametric spectral decomposition of a time series into arbitrary number of interpretable components. It involves a single parameter, window length L, which...

Filter Characteristics in Image Decomposition with Singular Spectrum Analysis

Singular spectrum analysis is developed as a nonparametric spectral decomposition of a time series. It can be easily extended to the decomposition of multidimensional lattice-like data through the filtering interpretation. In this viewpoint, the singular spectrum analysis can be understood as the adaptive and optimal generation of the filters and their two-step point-symmetric operation to the original data. In this paper, we point out that, when applied to the multidimensional data, the adaptively generated filters exhibit symmetry properties resulting from the bisymmetric nature of the lag-covariance matrices. The eigenvectors of the lag-covariance matrix are either symmetric or antisymmetric, and for the 2D image data, these lead to the differential-type filters with even- or odd-order derivatives. The dominant filter is a smoothing filter, reflecting the dominance of low-frequency components of the photo images. The others are the edge-enhancement or the noise filters corresponding to the band-pass or the high-pass filters. The implication of the decomposition to the image denoising is briefly discussed.

Additive Decomposition of Power Spectrum Density in Singular Spectrum Analysis

Singular spectrum analysis (SSA) is a nonparametric and adaptive spectral decomposition of a time series. The singular value decomposition of the trajectory matrix and the anti-diagonal averaging lead to a time-series decomposition. In this paper, we propose an novel algorithm for the additive decomposition of the power spectrum density of a time series based on the filtering interpretation of SSA. This can be used to examine the spectral overlap or the admixture of the SSA decomposition. We can obtain insights into the spectral structure of the SSA decomposition which helps us for the proper choice of the window length in the practical application. The relationship to the conventional SSA decomposition of a time series is also discussed.

Relativistic Description of Semi-Infinite Nuclear Matter with Vacuum Polarization

We study the property of semi-infinite nuclear matter using the relativistic mean field (RMF) model with vacuum polarization. The vacuum polarization effect is calculated by the derivative expansion method, which has been shown to be a good approximation in rigorous numerical calculations. The Lagrangian density is written in terms of positive energy nucleon states together with the meson fields and the derivative meson terms for the vacuum polarization. We find that the vacuum polarization makes both the surface thickness and surface energy coefficient larger, and therefore, it is important to describe the empirical nuclear surface properties. Moreover, the vacuum polarization smoothens the oscillatory behavior of the nuclear density observed inside the nuclear surface in the RMF model.

Elastic and inelastic scattering of {pi}{sup +} and {pi}{sup -} on {sup 12}C at 995 MeV/c

{pi}{sup +} and {pi}{sup -} elastic and inelastic scattering to the 2{sub 1}{sup +}(4.44 MeV) state on {sup 12}C at 995 MeV/c were measured over an angular range for elastic-scattering from 5.4 deg. to 28.2 deg. and for inelastic scattering from 15.2 deg. to 22.8 deg. Both of the elastic-scattering data sets were well reproduced by first-order factorized momentum-space optical potential calculations with free {pi}-N elementary amplitudes and three different ground state densities, which were deduced from the charge density and microscopic model calculations, the cluster model and the shell model. We also extracted {sigma}{sub tot},{sigma}{sub el}, and {sigma}{sub R} phenomenologically and compared them with a Fermi averaging model. The inelastic cross sections of {pi}{sup +}-{sup 12}C and {pi}{sup -}-{sup 12}C were compared with the DWIA calculations, one using the transition density(0{sup +}{yields}2{sub 1}{sup +}) deduced by the cluster model and the other using the transition density deduced by the shell model.