2014 年 13 巻 6 号 p. 314-316
The maximum entropy method (MEM) is one of the key techniques for spectral analysis. The main feature is to describe spectra in low frequency with short time-series data. We adopted MEM to analyze the spectrum from the dipole moment obtained by the time-dependent density functional theory (TDDFT) calculation in real time, which is intensively studied and applied to computing optical properties. In the MEM analysis, however, the maximum lag of the autocorrelation is restricted by the total number of time-series data. We proposed that, as an improved MEM analysis, we use the concatenated data set made from several-times repeated raw data. We have applied this technique to the spectral analysis of the TDDFT dipole moment of ethylene and oligo-fluorene with n = 8. As a result, higher resolution can be obtained, which is closer to that of FT with just raw data. The efficiency and the characteristic feature of this technique are presented in this paper.