[Published online Journal of Computer Chemistry, Japan Vol.24, 80-82, by J-STAGE]
<Title:> SVDを用いた実時間TDDFTのスペクトル解析
<Author(s):> 谷 直樹, 狩野 覚, 善甫 康成
<Corresponding author E-Mill:> naoki.tani.7x(at)stu.hosei.ac.jp
<Abstract:> Optical spectrum prediction based on first-principles calculations is important for the development of optical materials. In particular, Time Dependent Density Functional Theory (TDDFT) in real-time is one of the most widely used calculation methods. In real-time TDDFT, the dynamic dipole moment is used to obtain the polarizability by Fourier transform (FT). The optical spectrum can be obtained from this polarizability. However, if the time length is not sufficient, the spectrum resolution depends on the length and becomes ambiguous. To solve this problem, we introduced Dynamic Mode Decomposition (DMD). This spectral analysis technique uses both Singular Value Decomposition and Proper Orthogonal Decomposition to obtain frequencies and intensities of spectrum. The signal frequency and the intensity are directly obtained. This method was applied to TDDFT time series data for ethylene and small molecules of benzene, naphthalene, anthracene, and tetracene. Compared to conventional FT, clear spectra were obtained from a short time series data.
<Keywords:> Keywords TDDFT, Dynamic Mode Decomposition (DMD), Fourier Transform (FT), Singular Value Decomposition (SVD), Real-time TDDFT
<URL:> https://www.jstage.jst.go.jp/article/jccj/24/3/24_2025-0010/_article/-char/ja/
<Title:> SVDを用いた実時間TDDFTのスペクトル解析
<Author(s):> 谷 直樹, 狩野 覚, 善甫 康成
<Corresponding author E-Mill:> naoki.tani.7x(at)stu.hosei.ac.jp
<Abstract:> Optical spectrum prediction based on first-principles calculations is important for the development of optical materials. In particular, Time Dependent Density Functional Theory (TDDFT) in real-time is one of the most widely used calculation methods. In real-time TDDFT, the dynamic dipole moment is used to obtain the polarizability by Fourier transform (FT). The optical spectrum can be obtained from this polarizability. However, if the time length is not sufficient, the spectrum resolution depends on the length and becomes ambiguous. To solve this problem, we introduced Dynamic Mode Decomposition (DMD). This spectral analysis technique uses both Singular Value Decomposition and Proper Orthogonal Decomposition to obtain frequencies and intensities of spectrum. The signal frequency and the intensity are directly obtained. This method was applied to TDDFT time series data for ethylene and small molecules of benzene, naphthalene, anthracene, and tetracene. Compared to conventional FT, clear spectra were obtained from a short time series data.
<Keywords:> Keywords TDDFT, Dynamic Mode Decomposition (DMD), Fourier Transform (FT), Singular Value Decomposition (SVD), Real-time TDDFT
<URL:> https://www.jstage.jst.go.jp/article/jccj/24/3/24_2025-0010/_article/-char/ja/


