High precision modeling of a damped oscillation in coherent phonon signals by Bayesian inference
Author(s) -
Shingo Aihara,
Masaki Hamamoto,
Kazunori Iwamitsu,
Masato Okada,
Ichiro Akai
Publication year - 2017
Publication title -
aip advances
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.421
H-Index - 58
ISSN - 2158-3226
DOI - 10.1063/1.4980021
Subject(s) - oscillation (cell signaling) , phonon , bayesian probability , posterior probability , bayesian inference , probability distribution , fourier transform , signal (programming language) , physics , statistical physics , phase (matter) , noise (video) , algorithm , computational physics , mathematics , computer science , statistics , artificial intelligence , quantum mechanics , image (mathematics) , programming language , genetics , biology
By Bayesian inference with Metropolis algorithm, we have succeeded highly accurate estimation of a vibrational frequency as well as an initial phase for a damped oscillation contained in coherent phonon signals. Although a rise and damping profile of such vibrating signal impedes high precision estimation in conventional methods based on plane-waves expansion, the Bayesian inference makes it possible to obtain posterior probability distributions of all parameters in an appropriate physical model. On coherent phonon signals with a signal-to-noise ratio of ∼16dB, the probability distribution width of the vibrating frequency becomes two-orders of magnitude smaller than the Fourier spectral width. In addition, we can also estimate the initial phase with an accuracy on the order of 10 milli-radians as well as other parameters
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