Continuous and long-term stabilization of degenerate optical parametric oscillators for large-scale optical hybrid computers
Author(s) -
Takuya Ikuta,
Takahiro Inagaki,
Kensuke Inaba,
Toshimori Honjo,
Takushi Kazama,
Koji Enbutsu,
Takahiro Kashiwazaki,
Ryoichi Kasahara,
Takeshi Umeki,
Hiroki Takesue
Publication year - 2020
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.412078
Subject(s) - allan variance , computer science , scalability , reservoir computing , optical computing , optical fiber , phase noise , parametric statistics , optical parametric oscillator , optics , computation , noise (video) , electronic engineering , standard deviation , telecommunications , physics , algorithm , mathematics , engineering , laser , statistics , database , machine learning , artificial intelligence , recurrent neural network , artificial neural network , image (mathematics)
The minimum requirements for an optical reservoir computer, a recent paradigm for computation using simple algorithms, are nonlinearity and internal interactions. A promising optical system satisfying these requirements is a platform based on coupled degenerate optical parametric oscillators (DOPOs) in a fiber ring cavity. We can expect advantages using DOPOs for reservoir computing with respect to scalability and reduction of excess noise; however, the continuous stabilization required for reservoir computing has not yet been demonstrated. Here, we report the continuous and long-term stabilization of an optical system by introducing periodical phase modulation patterns for DOPOs and a local oscillator. We observed that the Allan variance of the optical phase up to 100 ms was suppressed and that the homodyne measurement signal had a relative standard deviation of 1.4% over 62,500 round trips. The proposed methods represent important technical bases for realizing stable computation on large-scale optical hybrid computers.
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