Flatness Optimization of Optical Frequency Combs Using an Adapted Differential Evolution Algorithm

Pendiuk, Guilherme Francisco Iakmiu; Neves, Paulo de Tarso; Pohl, Alexandre de Almeida Prado

doi:10.1364/fio.2018.jw3a.82

Cited by 1 publication

(1 citation statement)

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“…In recent years, optimization algorithms have been used in OFC generation technology to improve design efficiency. The differential evolution algorithm is applied to the OFC generator based on cascaded Mach-Zehnder modulators (MZMs) [22] and dual parallel MZMs [23] to optimize the amplitudes of the driving voltages and bias voltages of the two MZMs. The OFC with 7 comb lines and good flatness (<2 dB) is obtained.…”

Section: Introductionmentioning

confidence: 99%

Inverse design of programmable optical frequency comb using deep learning

ma¹,

Li²,

shi³

2022

J. Opt.

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Optical frequency comb (OFC) has important applications in measurement, communication, military and other fields. Usually, OFC needs to be designed according to different applications. However, the existing methods to design the operating parameters of the OFC generators are time-consuming, inefficient, and difficult to achieve optimal results. In this paper, a novel method of inversely designing OFC using deep learning, which is real-time and can improve the performance of the generated OFC, is proposed and applied to an OFC generator based on a single dual-drive Mach-Zehnder modulator. In this method, according to the required target OFC, the trained neural network can be used to inversely design the corresponding parameters. Using this inverse design method, the generated OFC not only is highly consistent with the target OFC, but also has the programmability of comb-line number, comb-line power, side mode suppression ratio, and comb spacing. Moreover, the proposed method can be utilized for more complicated OFC generator, and is an inspiration for efficient design of OFC.

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Section: Introductionmentioning

confidence: 99%