Details
| Original language | English |
|---|---|
| Title of host publication | 2023 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2023 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (electronic) | 9798350345995 |
| ISBN (print) | 979-8-3503-4600-8 |
| Publication status | Published - 2023 |
| Event | 2023 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2023 - Munich, Germany Duration: 26 Jun 2023 → 30 Jun 2023 |
Publication series
| Name | Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference |
|---|---|
| ISSN (Print) | 2639-5452 |
| ISSN (electronic) | 2833-1052 |
Abstract
Spectral broadening due to Modulation Instability (MI) during nonlinear propagation in fiber optics, can arise from noise amplification and involve incoherent and complex coupled processes, making their experimental control challenging. Over the years, MI control within both noise-driven and seeded regimes demonstrated different degrees of success [1-3]. In this experimental study, we propose a new approach of MI control by all-optical seeding, whose parameters are suitably adjusted via machine learning optimization techniques. In particular, we use Genetic Algorithms (GA) to tune the wavelength and phase parameters of two weak (yet coherent) optical seeds competing with spontaneous (noise-driven) MI dynamics. This all-optical control of noise-driven nonlinear dynamics is used to optimize the correlation between two specific wavelengths in the incoherent output spectrum. Experimentally, an 80 fs laser pulse, centered at 1560 nm, is filtered using a programmable spectral filter to reshape the broadband pulse into a picosecond pump and conjointly generate two seeds with controllable parameters (i.e., wavelength λ and phase Φ) - see Fig. 1(a). The three input signals are then amplified before entering a highly nonlinear fiber (HNLF), and the fluctuating output spectra detected in real-time using the dispersive Fourier transform (DFT) technique [4]. The corresponding spectral correlation maps can be extracted, as seen in Fig. 1(c-d), and the correlation between two selected wavelengths p(λa, λb) can be optimized by iteratively adjusting the wavelength and phase of the input seeds, as shown in Fig. 1(b).
ASJC Scopus subject areas
- Materials Science(all)
- Electronic, Optical and Magnetic Materials
- Physics and Astronomy(all)
- Instrumentation
- Physics and Astronomy(all)
- Atomic and Molecular Physics, and Optics
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2023 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Modulation Instability Control via Optical Seeding and Machine Learning Optimization
AU - Sader, Lynn
AU - Hoang, Van Thuy
AU - Boussafa, Yassin
AU - Haldar, Raktim
AU - Kermene, Vincent
AU - Kues, Michael
AU - Wetzel, Benjamin
PY - 2023
Y1 - 2023
N2 - Spectral broadening due to Modulation Instability (MI) during nonlinear propagation in fiber optics, can arise from noise amplification and involve incoherent and complex coupled processes, making their experimental control challenging. Over the years, MI control within both noise-driven and seeded regimes demonstrated different degrees of success [1-3]. In this experimental study, we propose a new approach of MI control by all-optical seeding, whose parameters are suitably adjusted via machine learning optimization techniques. In particular, we use Genetic Algorithms (GA) to tune the wavelength and phase parameters of two weak (yet coherent) optical seeds competing with spontaneous (noise-driven) MI dynamics. This all-optical control of noise-driven nonlinear dynamics is used to optimize the correlation between two specific wavelengths in the incoherent output spectrum. Experimentally, an 80 fs laser pulse, centered at 1560 nm, is filtered using a programmable spectral filter to reshape the broadband pulse into a picosecond pump and conjointly generate two seeds with controllable parameters (i.e., wavelength λ and phase Φ) - see Fig. 1(a). The three input signals are then amplified before entering a highly nonlinear fiber (HNLF), and the fluctuating output spectra detected in real-time using the dispersive Fourier transform (DFT) technique [4]. The corresponding spectral correlation maps can be extracted, as seen in Fig. 1(c-d), and the correlation between two selected wavelengths p(λa, λb) can be optimized by iteratively adjusting the wavelength and phase of the input seeds, as shown in Fig. 1(b).
AB - Spectral broadening due to Modulation Instability (MI) during nonlinear propagation in fiber optics, can arise from noise amplification and involve incoherent and complex coupled processes, making their experimental control challenging. Over the years, MI control within both noise-driven and seeded regimes demonstrated different degrees of success [1-3]. In this experimental study, we propose a new approach of MI control by all-optical seeding, whose parameters are suitably adjusted via machine learning optimization techniques. In particular, we use Genetic Algorithms (GA) to tune the wavelength and phase parameters of two weak (yet coherent) optical seeds competing with spontaneous (noise-driven) MI dynamics. This all-optical control of noise-driven nonlinear dynamics is used to optimize the correlation between two specific wavelengths in the incoherent output spectrum. Experimentally, an 80 fs laser pulse, centered at 1560 nm, is filtered using a programmable spectral filter to reshape the broadband pulse into a picosecond pump and conjointly generate two seeds with controllable parameters (i.e., wavelength λ and phase Φ) - see Fig. 1(a). The three input signals are then amplified before entering a highly nonlinear fiber (HNLF), and the fluctuating output spectra detected in real-time using the dispersive Fourier transform (DFT) technique [4]. The corresponding spectral correlation maps can be extracted, as seen in Fig. 1(c-d), and the correlation between two selected wavelengths p(λa, λb) can be optimized by iteratively adjusting the wavelength and phase of the input seeds, as shown in Fig. 1(b).
UR - http://www.scopus.com/inward/record.url?scp=85175697725&partnerID=8YFLogxK
U2 - 10.1109/CLEO/EUROPE-EQEC57999.2023.10232691
DO - 10.1109/CLEO/EUROPE-EQEC57999.2023.10232691
M3 - Conference contribution
AN - SCOPUS:85175697725
SN - 979-8-3503-4600-8
T3 - Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference
BT - 2023 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2023
Y2 - 26 June 2023 through 30 June 2023
ER -