What question did this study set out to answer?

To design and experimentally validate a machine-learning-controlled, highly nonlinear fiber amplifier that broadens ultrashort pulse amplification into the L- and U-bands.

August 14, 2026Photonics ResearchOpen Access

A highly nonlinear ultrafast fiber amplifier beyond the L-band harnessed with machine learning

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Authors

MKMikołaj Krakowski AKAlicja Kwaśny DSDorota Stachowiak

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Overview

Experimental study demonstrates machine learning optimization of an ultrafast fiber amplifier across L- and U-bands, enabling smart laser development with adaptive spectral shaping.

Key Points

To design and experimentally validate a machine-learning-controlled, highly nonlinear fiber amplifier that broadens ultrashort pulse amplification into the L- and U-bands.
Implemented an erbium-ytterbium co-doped, small-core (3.8 μm) double-clad fiber operating in the normal-dispersion regime.
Used a programmable optical filter to adjust the spectral phase and shape of input seed pulses.
Applied a machine-learning optimization algorithm to iteratively configure input conditions for targeted spectral emission and compressibility.
Achieved ultrashort pulse amplification across both the L-band (1565–1625 nm) and U-band (1625–1675 nm) via nonlinear spectral broadening and redshifting.
Demonstrated user-defined spectral maximization while maintaining near-transform-limited pulse compressibility.

Cite This Study

Krakowski et al. (2026) studied this question.

synapsesocial.com/papers/6a7ec6c6b70b84ec8b912cf9 https://doi.org/10.1364/prj.606476

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August 14, 2026Photonics ResearchOpen Access

A highly nonlinear ultrafast fiber amplifier beyond the L-band harnessed with machine learning

View Full Paper

Ask AI

Bookmark

Authors

MKMikołaj Krakowski AKAlicja Kwaśny DSDorota Stachowiak

Discussion

Member takes

Overview

Experimental study demonstrates machine learning optimization of an ultrafast fiber amplifier across L- and U-bands, enabling smart laser development with adaptive spectral shaping.

Key Points

To design and experimentally validate a machine-learning-controlled, highly nonlinear fiber amplifier that broadens ultrashort pulse amplification into the L- and U-bands.
Implemented an erbium-ytterbium co-doped, small-core (3.8 μm) double-clad fiber operating in the normal-dispersion regime.
Used a programmable optical filter to adjust the spectral phase and shape of input seed pulses.
Applied a machine-learning optimization algorithm to iteratively configure input conditions for targeted spectral emission and compressibility.
Achieved ultrashort pulse amplification across both the L-band (1565–1625 nm) and U-band (1625–1675 nm) via nonlinear spectral broadening and redshifting.
Demonstrated user-defined spectral maximization while maintaining near-transform-limited pulse compressibility.

Cite This Study

Krakowski et al. (2026) studied this question.

synapsesocial.com/papers/6a7ec6c6b70b84ec8b912cf9 https://doi.org/10.1364/prj.606476

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