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Conferences > OFC > 2024 > M3I > M3I.2

Recalibration Learning: Enabling Universal Transfer of ML Model of Gain and NF for Remote Optically Pumped Amplifiers

Arthur Minakhmetov, Benjamin Prieur, Maël Le Monnier, Delphine Rouvillain, and Bruno Lavigne

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Abstract

We demonstrate a novel, physical assumptions-based method – recalibration learning, that transfers Gain and Noise Figure ML models across remote optically pumped amplifiers. Spectral measurements over just two configurations on a target device ensure reliable transfer.

© 2024 The Author(s)

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