Scalable control techniques for automated configuration of programmable photonic circuits

As the scale of reconfigurable photonic chips increases, solutions are needed to address the increasing complexity of the electronic readout circuits needed to monitor the optical functionality. The number of these elements is strictly related to the scale of the photonic chip, and it can represent a significant overhead, in terms of electrical connections and area occupation, when the optical complexity increases. Here, we propose two scalable methods for controlling programmable chips using a single readout circuit, by individually labeling each photonic device. Experimental results at 10 Gbit/s confirm the effectiveness of the approach, while simulation analyses highlight the trade-offs that need to be considered when employing the proposed techniques.

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Publication Details

Journal
Optics Letters
Published
2026-04-21
DOI
https://doi.org/10.1364/ol.599482
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
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article

Scalable control techniques for automated configuration of programmable photonic circuits

Maziyar Milanizadeh, Francesco Morichetti, Marco Sampietro, Francesco Zanetto et al.
Optics Letters
Neural Networks and Reservoir Computing
article

Scalable control techniques for automated configuration of programmable photonic circuits

Maziyar Milanizadeh, Francesco Morichetti, Marco Sampietro, Francesco Zanetto, Andrea Melloni, Giorgio Ferrari
article en

Abstract

As the scale of reconfigurable photonic chips increases, solutions are needed to address the increasing complexity of the electronic readout circuits needed to monitor the optical functionality. The number of these elements is strictly related to the scale of the photonic chip, and it can represent a significant overhead, in terms of electrical connections and area occupation, when the optical complexity increases. Here, we propose two scalable methods for controlling programmable chips using a single readout circuit, by individually labeling each photonic device. Experimental results at 10 Gbit/s confirm the effectiveness of the approach, while simulation analyses highlight the trade-offs that need to be considered when employing the proposed techniques.

Optics LettersVol. 51(10)
Politecnico di Milano (IT)
Affordable and clean energy
Openalex Percentile: Top 21%
Neural Networks and Reservoir Computing
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