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Scalable Non‐Volatile Tuning of Photonic Computational Memories by Automated Silicon Ion Implantation

Akhil Varri, Shabnam Taheriniya, Frank Brückerhoff‐Plückelmann, Ivonne Bente, Nikolaos Farmakidis, Daniel Bernhardt, Harald Rösner, Maximilian Kruth, Achim Nadzeyka, Torsten Richter, C. David Wright, Harish Bhaskaran, Gerhard Wilde, Wolfram H. P. Pernice

2023Advanced Materials18 citationsDOIOpen Access PDF

Abstract

Photonic integrated circuits (PICs) are revolutionizing the realm of information technology, promising unprecedented speeds and efficiency in data processing and optical communication. However, the nanoscale precision required to fabricate these circuits at scale presents significant challenges, due to the need to maintain consistency across wavelength-selective components, which necessitates individualized adjustments after fabrication. Harnessing spectral alignment by automated silicon ion implantation, in this work scalable and non-volatile photonic computational memories are demonstrated in high-quality resonant devices. Precise spectral trimming of large-scale photonic ensembles from a few picometers to several nanometres is achieved with long-term stability and marginal loss penalty. Based on this approach, spectrally aligned photonic memory and computing systems for general matrix multiplication are demonstrated, enabling wavelength multiplexed integrated architectures at large scales.

Topics & Concepts

Materials sciencePhotonicsScalabilityMultiplexingPhotonic integrated circuitSilicon photonicsOptoelectronicsElectronic circuitFabricationSiliconNanotechnologyIntegrated circuitElectronic engineeringComputer scienceTelecommunicationsElectrical engineeringEngineeringAlternative medicinePathologyDatabaseMedicineNeural Networks and Reservoir ComputingPhotonic and Optical DevicesOptical Network Technologies
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