High-Speed Coherent Photonic Random-Access Memory in Long-Lasting Sound Waves

In recent years, remarkable advances in photonic computing have highlighted the need for photonic memory, particularly high-speed and coherent random-access memory. Addressing the ongoing challenge of implementing photonic memories is required to fully harness the potential of photonic computing. A photonic-phononic memory based on stimulated Brillouin scattering is a possible solution, as it coherently transfers optical information into sound waves at high-speed. Such an optoacoustic memory has shown great potential as it fulfills key requirements for high-performance optical random-access memory due to its coherence, on-chip compatibility, frequency selectivity, and high bandwidth. However, the storage time has so far been limited to a few nanoseconds due to the nanosecond decay of the acoustic wave. In this work, we experimentally enhance the intrinsic storage time of an optoacoustic memory by more than 1 order of magnitude and coherently retrieve optical information after a storage time of 123 ns. This is achieved by employing the optoacoustic memory in a highly nonlinear fiber at 4.2 K, increasing the intrinsic phonon lifetime by a factor of 6. We demonstrate the capability of our scheme by measuring the initial and readout optical data pulses with a direct and double homodyne detection scheme. Finally, we analyze the dynamics of the optoacoustic memory at different cryogenic temperatures in the range of 4.2–20 K and compare the findings to continuous wave measurements. The extended storage time is beneficial not only for photonic computing but also for Brillouin applications that require long phonon lifetimes, such as optoacoustic filters, true-time delay networks, and synthesizers in microwave photonics.

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Publication Details

Journal
ACS Photonics
Published
2024-10-18
DOI
https://doi.org/10.1021/acsphotonics.4c00478
Citations
7
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
2.43

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article

High-Speed Coherent Photonic Random-Access Memory in Long-Lasting Sound Waves

Andreas Geilen, Birgit Stiller, Steven Becker
7 citations
ACS Photonics
Neural Networks and Reservoir Computing
2.43
article

High-Speed Coherent Photonic Random-Access Memory in Long-Lasting Sound Waves

Andreas Geilen, Birgit Stiller, Steven Becker
article en
7 citations

Abstract

In recent years, remarkable advances in photonic computing have highlighted the need for photonic memory, particularly high-speed and coherent random-access memory. Addressing the ongoing challenge of implementing photonic memories is required to fully harness the potential of photonic computing. A photonic-phononic memory based on stimulated Brillouin scattering is a possible solution, as it coherently transfers optical information into sound waves at high-speed. Such an optoacoustic memory has shown great potential as it fulfills key requirements for high-performance optical random-access memory due to its coherence, on-chip compatibility, frequency selectivity, and high bandwidth. However, the storage time has so far been limited to a few nanoseconds due to the nanosecond decay of the acoustic wave. In this work, we experimentally enhance the intrinsic storage time of an optoacoustic memory by more than 1 order of magnitude and coherently retrieve optical information after a storage time of 123 ns. This is achieved by employing the optoacoustic memory in a highly nonlinear fiber at 4.2 K, increasing the intrinsic phonon lifetime by a factor of 6. We demonstrate the capability of our scheme by measuring the initial and readout optical data pulses with a direct and double homodyne detection scheme. Finally, we analyze the dynamics of the optoacoustic memory at different cryogenic temperatures in the range of 4.2–20 K and compare the findings to continuous wave measurements. The extended storage time is beneficial not only for photonic computing but also for Brillouin applications that require long phonon lifetimes, such as optoacoustic filters, true-time delay networks, and synthesizers in microwave photonics.

ACS PhotonicsVol. 11(11)
Friedrich-Alexander-Universität Erlangen-Nürnberg (DE), Max Planck Institute for the Science of Light (DE)
Deutsche Forschungsgemeinschaft, Max-Planck-Gesellschaft, Studienstiftung des Deutschen Volkes
Affordable and clean energy
Openalex Percentile: Top 9%
Neural Networks and Reservoir Computing
2.43
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