Tunable dispersion and dispersion slope compensators for 10 Gb/s using all-pass multicavity etalons

Moss, David; Lamont, Michael R. E.; Mclaughlin, Sheldon; Randall, G.; Colbourne, Paul; Kiran, Shiva; Hulse, Charles A.

doi:10.1109/leosst.2002.1027561

Cited by 8 publications

(6 citation statements)

References 7 publications

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“…This work highlights the potential for microcombs in microwave signal processing , particularly in the Hydex glass platform [88-99], including recent results in optical communications [101] and neural networks [102,103] as well as quantum optics [104][105][106][107][108][109][110][111][112]. Integrating devices such as detectors [113] and dispersion compensation delays on-chip [114][115][116][117] will further enhance the power and greatly reduce the footprint of these systems.…”

Section: Resultsmentioning

confidence: 99%

Microwave photonic filters using optical to microwave frequency bandwidth translation with Kerr soliton crystal micro-combs

Moss¹

2021

Preprint

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We demonstrate high-resolution photonic RF filters using an RF bandwidth scaling approach based on integrated Kerr optical micro-combs. By employing both an active nonlinear micro-ring resonator (MRR) as a high-quality micro-comb source and a passive high-Q MRR to slice the shaped comb, a large RF instantaneous bandwidth of 4.64 GHz and a high resolution of 117 MHz are achieved, together with a broad RF operation band covering 3.28 to 19.4 GHz (L to Ku bands) using thermal tuning. We achieve programmable RF transfer functions including binary-coded notch filters and RF equalizing filters with reconfigurable slopes. Our approach is an attractive solution for high performance RF spectral shaping with high performance and flexibility.

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Section: Resultsmentioning

confidence: 99%

Microwave photonic filters using optical to microwave frequency bandwidth translation with Kerr soliton crystal micro-combs

Moss¹

2021

Preprint

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“…Although we had a non-trivial optical latency of 0.11 μs introduced by dispersive bre spool, this did not affect the operational speed. Moreover, the latency of the delay function can be virtually eliminated (to < 200 ps) by using integrated highly dispersive devices such as photonic crystals or customized chirped Bragg gratings [92] or even tunable dispersion compensators [93,94]. Finally, current nanofabrication techniques can enable signi cantly higher levels of integration of the convolutional accelerator.…”

Section: Discussionmentioning

confidence: 99%

Advanced applications of microcombs: From optical neural networks to data transmission

Tan

Moss

2021

Preprint

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We report ultrahigh bandwidth applications of Kerr microcombs to optical neural networks and to optical data transmission, at data rates from 44 Terabits/s (Tb/s) to approaching 100 Tb/s. Convolutional neural networks (CNNs) are a powerful category of artificial neural networks that can extract the hierarchical features of raw data to greatly reduce the network complexity and enhance the accuracy for machine learning tasks such as computer vision, speech recognition, playing board games and medical diagnosis [1-7]. Optical neural networks can dramatically accelerate the computing speed to overcome the inherent bandwidth bottleneck of electronics. We use a new and powerful class of micro-comb called soliton crystals that exhibit robust operation and stable generation as well as a high intrinsic efficiency with an extremely low spacing of 48.9 GHz. We demonstrate a universal optical vector convolutional accelerator operating at 11 Tera-OPS/s (TOPS) on 250,000 pixel images for 10 kernels simultaneously — enough for facial image recognition. We use the same hardware to sequentially form a deep optical CNN with ten output neurons, achieving successful recognition of full 10 digits with 900 pixel handwritten digit images. We also report world record high data transmission over standard optical fiber from a single optical source, at 44.2 Terabits/s over the C-band, with a spectral efficiency of 10.4 bits/s/Hz, with a coherent data modulation format of 64 QAM. We achieve error free transmission across 75 km of standard optical fiber in the lab and over a field trial with a metropolitan optical fiber network. Our work demonstrates the ability of optical soliton crystal micro-combs to exceed other approaches in performance for the most demanding practical optical communications applications.

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“…Although we had a non-trivial optical latency of 0.11 μs introduced by dispersive fibre spool, this did not affect the operational speed. Moreover, the latency of the delay function can be virtually eliminated (to < 200 ps) by using integrated highly dispersive devices such as photonic crystals or customized chirped Bragg gratings [92] or even tunable dispersion compensators [93][94][95][96]. Finally, current nanofabrication techniques can enable significantly higher levels of integration of the convolutional accelerator.…”

Section: Discussionmentioning

confidence: 99%

Photonic convolutional accelerator operating at Tera-OPs speeds for neural networks with Kerr microcombs

Moss¹

2021

Preprint

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<p>Convolutional neural networks (CNNs), inspired by biological visual cortex systems, are a powerful category of artificial neural networks that can extract the hierarchical features of raw data to greatly reduce the network parametric complexity and enhance the predicting accuracy. They are of significant interest for machine learning tasks such as computer vision, speech recognition, playing board games and medical diagnosis [1-7]. Optical neural networks offer the promise of dramatically accelerating computing speed to overcome the inherent bandwidth bottleneck of electronics. Here, we demonstrate a universal optical vector convolutional accelerator operating beyond 10 Tera-OPS (TOPS - operations per second), generating convolutions of images of 250,000 pixels with 8-bit resolution for 10 kernels simultaneously — enough for facial image recognition. We then use the same hardware to sequentially form a deep optical CNN with ten output neurons, achieving successful recognition of full 10 digits with 900 pixel handwritten digit images with 88% accuracy. Our results are based on simultaneously interleaving temporal, wavelength and spatial dimensions enabled by an integrated microcomb source. This approach is scalable and trainable to much more complex networks for demanding applications such as unmanned vehicle and real-time video recognition. <i> </i></p>

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Tunable dispersion and dispersion slope compensators for 10 Gb/s using all-pass multicavity etalons

Cited by 8 publications

References 7 publications

Microwave photonic filters using optical to microwave frequency bandwidth translation with Kerr soliton crystal micro-combs

Microwave photonic filters using optical to microwave frequency bandwidth translation with Kerr soliton crystal micro-combs

Advanced applications of microcombs: From optical neural networks to data transmission

Photonic convolutional accelerator operating at Tera-OPs speeds for neural networks with Kerr microcombs

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