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Maxim Kuschnerov

Publications and source records attributed to Maxim Kuschnerov.

8 recordsLinked to original sources

Photonic Chiplet Interconnection via 3D-Nanoprinted Interposer

Photonic integrated circuits utilize various waveguide materials, each excelling in specific metrics like efficient light emission, low propagation loss, high electro-optic efficiency, and potential for mass production. Inherent shortcomings in each platform push exploration of hybrid and heterogeneous integration, which demands specialized designs and extra fabrication processes for each material combination. Our work introduces a novel hybrid integration scheme employing a 3D-nanoprinted interposer for a photonic chiplet interconnection system. This method represents a generic solution that can readily couple between chips of any material system, with each fabricated on its own technology platform with no change in the established process flow for the individual chips. Mode-size engineering is enhanced by the off-chip parabolic micro-reflectors. The 3D-nanoprinted chip-coupling frame and fiber-guiding funnel enable low-loss, fully passive assembly with a fast-printing process achieving sub-micron accuracy. Mode-field-dimension conversion ratio of 5:2 from fiber to chip is demonstrated with <0.5dB excess loss on top of the 1.7dB inherent coupling loss, marking the largest mode size conversion using non-waveguided components. Additionally, our system demonstrates a 2.5dB die-to-die coupling loss between silicon and InP chips over a 140nm wavelength range (1480nm to 1620nm), showcasing the potential for extensive cross-platform integration by bridging different waveguide materials.

physics.optics

Spiking Neural Network Nonlinear Demapping on Neuromorphic Hardware for IM/DD Optical Communication

Neuromorphic computing implementing spiking neural networks (SNN) is a promising technology for reducing the footprint of optical transceivers, as required by the fast-paced growth of data center traffic. In this work, an SNN nonlinear demapper is designed and evaluated on a simulated intensity-modulation direct-detection link with chromatic dispersion. The SNN demapper is implemented in software and on the analog neuromorphic hardware system BrainScaleS-2 (BSS-2). For comparison, linear equalization (LE), Volterra nonlinear equalization (VNLE), and nonlinear demapping by an artificial neural network (ANN) implemented in software are considered. At a pre-forward error correction bit error rate of 2e-3, the software SNN outperforms LE by 1.5 dB, VNLE by 0.3 dB and the ANN by 0.5 dB. The hardware penalty of the SNN on BSS-2 is only 0.2 dB, i.e., also on hardware, the SNN performs better than all software implementations of the reference approaches. Hence, this work demonstrates that SNN demappers implemented on electrical analog hardware can realize powerful and accurate signal processing fulfilling the strict requirements of optical communications.

eess.SP

1.71 Tb/s Single-Channel and 56.51 Tb/s DWDM Transmission over 96.5 km Field-Deployed SSMF

We report an industry leading optical dense wavelength division multiplexing (DWDM) field trial with line rates per channel exceeding 1.66 Tb/s using 130 GBaud dual-polarization probabilistic constellation shaping 256-ary quadrature amplitude modulation (DP-PCS256QAM) in a high capacity data center interconnect (DCI) scenario. This research trial was performed on 96.5 km of field-deployed standard single mode G.652 fiber infrastructure of Deutsche Telekom in Germany employing Erbium-doped fiber amplifier (EDFA)-only amplification. A total of 34 channels were transmitted with 150 GHz spacing for a total fiber capacity of 56.51 Tb/s and a spectral efficiency higher than 11bit/s/Hz. In the single-channel transmission scenario 1.71 Tb/s was achieved over the same link. In addition, we successfully demonstrate record net bitrates of 1.88 Tb/s in back-to-back (B2B) using 130 GBaud DP-PCS400QAM.

eess.SP