Power-efficient programmable integrated multiport photonic interferometer in CMOS-compatible silicon nitride

Silicon nitride(SiNx)is an appealing waveguide material choice for large-scale,high-performance photonic integrated circuits(PICs)due to its low optical loss.However,SiNx PICs require high electric power to realize optical reconfiguration via the weak thermo-optic effect,which limits their scalability in terms of device density and chip power dissipation.We report a 6-mode programmable interferometer PIC operating at the wavelength of 1550 nm on a CMOS-compatible low-temperature inductance coupled plasma chemical vapor deposition(ICP-CVD)silicon nitride platform.By employing suspended thermo-optic phase shifters,the PIC achieves 2×improvement in compactness and 10×enhancement in power efficiency compared to conventional devices.Reconfigurable 6-dimensional linear transformations are demonstrated including cyclic transformations and arbitrary unitary matrices.This work demonstrates the feasibility of fabricating power-efficient large-scale reconfigurable PICs on the low-temperature ICP-CVD silicon nitride platform.

1-Pbps orbital angular momentum fibre-optic transmission

Space-division multiplexing(SDM),as a main candidate for future ultra-high capacity fibre-optic communications,needs to address limitations to its scalability imposed by computation-intensive multi-input multi-output(MIMO)digital signal processing(DSP)required to eliminate the crosstalk caused by optical coupling between multiplexed spatial channels.By exploiting the unique propagation characteristics of orbital angular momentum(OAM)modes in ring core fibres(RCFs),a system that combines SDM and C+L band dense wavelength-division multiplexing(DWDM)in a 34 km 7-core RCF is demonstrated to transport a total of 24960 channels with a raw(net)capacity of 1.223(1.02)Peta-bit s−1(Pbps)and a spectral efficiency of 156.8(130.7)bit s−1 Hz−1.Remarkably for such a high channel count,the system only uses fixed-size 4×4 MIMO DSP modules with no more than 25 time-domain taps.Such ultra-low MIMO complexity is enabled by the simultaneous weak coupling among fibre cores and amongst non-degenerate OAM mode groups within each core that have a fixed number of 4 modes.These results take the capacity of OAM-based fibre-optic communications links over the 1 Pbps milestone for the first time.They also simultaneously represent the lowest MIMO complexity and the 2nd smallest fibre cladding diameter amongst reported few-mode multicore-fibre(FM-MCF)SDM systems of>1 Pbps capacity.We believe these results represent a major step forward in SDM transmission,as they manifest the significant potentials for further up-scaling the capacity per optical fibre whilst keeping MIMO processing to an ultra-low complexity level and in a modularly expandable fashion.

Soliton frequency comb generation in CMOS-compatible silicon nitride microresonators

The monolithic integration of soliton microcomb devices with active photonic components and high-frequency electronics is highly desirable for practical applications. Among many materials, silicon nitride(SiN_(x)) waveguide layers prepared by low-pressure chemical vapor deposition(LPCVD) have been the main platform for on-chip optical frequency comb generation. However, the high temperatures involved in LPCVD render it incompatible as a back-end process with complementary metal oxide semiconductor(CMOS) or active Ⅲ-Ⅴ compound semiconductor fabrication flows. We report the generation of coherent soliton frequency combs in micro-ring resonators fabricated in deuterated silicon nitride(SiN_(x):D) waveguides with a loss of 0.09 d B/cm. Deposited at 270℃ by an inductance-coupled plasma chemical vapor deposition(ICP-CVD) process, the material preparation and fabrication flow are fully CMOS-compatible. These results enable the integration of silicon-nitride-based optical combs and photonic integrated circuits(PICs) on prefabricated CMOS and/or Ⅲ-Ⅴ substrates, therefore marking a major step forward in Si Nxphotonic technologies.

Fast Maximum Entropy Machine for Big Imbalanced Datasets

Driven by the need of a plethora of machine learning applications,several attempts have been made at improving the performance of classifiers applied to imbalanced datasets.In this paper,we present a fast maximum entropy machine(MEM)combined with a synthetic minority over-sampling technique for handling binary classification problems with high imbalance ratios,large numbers of data samples,and medium/large numbers of features.A random Fourier feature representation of kernel functions and primal estimated sub-gradient solver for support vector machine(PEGASOS)are applied to speed up the classic MEM.Experiments have been conducted using various real datasets(including two China Mobile datasets and several other standard test datasets)with various configurations.The obtained results demonstrate that the proposed algorithm has extremely low complexity but an excellent overall classification performance(in terms of several widely used evaluation metrics)as compared to the classic MEM and some other state-of-the-art methods.The proposed algorithm is particularly valuable in big data applications owing to its significantly low computational complexity.