Transmission of 120 Gbaud QAM with an all-silicon segmented modulator

Segmenting a silicon modulator can substantially increase its electro-optic bandwidth without sacrificing modulation efficiency. We demonstrate a segmented silicon IQ modulator and experimentally explore both modulator design and operating point to optimize systems trade-offs in coherent detection. An electro–optic bandwidth of greater than 40 GHz is measured for a 4-mm-long segment, and greater than 60 GHz for a 2-mmlong segment. We evaluate optical transmission experimentally at 120 Gbaud for 16-ary quadrature amplitude modulation (QAM) and 32QAM. The segments are operated in tandem with identical data at each segment. We present an experimental method to align data timing between the segments. Through the optimization of segment biasing and linear compensation, we have achieved a bit error rate (BER) of 16QAM well below the 20% forward error correction (FEC) threshold (2 × 10−2 ). Adding nonlinear pre-compensation allows for 32QAM with a BER below the 24% FEC threshold (4.5 × 10−2 ), enabling a net rate of 483 Gbs per polarization. The modulator can also be operated as an optical digital analogy converter for complex optical signal generation, for which 100 Gbs is achieved for a proof of concept

Nano-channel-based physical and chemical synergic regulation for dendrite-free lithium plating

Uncontrollable dendrite growth resulting from the non-uniform lithium ion (Li+) flux and volume expansion in lithium metal (Li) negative electrode leads to rapid performance degradation and serious safety problems of lithium metal batteries. Although N-containing functional groups in carbon materials are reported to be effective to homogenize the Li+ flux, the effective interaction distance between lithium ions and N-containing groups should be relatively small (down to nanometer scale) according to the Debye length law. Thus, it is necessary to carefully design the microstructure of N-containing carbon materials to make the most of their roles in regulating the Li+ flux. In this work, porous carbon nitride microspheres (PCNMs) with abundant nanopores have been synthesized and utilized to fabricate a uniform lithiophilic coating layer having hybrid pores of both the nano- and micrometer scales on the Cu/Li foil. Physically, the three-dimensional (3D) porous framework is favorable for absorbing volume changes and guiding Li growth. Chemically, this coating layer can render a suitable interaction distance to effectively homogenize the Li+ flux and contribute to establishing a robust and stable solid electrolyte interphase (SEI) layer with Li-F, Li-N, and Li-O-rich contents based on the Debye length law. Such a physical-chemical synergic regulation strategy using PCNMs can lead to dendrite-free Li plating, resulting in a low nucleation overpotential and stable Li plating/stripping cycling performance in both the Li‖Cu and the Li‖Li symmetric cells. Meanwhile, a full cell using the PCNM coated Li foil negative electrode and a LiFePO4 positive electrode has delivered a high capacity retention of ∼ 80% after more than 200 cycles at 1 C and achieved a remarkable rate capability. The pouch cell fabricated by pairing the PCNM coated Li foil negative electrode with a NCM 811 positive electrode has retained ∼ 73% of the initial capacity after 150 cycles at 0.2 C

Statistics of weakly nonlinear waves on currents with strong vertical shear

We investigate how the presence of a vertically sheared current affects wave statistics, including the probability of rogue waves, and apply it to a real-world case using measured spectral and shear current data from the mouth of the Columbia River. A theory for weakly nonlinear waves valid to second order in wave steepness is derived and used to analyze statistical properties of surface waves; the theory extends the classic theory by Longuet-Higgins [J. Fluid Mech. 12, 321 (1962)] to allow for an arbitrary depth-dependent background flow, U ( z ) , with U the horizontal velocity along the main direction of wave propagation and z the vertical axis. Numerical statistics are collected from a large number of realizations of random, irregular sea-states following a JONSWAP spectrum, on linear and exponential model currents of varying strengths. A number of statistical quantities are presented and compared to a range of theoretical expressions from the literature; in particular the distribution of wave surface elevation, surface maxima, and crest height; the exceedance probability including the probability of rogue waves; the maximum crest height among N s waves, and the skewness of the surface elevation distribution. We find that compared to no-shear conditions, opposing vertical shear [ U ′ ( z ) > 0 ] leads to increased wave height and increased skewness of the nonlinear-wave elevation distribution, while a following shear [ U ′ ( z ) < 0 ] has opposite effects. With the wave spectrum and velocity profile measured in the Columbia River estuary by Zippel and Thomson [J. Geophys. Res.: Oceans 122, 3311 (2017)] our second-order theory predicts that the probability of rogue waves is significantly reduced and enhanced during ebb and flood, respectively, adding support to the notion that shear currents need to be accounted for in wave modeling and prediction.publishedVersio

Experimental Study of Hardening Small Strain Model Parameters for Strata Typical of Zhengzhou and Their Application in Foundation Pit Engineering

The hardening small strain (HSS) model, which considers the non-linear characteristics of the shear modulus of soil in the small strain range, is commonly utilized in the numerical analysis of excavations in sensitive environments. In order to ascertain the parameters of an HSS model for strata typical of Zhengzhou, an extensive series of laboratory tests was executed. Subsequently, a statistical analysis was utilized to establish the relationships between the principal parameters. A three-dimensional finite element model was established based on the excavation of representative strata in Zhengzhou. The accuracy and applicability of the model parameters were verified using the field measurement data. In addition, an analysis of the sensitivity of the main HSS model parameters to the foundation pit deformation was also carried out. The results show that the HSS model can analyze excavation deformation with greater precision than the hardening soil (HS) model or the Mohr–Coulomb (MC) model. The small strain parameters G0ref and γ0.7 have a great influence on the horizontal displacement of the support and the vertical displacement of soil behind the wall, respectively. The research results serve as a reliable foundation for both the analysis of excavation deformation and the determination of HSS model parameters for strata typical of Zhengzhou

Pushing capacity limits with multi-segment SiP modulators

The use of multiple segments on a silicon photonic modulator can increase bandwidth at the cost of greater complexity in the driving signals. We propose and demonstrate a simple driving scheme for use with dual segment modulators that involves very little additional complexity when equal length segments are used. The increased bandwidth with segmentation scales linearly with the number of segments, but the net bit rate does not; net rate depends on many factors. With an IQ modulator with two 2 mm segments, we demonstrate an improvement of 14% in net bit rate as compared to a single 4 mm segment. We examine the trade-offs in moving to three-segment modulation. We explore implementation penalties and use probabilistic shaping and optical pre-emphasis to achieve a net rate of 1.07 Tb/s with dual polarization transmission over 80 km of fiber at 116 Gbaud using 64QAM modulation

Integrating Linguistic Knowledge to Sentence Paraphrase Generation

Paraphrase generation aims to rewrite a text with different words while keeping the same meaning. Previous work performs the task based solely on the given dataset while ignoring the availability of external linguistic knowledge. However, it is intuitive that a model can generate more expressive and diverse paraphrase with the help of such knowledge. To fill this gap, we propose Knowledge-Enhanced Paraphrase Network (KEPN), a transformer-based framework that can leverage external linguistic knowledge to facilitate paraphrase generation. (1) The model integrates synonym information from the external linguistic knowledge into the paraphrase generator, which is used to guide the decision on whether to generate a new word or replace it with a synonym. (2) To locate the synonym pairs more accurately, we adopt an incremental encoding scheme to incorporate position information of each synonym. Besides, a multi-task architecture is designed to help the framework jointly learn the selection of synonym pairs and the generation of expressive paraphrase. Experimental results on both English and Chinese datasets show that our method significantly outperforms the state-of-the-art approaches in terms of both automatic and human evaluation