锥形透镜光纤聚焦特性研究

锥形透镜光纤(TLF)是实现光纤与平面光波光路(PLC)芯片高效耦合的核心元件。了解和掌握其聚焦特性是指导平面光波光路尾纤封装技术的关键。给出了表征锥形透镜光纤聚焦特性的两个参量出射光斑直径和远场发散角的理论分析模型,其误差小于1.14%;采用光束传播法数值模拟了锥形透镜光纤中的光波传输和模斑的演化,确定了锥形透镜光纤端面出射光斑的大小;优化锥形透镜光纤结构参量为:拉锥长度300μm,锥角0.733°,透镜曲率半径13.485μm;建立了基于数字摄像机的锥形透镜光纤出射光场测试系统,提出了物理光学反向推演法,计算出锥形透镜光纤聚焦光斑尺寸和远场发散角。理论与实验结果有着良好的一致:对于相同结构参量的锥形透镜光纤,实验反推法得到的出射光斑尺寸与理论值相比误差为3.15%,远场发散角误差为3.67%。     

An Improved Upper Bound on the Linear 2-arboricity of 1-planar Graphs

The linear 2-arboricity la_2(G) of a graph G is the least integer k such that G can be partitioned into k edge-disjoint forests,whose component trees are paths of length at most 2.In this paper,we prove that if G is a 1-planar graph with maximum degree Δ,then la_2(G)≤[(Δ+1)/2]+7.This improves a known result of Liu et al.(2019) that every 1-planar graph G has la_2(G)≤[(Δ+1)/2]+14.We also observe that there exists a 7-regular 1-planar graph G such that la_2(G)=6=[(Δ+1)/2]+2,which implies that our solution is within 6 from optimal.     

正整数的一类三分拆的应用

利用正整数n的一类特殊的3分拆n=n1+n2+n3,n1>n2>n3≥1,且n2+n3>n1的Ferrers图将不定方程4x1+3x2+2x3=n(n≥9)的正整数解与这种分拆联系起来,从而得到了该不定方程的正整数解数公式;同时也给出了正整数n的一类4分拆的计数公式.此外,还给出了周长为n的整边三角形的计数公式的一个简单证明.     

融合图卷积神经网络和注意力机制的PM2.5小时浓度多步预测

PM_2.5小时浓度多为单步预测。为实现PM_2.5小时浓度的多步预测,基于“编码器-解码器”的序列-序列预测（Seq2Seq）模型,集合图卷积神经网络提取非欧式空间数据特征的能力以及注意力机制自适应关注特征的能力,提出了融合图卷积神经网络和注意力机制的PM_2.5小时浓度多步预测（GCN_Attention_Seq2Seq）模型。并与Seq2Seq模型和使用了图卷积神经网络、未使用注意力机制的GCN_Seq2Seq模型进行了对照,以2015—2016年北京市22个空气质量监测站点的空气质量数据为样本进行实例验证,结果表明,Seq2Seq模型和图卷积神经网络（GCN）可对PM_2.5小时浓度数据的时空依赖进行有效建模,注意力机制有助于减缓多步预测中的预测精度衰减,提升PM_2.5小时浓度多步预测的精度。GCN_Attention_Seq2Seq模型可有效应用于多种长度的PM_2.5浓度预测窗口。     

Prediction of Compound Synthesis Accessibility Based on Reaction Knowledge Graph

With the increasing application of deep-learning-based generative models for de novo molecule design, the quantitative estimation of molecular synthetic accessibility (SA) has become a crucial factor for prioritizing the structures generated from generative models. It is also useful for helping in the prioritization of hit/lead compounds and guiding retrosynthesis analysis. In this study, based on the USPTO and Pistachio reaction datasets, a chemical reaction network was constructed for the identification of the shortest reaction paths (SRP) needed to synthesize compounds, and different SRP cut-offs were then used as the threshold to distinguish a organic compound as either an easy-to-synthesize (ES) or hard-to-synthesize (HS) class. Two synthesis accessibility models (DNN-ECFP model and graph-based CMPNN model) were built using deep learning/machine learning algorithms. Compared to other existing synthesis accessibility scoring schemes, such as SYBA, SCScore, and SAScore, our results show that CMPNN (ROC AUC: 0.791) performs better than SYBA (ROC AUC: 0.76), albeit marginally, and outperforms SAScore and SCScore. Our prediction models based on historical reaction knowledge could be a potential tool for estimating molecule SA.     

有限图上高阶Yamabe型方程的非平凡解

该文研究了以下高阶Yamabe型方程Lm,pu - g|u|p-2 u = λ f|u|α-2 u在有限图上的非平凡正解的存在性,其中Lm,p是一个2m阶差分算子,它是一种p次(-Δ)m算子更一般化,α≥p≥2,g＞0和f ＞0是定义在G的所有顶点上的实函数,m≥1是一个整数.     

Topological bulk-edge effects in quantum graph transport

We examine quantum transport in periodic quantum graphs with a vertex coupling non-invariant with respect to time reversal. It is shown that the graph topology may play a decisive role in the conductivity properties illustrating this claim with two examples. In the first, the transport is possible at high energies in the bulk only being suppressed at the sample edges, while in the second one the situation is opposite, the transport is possible at the edge only.     

Neural network representations of quantum many-body states

Machine learning is currently the most active interdisciplinary field having numerous applications;additionally,machine-learning techniques are used to research quantum many-body problems.In this study,we first propose neural network quantum states(NNQSs)with general input observables and explore a few related properties,such as the tensor product and local unitary operation.Second,we determine the necessary and sufficient conditions for the representability of a general graph state using normalized NNQS.Finally,to quantify the approximation degree of a given pure state,we define the best approximation degree using normalized NNQSs.Furthermore,we observe that some 7V-qubit states can be represented by a normalized NNQS,such as separable pure states,Bell states and GHZ states.     

M@B<Subscript>9</Subscript> and M@B<Subscript>10</Subscript> molecular wheels containing planar nona- and deca-coordinate heavy group 11, 12, and 13 metals (M=Ag,Au, Cd,Hg, In,Tl)

A density functional and ab initio theory investigation on M@B₉ and M@B₁₀ molecular wheels containing planar nona- and deca-coordinate heavy group 11, 12 and 13 metals (M=Ag, Au, Cd, Hg, In, Ti) has been performed. These unusual clusters all prove to be true minima on the potential energy surfaces of the systems and σ+π double aromatic in nature. The first two vertical one-electron detachment energies of M@B₁₀⁻ (M=Ag, Au) anions and first two ionization potentials of M@B₉ (M=Ag, Au) and M@B₁₀ (M=Cd, Hg) neutrals were calculated to aid future experiments. The cluster complexes designed in this work may expend the domain of planar hyper-coordinate elements to include heavy group 11, 12, and 13 metals and serve as interesting candidates to be targeted in experiments. Electronic Supplementary Material  Supplementary material is available for this article at and is accessible for authorized users. Supported by the National Natural Science Foundation of China (Grant No. 20873117)