Linearizability of planar polynomial Hamiltonian systems

Isochronicity and linearizability of two-dimensional polynomial Hamiltonian systems are revisited and new results are presented. We give a new computational procedure to obtain the necessary and sufficient conditions for the linearization of a polynomial system. Using computer algebra systems we provide necessary and sufficient conditions for linearizability of Hamiltonian systems with homogeneous non-linearities of degrees 5, 6 and 7. We also present some sufficient conditions for systems with nonhomogeneous nonlinearities of degrees two, three and five.     

Hamiltonian cycles in 7-tough (P3 ∪ 2P1)-free graphs

The toughness of a noncomplete graph G is the maximum real number t such that the ratio of $|S|$ to the number of components of $G?S$ is at least t for every cutset S of G. Determining the toughness for a given graph is NP-hard. Chvátal's toughness conjecture, stating that there exists a constant $t_0$ such that every graph with toughness at least $t_0$ is hamiltonian, is still open for general graphs. A graph is called $(P_3\cup 2P_1)$-free if it does not contain any induced subgraph isomorphic to $P_3\cup 2P_1$, the disjoint union of $P_3$ and two isolated vertices. In this paper, we confirm Chvátal's toughness conjecture for $(P_3\cup 2P_1)$-free graphs by showing that every 7-tough $(P_3\cup 2P_1)$-free graph on at least three vertices is hamiltonian.     

Hamiltonian and long paths in bipartite graphs with connectivity

Let G be a graph, $\nu (G)$ the order of G, $\kappa (G)$ the connectivity of G and k a positive integer such that $k\le (\nu (G)?2)/2$. Then G is said to be k-extendable if it has a matching of size k and every matching of size k extends to a perfect matching of G. A Hamiltonian path of a graph G is a spanning path of G. A bipartite graph G with vertex sets $V_1$ and $V_2$ is defined to be Hamiltonian-laceable if such that $|V_1|=|V_2|$ and for every pair of vertices $p\in V_1$ and $q\in V_2$, there exists a Hamiltonian path in G with endpoints p and q, or $|V_1|=|V_2|+1$ and for every pair of vertices $p,q\in V_1,p\ne q$, there exists a Hamiltonian path in G with endpoints p and q. Let G be a bipartite graph with bipartition $(X,Y)$. Define $bn(G)$ to be a maximum integer such that $0\le bn(G)<min\{|X|,|Y|\}$ and (1) for each non-empty subset S of X, if $|S|\le |X|?bn(G)$, then $|N(S)|\ge |S|+bn(G)$, and if $|X|?bn(G)<|S|\le |X|$, then $N(S)=Y$; and (2) for each non-empty subset S of Y, if $|S|\le |Y|?bn(G)$, then $|N(S)|\ge |S|+bn(G)$, and if $|Y|?bn(G)<|S|\le |Y|$, then $N(S)=X$; and (3) $bn(G)=0$ if there is no non-negative integer satisfying (1) and (2).Let G be a bipartite graph with bipartition $(X,Y)$ such that $|X|=|Y|$ and $bn(G)>0$. In this paper, we show that if $\nu (G)\le 2\kappa (G)+4bn(G)?4$, then G is Hamiltonian-laceable; or if $\nu (G)>6bn(G)?2$, then for every pair of vertices $x\in X$ and $y\in Y$, there is an $(x,y)$-path P in G with $|V(P)|\ge 6bn(G)?2$. We show some of its corollaries in k-extendable, bipartite graphs and a conjecture in k-extendable graphs.     

Yb3+掺杂稀土钽铌酸盐的晶体场从头计算研究

Yb³⁺掺杂晶体材料是重要的激光材料,在超短脉冲激光、大功率激光等领域有重要应用前景,但长期以来很难通过实验拟合确定Yb3+晶体场参数,尤其是低对称体系,从头计算是解决此问题的重要途经.本文介绍了适合计算稀土离子掺杂晶体的从头计算DV-Xα方法和有效哈密顿量模型,用该方法计算了Yb³⁺掺杂M型和M'型钽铌酸盐的晶场参数和旋轨耦合参数,得到的能级结构和实验能很好地符合,并发现了Yb³⁺掺杂钽铌酸盐的晶场强度参数随稀土原子序数呈现规律变化.表明结合DV-Xα计算和有效哈密顿量方法是计算Yb³⁺掺杂低对称钽铌酸盐晶体场的有效途径,结果显示Yb3+掺杂钽铌酸盐晶体有望成为新型全固态激光工作物质.     

高光谱成像的土壤剖面水分含量反演及制图

传统土壤水分的获取方法仅可获得离散的土壤水分点位数据，难以获得剖面上精细且连续的水分含量分布图。研究了野外条件下利用近红外高光谱（882～1 709 nm）成像反演剖面土壤水分含量（SMC），并实现精细制图的可行性。研究剖面位于江苏省东台市，我们利用近红外高光谱成像仪对剖面进行了5天原位连续观测，共采集了280个土样用于烘干法测定SMC。原始高光谱图像经数字量化值（DN）校正、黑白校正、拼接、几何校正、剪切和掩膜等一系列预处理后，提取各采样点的平均光谱反射率。提取光谱（Raw）经吸光度[LOG₁₀(1/R)]，Savitzky-Golay平滑（SG）、一阶微分（FD）、二阶微分（SD）、多元散射校正（MSC）和标准正态变量（SNV）转换后，采用偏最小二乘回归（PLSR）和最小二乘支持向量机（LS-SVM）方法建立SMC预测模型，并对比分析不同光谱预处理方法与建模方法组合条件下SMC的预测精度。结果表明，光谱反射率随SMC增加逐渐降低，不同光谱预处理方法的预测精度有所差异，除MSC方法外，同一光谱预处理方法的LS-SVM模型预测精度均高于PLSR模型，并且基于LOG₁₀(1/R)光谱的LS-SVM模型对SMC预测精度最高，其建模集的决定系数（R2_c）和均方根误差（RMSE_c）分别为0.96和0.65%，预测集的决定系数（R2_p）、均方根误差（RMSE_p）和相对分析误差（RPD_p）分别为0.88，1.05%和2.88。利用最优模型进行剖面SMC的高空间分辨率精细制图，通过比较SMC反演图中提取的预测值与实测值关系发现预测精度较高（R2: 0.85～0.95, RMSE: 0.94%～1.02%），且两者在剖面中的变化趋势基本一致，说明SMC反演图不仅能很好地反映出土壤水分在整个剖面中毫米级的含量分布信息，也可反映出同一位置处不同天数间的含量差异。因此，利用近红外高光谱成像结合优化的预测模型，能够实现土壤剖面SMC的定量预测及精细制图，有助于快速、有效监测田间剖面土壤水分状况。