Results 41 to 50 of about 1,624,240 (288)
On the Laplacian, signless Laplacian and normalized Laplacian characteristic polynomials of a graph [PDF]
, 2013 summary:The Laplacian, signless Laplacian and normalized Laplacian characteristic polynomials of a graph are the characteristic polynomials of its Laplacian matrix, signless Laplacian matrix and normalized Laplacian matrix, respectively.
Li, Jianxi, Guo, Ji-Ming, Shiu, Wai Chee
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Seidel Signless Laplacian Energy of Graphs [PDF]
Mathematics Interdisciplinary Research, 2017 Let S(G) be the Seidel matrix of a graph G of order n and let DS(G)=diag(n-1-2d1, n-1-2d2,..., n-1-2dn) be the diagonal matrix with d_i denoting the degree of a vertex v_i in G.
Harishchandra Ramane +3 more
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MathematicsFor network graphs, numerous graph features are intimately linked to eigenvalues of the Laplacian matrix, such as connectivity and diameter. Thus, it is very important to solve eigenvalues of the Laplacian matrix for graphs.
Changlei Zhan, Xiangyu Li, Jie Chen
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On Eccentricity Version of Laplacian Energy of a Graph [PDF]
Mathematics Interdisciplinary Research, 2017 The energy of a graph G is equal to the sum of absolute values of the eigenvalues of the adjacency matrix of G, whereas the Laplacian energy of a graph G is equal to the sum of the absolute value of the difference between the eigenvalues of the Laplacian
Nilanjan De
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On the Adjacency, Laplacian, and Signless Laplacian Spectrum of Coalescence of Complete Graphs
Journal of Mathematics, 2016 Coalescence as one of the operations on a pair of graphs is significant due to its simple form of chromatic polynomial. The adjacency matrix, Laplacian matrix, and signless Laplacian matrix are common matrices usually considered for discussion under ...
S. R. Jog, Raju Kotambari
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The Distance Laplacian Spectral Radius of Clique Trees
Discrete Dynamics in Nature and Society, 2020 The distance Laplacian matrix of a connected graph G is defined as ℒG=TrG−DG, where DG is the distance matrix of G and TrG is the diagonal matrix of vertex transmissions of G.
Xiaoling Zhang, Jiajia Zhou
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Organic Materials of Tomorrow: Horizons of Artificial Intelligence
Advanced Materials, EarlyView.This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
Considering spatiotemporal evolutionary information in dynamic multi‐objective optimisation
CAAI Transactions on Intelligence Technology, EarlyView., 2023 Abstract Preserving population diversity and providing knowledge, which are two core tasks in the dynamic multi‐objective optimisation (DMO), are challenging since the sampling space is time‐ and space‐varying. Therefore, the spatiotemporal property of evolutionary information needs to be considered in the DMO.
Qinqin Fan +3 more
wiley +1 more source
Orchestrating Anion–π+ Interactions to Accelerate Metal‐Free Room‐Temperature Phosphorescence
Angewandte Chemie, EarlyView.Tuning anion–π+ interactions in pyridinium iodide contact ion pairs enables ultrafast metal‐free room‐temperature phosphorescence (540–605 nm) with radiative rates up to 5.2×105 s−1. Strong iodide→π+ charge‐transfer coupling, enhanced spin–orbit interactions, and dynamic ion‐pair organization accelerate intersystem crossing and emission, establishing ...
Eetu Hakkarainen +12 more
wiley +2 more sources
On Minimum Algebraic Connectivity of Tricyclic Graphs [PDF]
Mathematics Interdisciplinary ResearchConsider a simple, undirected graph $ G=(V,E)$, where $A$ represents the adjacency matrix and $Q$ represents the Laplacian matrix of $G$. The second smallest eigenvalue of Laplacian matrix of $G$ is called the algebraic connectivity of $G$.
Hassan Taheri, Gholam Hossein Fath-Tabar
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