Power Graphs of Finite Groups Determined by Hosoya Properties.

Entropy (Basel)

Department of Mathematical Sciences, University of Lakki Marwat, Lakki Marwat 28420, Pakistan.

Published: January 2022

Suppose G is a finite group. The power graph represented by P(G) of G is a graph, whose node set is G, and two different elements are adjacent if and only if one is an integral power of the other. The Hosoya polynomial contains much information regarding graph invariants depending on the distance. In this article, we discuss the Hosoya characteristics (the Hosoya polynomial and its reciprocal) of the power graph related to an algebraic structure formed by the symmetries of regular molecular gones. As a consequence, we determined the Hosoya index of the power graphs of the dihedral and the generalized groups. This information is useful in determining the renowned chemical descriptors depending on the distance. The total number of matchings in a graph Γ is known as the -index or Hosoya index. The -index is a well-known type of topological index, which is popular in combinatorial chemistry and can be used to deal with a variety of chemical characteristics in molecular structures.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8871142PMC
http://dx.doi.org/10.3390/e24020213DOI Listing

Publication Analysis

Top Keywords

power graphs
8
determined hosoya
8
power graph
8
hosoya polynomial
8
depending distance
8
hosoya
6
power
5
graph
5
graphs finite
4
finite groups
4

Similar Publications

We introduce a change of perspective on tensor network states that is defined by the computational graph of the contraction of an amplitude. The resulting class of states, which we refer to as tensor network functions, inherit the conceptual advantages of tensor network states while removing computational restrictions arising from the need to converge approximate contractions. We use tensor network functions to compute strict variational estimates of the energy on loopy graphs, analyze their expressive power for ground states, show that we can capture aspects of volume law time evolution, and provide a mapping of general feed-forward neural nets onto efficient tensor network functions.

View Article and Find Full Text PDF

Investigating time-independent and time-dependent diffusion phenomena using steady-state diffusion MRI.

Sci Rep

January 2025

Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.

Diffusion MRI is a leading method to non-invasively characterise brain tissue microstructure across multiple domains and scales. Diffusion-weighted steady-state free precession (DW-SSFP) is an established imaging sequence for post-mortem MRI, addressing the challenging imaging environment of fixed tissue with short T and low diffusivities. However, a current limitation of DW-SSFP is signal interpretation: it is not clear what diffusion 'regime' the sequence probes and therefore its potential to characterise tissue microstructure.

View Article and Find Full Text PDF

An Automated Approach for Domain-Specific Knowledge Graph Generation─Graph Measures and Characterization.

J Chem Inf Model

January 2025

Center for Engineering Concepts Development, Department of Mechanical Engineering, University of Maryland, College Park, Maryland 20742, United States.

In 2020, nearly 3 million scientific and engineering papers were published worldwide (White, K. Publications Output: U.S.

View Article and Find Full Text PDF

Machine learning reveals the dynamic importance of accessory sequences for outbreak clustering.

mBio

January 2025

Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia, Canada.

Unlabelled: Bacterial typing at whole-genome scales is now feasible owing to decreasing costs in high-throughput sequencing and the recent advances in computation. The unprecedented resolution of whole-genome typing is achieved by genotyping the variable segments of bacterial genomes that can fluctuate significantly in gene content. However, due to the transient and hypervariable nature of many accessory elements, the value of the added resolution in outbreak investigations remains disputed.

View Article and Find Full Text PDF

This study demonstrates the use of GPT-4 and variants, advanced language models readily accessible to many social scientists, in extracting political networks from text. This approach showcases the novel integration of GPT-4's capabilities in entity recognition, relation extraction, entity linking, and sentiment analysis into a single cohesive process. Based on a corpus of 1009 Chilean political news articles, the study validates the graph extraction method using 'legislative agreement', i.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!