Comparison of Different Properties of Graph Using Adjacency Matrix and Signless Laplacian Matix

Authors

  • Km. Priti Sahrawat Student, MSOSH, Maharishi University of Information Technology, Lucknow, Uttar Pradesh, India Author
  • Dr. Ashish Kumar Assistant Professor, MSOSH, Maharishi University of Information Technology, Lucknow, Uttar Pradesh, India Author

DOI:

https://doi.org/10.32628/IJSRSET25122211

Keywords:

Signless Laplacian Spectrum, Adjacency Matrix, Graph Representation, Spectral Graph Theory, Eigenvalue Analysis, Graph Characterization

Abstract

This study highlights the advantages of using the Signless Laplacian spectrum over the traditional Adjacency matrix spectrum for graph representation. It demonstrates that the Signless Laplacian possesses greater representational power and stronger characterization properties, making it a more effective tool for analyzing graph structures. Particularly, in the case of Sierpinski graphs, the eigenvalue analysis of the Signless Laplacian matrix outperforms that of the Adjacency matrix, reinforcing its utility in encoding and interpreting graph properties.

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References

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Published

03-05-2025

Issue

Section

Research Articles

How to Cite

[1]
Km. Priti Sahrawat and Dr. Ashish Kumar, “Comparison of Different Properties of Graph Using Adjacency Matrix and Signless Laplacian Matix”, Int J Sci Res Sci Eng Technol, vol. 12, no. 3, pp. 01–05, May 2025, doi: 10.32628/IJSRSET25122211.

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