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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
Moreover, we give new results on Laplacian energy.
📌 3 Key Takeaways
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Objective & Hypothesis:Let G denote the set of all simple graphs with n vertices and m edges.
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Key Findings & Data:These results yield criterions for deciding when two graphs are almost A-equienergetic.
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Conclusion & Impact:Moreover, we give new results on Laplacian energy.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:(A-) energy of graph · almost (A-) equienergetic graphs
Abstract
Let G denote the set of all simple graphs with n vertices and m edges. In this paper, for a given type of graph Hermite matrix A, we determine the average values of the difference between A-energies of two graphs randomly chosen from G . These results yield criterions for deciding when two graphs are almost A-equienergetic. Our results generalize some previous results in the literature. Moreover, we give new results on Laplacian energy.
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Cite This Article
Altındağ, İ. (2020). Generalization for the Average Value of the Difference Between the Energies of Two Graphs. Gazi University Journal of Science, Volume: 33 Issue: 1. https://doi.org/10.35378/gujs.532697