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arxiv: 2412.14936 · v1 · pith:6T4OIUBEnew · submitted 2024-12-19 · 🧮 math.CO

An Optimization Approach to Degree Deviation and Spectral Radius

classification 🧮 math.CO
keywords degreedeltafracdeviationmboxsqrtcaseseigenvalue
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For a finite, simple, and undirected graph $G$ with $n$ vertices and average degree $d$, Nikiforov introduced the degree deviation of $G$ as $s=\sum_{u\in V(G)}\left|d_G(u)-d\right|$. Provided that $G$ has largest eigenvalue $\lambda$, minimum degree at least $\delta$, and maximum degree at most $\Delta$, where $0\leq\delta<d<\Delta<n$, we show $$s\leq \frac{2n(\Delta-d)(d-\delta)}{\Delta-\delta} \,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\mbox{and}\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\, \lambda \geq \begin{cases} \frac{d^2n}{\sqrt{d^2n^2-s^2}} & \mbox{, if } s\leq \frac{dn}{\sqrt{2}},\\[3mm] \frac{2s}{n} & \mbox{, if } s> \frac{dn}{\sqrt{2}}. \end{cases}$$ Our results are based on a smoothing technique relating the degree deviation and the largest eigenvalue to low-dimensional non-linear optimization problems.

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