登录 注册

Cluster-Graph Edit Distance: Metric Proxies, Multiscale Embeddings, and Complexity

🔗 访问原文
🔗 Access Paper

📝 摘要
Abstract

The cluster graphs on $n$ vertices, the disjoint unions of complete graphs, have the integer partitions of $n$ as their isomorphism classes, and the quotient edit distance $q^*(λ,μ)=\min_{σ\in S_n}|E(G_λ)\triangleσE(G_μ)|$ makes that set a metric space. Its metric geometry and its computational complexity both issue from one identity: $q^*$ is an affine function of the maximum of $\lVert X\rVert_F^2$ over the contingency tables with margins $λ$ and $μ$. Combinatorially, it yields two explicit $\ell_1$ models: the vertex-mass metric $δ_1$ on sorted degree sequences, with $\frac12δ_1\le q^*<\frac32δ_1$ and both constants optimal, and the block-energy metric $B$ on the vectors $\bigl(\binom{λ_i}2\bigr)_i$, with $q^*\le B\le2q^*-1$ by a per-table refinement measuring how far an alignment is from a block bijection. Hence $c_1(\mathcal K_n)\le2$, and an $O(n\log n)$-time algorithm returns an alignment of cost below $2q^*$ with the certificate $q^*\in[\lceil(B+1)/2\rceil,B]$. The Euclidean distortion of the class is $c_2(\mathcal K_n)=Θ(n^{1/4})$; against it we measure the weighted dyadic sums $F^{(γ)}$ of the Ferrers staircase, of dimension below $4n$ and computable in $O(n)$ time. The unweighted member has distortion exactly $Θ(n^{1/4}\sqrt{\log n})$, while the critical weight $γ=\frac14$ improves this unconditionally to $O(n^{1/4}(\log n)^{1/4})$ through an inverse energy inequality proved from the quantization of staircase jumps; removing the residual $(\log n)^{1/4}$ is reduced to one inverse inequality on the realizable cone. Computationally, the same identity gives a classification: deciding $q^*(λ,μ)\le Q$ is strongly NP-complete, evaluation is strongly NP-hard and admits no FPTAS unless $\mathrm P=\mathrm{NP}$, while the farthest alignment is polynomial-time solvable.

📊 文章统计
Article Statistics

基础数据
Basic Stats

126 浏览
Views
0 下载
Downloads
27 引用
Citations

引用趋势
Citation Trend

阅读国家分布
Country Distribution

阅读机构分布
Institution Distribution

月度浏览趋势
Monthly Views

相关关键词
Related Keywords

影响因子分析
Impact Analysis

4.20 综合评分
Overall Score
引用影响力
Citation Impact
浏览热度
View Popularity
下载频次
Download Frequency

📄 相关文章
Related Articles

海洋智能分析Ocean AI Analysis

正在分析中,请稍候…Analyzing, please wait…
海洋智能体 🌊
海洋智能体
AI科研助手 · 3665篇文献
我看到你正在阅读一篇文献,需要我帮你解读摘要、推荐相关论文,或者分析研究方法论吗?