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1. Independent dominating sets in graphs of girth five

   https://doi.org/10.1017/s0963548320000279  

   Harutyunyan, Ararat; Horn, Paul; Verstraete, Jacques (May 2021, Combinatorics, Probability and Computing)

   Abstract Let $$\gamma(G)$$ and $${\gamma _ \circ }(G)$$ denote the sizes of a smallest dominating set and smallest independent dominating set in a graph G, respectively. One of the first results in probabilistic combinatorics is that if G is an n -vertex graph of minimum degree at least d , then $$\begin{equation}\gamma(G) \leq \frac{n}{d}(\log d + 1).\end{equation}$$ In this paper the main result is that if G is any n -vertex d -regular graph of girth at least five, then $$\begin{equation}\gamma_(G) \leq \frac{n}{d}(\log d + c)\end{equation}$$ for some constant c independent of d . This result is sharp in the sense that as $$d \rightarrow \infty$$ , almost all d -regular n -vertex graphs G of girth at least five have $$\begin{equation}\gamma_(G) \sim \frac{n}{d}\log d.\end{equation}$$ Furthermore, if G is a disjoint union of $${n}/{(2d)}$$ complete bipartite graphs $$K_{d,d}$$ , then $${\gamma_\circ}(G) = \frac{n}{2}$$ . We also prove that there are n -vertex graphs G of minimum degree d and whose maximum degree grows not much faster than d log d such that $${\gamma_\circ}(G) \sim {n}/{2}$$ as $$d \rightarrow \infty$$ . Therefore both the girth and regularity conditions are required for the main result. 

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2. Triangle-degrees in graphs and tetrahedron coverings in 3-graphs

   https://doi.org/10.1017/S0963548320000061  

   Falgas-Ravry, Victor; Markström, Klas; Zhao, Yi (March 2021, Combinatorics, Probability and Computing)

   null (Ed.)

   Abstract We investigate a covering problem in 3-uniform hypergraphs (3-graphs): Given a 3-graph F , what is c 1 ( n , F ), the least integer d such that if G is an n -vertex 3-graph with minimum vertex-degree $$\delta_1(G)>d$$ then every vertex of G is contained in a copy of F in G ? We asymptotically determine c 1 ( n , F ) when F is the generalized triangle $$K_4^{(3)-}$$ , and we give close to optimal bounds in the case where F is the tetrahedron $$K_4^{(3)}$$ (the complete 3-graph on 4 vertices). This latter problem turns out to be a special instance of the following problem for graphs: Given an n -vertex graph G with $m> n^2/4$ edges, what is the largest t such that some vertex in G must be contained in t triangles? We give upper bound constructions for this problem that we conjecture are asymptotically tight. We prove our conjecture for tripartite graphs, and use flag algebra computations to give some evidence of its truth in the general case. 

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3. Approximate Mining of Frequent -Subgraph Patterns in Evolving Graphs

   https://doi.org/10.1145/3442590  

   Nasir, Muhammad Anis; Aslay, Cigdem; Morales, Gianmarco De; Riondato, Matteo (April 2021, ACM Transactions on Knowledge Discovery from Data)

   null (Ed.)

   “Perhaps he could dance first and think afterwards, if it isn’t too much to ask him.” S. Beckett, Waiting for Godot Given a labeled graph, the collection of -vertex induced connected subgraph patterns that appear in the graph more frequently than a user-specified minimum threshold provides a compact summary of the characteristics of the graph, and finds applications ranging from biology to network science. However, finding these patterns is challenging, even more so for dynamic graphs that evolve over time, due to the streaming nature of the input and the exponential time complexity of the problem. We study this task in both incremental and fully-dynamic streaming settings, where arbitrary edges can be added or removed from the graph. We present TipTap , a suite of algorithms to compute high-quality approximations of the frequent -vertex subgraphs w.r.t. a given threshold, at any time (i.e., point of the stream), with high probability. In contrast to existing state-of-the-art solutions that require iterating over the entire set of subgraphs in the vicinity of the updated edge, TipTap operates by efficiently maintaining a uniform sample of connected -vertex subgraphs, thanks to an optimized neighborhood-exploration procedure. We provide a theoretical analysis of the proposed algorithms in terms of their unbiasedness and of the sample size needed to obtain a desired approximation quality. Our analysis relies on sample-complexity bounds that use Vapnik–Chervonenkis dimension, a key concept from statistical learning theory, which allows us to derive a sufficient sample size that is independent from the size of the graph. The results of our empirical evaluation demonstrates that TipTap returns high-quality results more efficiently and accurately than existing baselines. 

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4. Finding Most-Shattering Minimum Vertex Cuts of Polylogarithmic Size in Near-Linear Time

   https://doi.org/10.4230/LIPIcs.ICALP.2024.87  

   Hua, Kevin; Li, Daniel; Park, Jaewoo; Saranurak, Thatchaphol (January 2024, Schloss Dagstuhl – Leibniz-Zentrum für Informatik)

   Bringmann, Karl; Grohe, Martin; Puppis, Gabriele; Svensson, Ola (Ed.)

   We show the first near-linear time randomized algorithms for listing all minimum vertex cuts of polylogarithmic size that separate the graph into at least three connected components (also known as shredders) and for finding the most shattering one, i.e., the one maximizing the number of connected components. Our algorithms break the quadratic time bound by Cheriyan and Thurimella (STOC'96) for both problems that has been unimproved for more than two decades. Our work also removes an important bottleneck to near-linear time algorithms for the vertex connectivity augmentation problem (Jordan '95) and finding an even-length directed cycle in a graph, a problem shown to be equivalent to many other fundamental problems (Vazirani and Yannakakis '90, Robertson et al. '99). Note that it is necessary to list only minimum vertex cuts that separate the graph into at least three components because there can be an exponential number of minimum vertex cuts in general. To obtain a near-linear time algorithm, we have extended techniques in local flow algorithms developed by Forster et al. (SODA'20) to list shredders on a local scale. We also exploit fast queries to a pairwise vertex connectivity oracle subject to vertex failures (Long and Saranurak FOCS'22, Kosinas ESA'23). This is the first application of using connectivity oracles subject to vertex failures to speed up a static graph algorithm. 

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5. Computing Volumes of Adjacency Polytopes via Draconian Sequences

   https://doi.org/10.37236/9768  

   Davis, Robert; Chen, Tianran (January 2022, The Electronic Journal of Combinatorics)

   Adjacency polytopes appear naturally in the study of nonlinear emergent phenomena in complex networks. The ``"PQ-type" adjacency polytope, denoted $$\nabla^{\mathrm{PQ}}_G$$ and which is the focus of this work, encodes rich combinatorial information about power-flow solutions in sparse power networks that are studied in electric engineering. Of particular importance is the normalized volume of such an adjacency polytope, which provides an upper bound on the number of distinct power-flow solutions. In this article we show that the problem of computing normalized volumes for $$\nabla^{\mathrm{PQ}}_G$$ can be rephrased as counting $D(G)$-draconian sequences where $D(G)$ is a certain bipartite graph associated to the network. We prove recurrences for all networks with connectivity at most $$1$$ and, for $$2$$-connected graphs under certain restrictions, we give recurrences for subdividing an edge and taking the join of an edge with a new vertex. Together, these recurrences imply a simple, non-recursive formula for the normalized volume of $$\nabla^{\mathrm{PQ}}_G$$ when $$G$$ is part of a large class of outerplanar graphs; we conjecture that the formula holds for all outerplanar graphs. Explicit formulas for several other (non-outerplanar) classes are given. Further, we identify several important classes of graphs $$G$$ which are planar but not outerplanar that are worth additional study. 

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