On the complexity of recognizing S-composite and S-prime graphs

https://www.florian-lehner.net/pdf/hypergraph-product.pdf

Fast Factorization of Cartesian products of (Directed) Hypergraphs

Several variants of hypergraph products have been introduced as generalizations of the strong and direct products of graphs. Here we show that only some of them are associative. In addition to the Cartesian product, these are the minimal rank preserving direct product, and the normal product. Counter-examples are given for the strong product as well as the non-rank-preserving and the maximal rank preserving direct product.

Associativity and Non-Associativity of Some Hypergraph Products

This work is concerned with the prime factor decomposition (PFD) of strong product graphs. A new quasi-linear time algorithm for the PFD with respect to the strong product for arbitrary, finite, connected, undirected graphs is derived. Moreover, since most graphs are prime although they can have a product-like structure, also known as approximate graph products, the practical application of the well-known "classical" prime factorization algorithm is strictly limited. This new PFD algorithm is based on a local approach that covers a graph by small factorizable subgraphs and then utilizes this information to derive the global factors. Therefore, we can take advantage of this approach and derive in addition a method for the recognition of approximate graph products.

A Local Prime Factor Decomposition Algorithm for Strong Product Graphs.

Cartesian products of graphs and hypergraphs have been studied since the 1960s. For (un)directed hypergraphs, unique \emph{prime factor decomposition (PFD)} results with respect to the Cartesian product are known. However, there is still a lack of algorithms, that compute the PFD of directed hypergraphs with respect to the Cartesian product. 
In this contribution, we focus on the algorithmic aspects for determining the Cartesian prime factors of a finite, connected, directed hypergraph and present a first polynomial time algorithm to compute its PFD. In particular, the algorithm has time complexity $O(|E||V|r^2)$ for hypergraphs $H=(V,E)$, where the rank $r$ is the maximum number of vertices contained in an hyperedge of $H$. If $r$ is bounded, then this algorithm performs even in $O(|E|\log^2(|V|))$ time. Thus, our method additionally improves also the time complexity of PFD-algorithms designed for undirected hypergraphs that have time complexity $O(|E||V|r^6\Delta^6)$, where $\Delta$ is the maximum number of hyperedges a vertex is contained in.

Fast Factorization of Cartesian products of Hypergraphs

Strong Products of Hypergraphs: Unique Prime Factorization Theorems and Algorithms

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Strong Products of Hypergraphs: Unique Prime Factorization Theorems and Algorithms