Multitree

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The butterfly network, a multitree used in distributed computation, showing in red the undirected tree induced by the subgraph reachable from one of its vertices. Butterfly multitree.svg
The butterfly network, a multitree used in distributed computation, showing in red the undirected tree induced by the subgraph reachable from one of its vertices.

In combinatorics and order theory, a multitree may describe either of two equivalent structures: a directed acyclic graph (DAG) in which there is at most one directed path between any two vertices, or equivalently in which the subgraph reachable from any vertex induces an undirected tree, or a partially ordered set (poset) that does not have four items a, b, c, and d forming a diamond suborder with abd and acd but with b and c incomparable to each other (also called a diamond-free poset [1] ).

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In computational complexity theory, multitrees have also been called strongly unambiguous graphs or mangroves; they can be used to model nondeterministic algorithms in which there is at most one computational path connecting any two states. [2]

Multitrees may be used to represent multiple overlapping taxonomies over the same ground set. [3] If a family tree may contain multiple marriages from one family to another, but does not contain marriages between any two blood relatives, then it forms a multitree. [4]

Equivalence between DAG and poset definitions

In a directed acyclic graph, if there is at most one directed path between any two vertices, or equivalently if the subgraph reachable from any vertex induces an undirected tree, then its reachability relation is a diamond-free partial order. Conversely, in a diamond-free partial order, the transitive reduction identifies a directed acyclic graph in which the subgraph reachable from any vertex induces an undirected tree.

Diamond-free families

A diamond-free family of sets is a family F of sets whose inclusion ordering forms a diamond-free poset. If D(n) denotes the largest possible diamond-free family of subsets of an n-element set, then it is known that

,

and it is conjectured that the limit is 2. [1]

A polytree, a directed acyclic graph formed by orienting the edges of an undirected tree, is a special case of a multitree.

The subgraph reachable from any vertex in a multitree is an arborescence rooted in the vertex, that is a polytree in which all edges are oriented away from the root.

The word "multitree" has also been used to refer to a series–parallel partial order, [5] or to other structures formed by combining multiple trees.

Related Research Articles

<span class="mw-page-title-main">Tree (graph theory)</span> Undirected, connected and acyclic graph

In graph theory, a tree is an undirected graph in which any two vertices are connected by exactly one path, or equivalently a connected acyclic undirected graph. A forest is an undirected graph in which any two vertices are connected by at most one path, or equivalently an acyclic undirected graph, or equivalently a disjoint union of trees.

<span class="mw-page-title-main">Directed acyclic graph</span> Directed graph with no directed cycles

In mathematics, particularly graph theory, and computer science, a directed acyclic graph (DAG) is a directed graph with no directed cycles. That is, it consists of vertices and edges, with each edge directed from one vertex to another, such that following those directions will never form a closed loop. A directed graph is a DAG if and only if it can be topologically ordered, by arranging the vertices as a linear ordering that is consistent with all edge directions. DAGs have numerous scientific and computational applications, ranging from biology to information science to computation (scheduling).

<span class="mw-page-title-main">Hypergraph</span> Generalization of graph theory

In mathematics, a hypergraph is a generalization of a graph in which an edge can join any number of vertices. In contrast, in an ordinary graph, an edge connects exactly two vertices.

<span class="mw-page-title-main">Component (graph theory)</span> Maximal subgraph whose vertices can reach each other

In graph theory, a component of an undirected graph is a connected subgraph that is not part of any larger connected subgraph. The components of any graph partition its vertices into disjoint sets, and are the induced subgraphs of those sets. A graph that is itself connected has exactly one component, consisting of the whole graph. Components are sometimes called connected components.

This is a glossary of graph theory. Graph theory is the study of graphs, systems of nodes or vertices connected in pairs by lines or edges.

<span class="mw-page-title-main">Graph (discrete mathematics)</span> Vertices connected in pairs by edges

In discrete mathematics, and more specifically in graph theory, a graph is a structure amounting to a set of objects in which some pairs of the objects are in some sense "related". The objects correspond to mathematical abstractions called vertices and each of the related pairs of vertices is called an edge. Typically, a graph is depicted in diagrammatic form as a set of dots or circles for the vertices, joined by lines or curves for the edges. Graphs are one of the objects of study in discrete mathematics.

<span class="mw-page-title-main">Hasse diagram</span> Visual depiction of a partially ordered set

In order theory, a Hasse diagram is a type of mathematical diagram used to represent a finite partially ordered set, in the form of a drawing of its transitive reduction. Concretely, for a partially ordered set one represents each element of as a vertex in the plane and draws a line segment or curve that goes upward from one vertex to another vertex whenever covers . These curves may cross each other but must not touch any vertices other than their endpoints. Such a diagram, with labeled vertices, uniquely determines its partial order.

<span class="mw-page-title-main">Spanning tree</span> Tree which includes all vertices of a graph

In the mathematical field of graph theory, a spanning treeT of an undirected graph G is a subgraph that is a tree which includes all of the vertices of G. In general, a graph may have several spanning trees, but a graph that is not connected will not contain a spanning tree. If all of the edges of G are also edges of a spanning tree T of G, then G is a tree and is identical to T.

<span class="mw-page-title-main">Strongly connected component</span> Partition of a graph whose components are reachable from all vertices

In the mathematical theory of directed graphs, a graph is said to be strongly connected if every vertex is reachable from every other vertex. The strongly connected components of an arbitrary directed graph form a partition into subgraphs that are themselves strongly connected. It is possible to test the strong connectivity of a graph, or to find its strongly connected components, in linear time (that is, Θ(V + E)).

<span class="mw-page-title-main">Connectivity (graph theory)</span> Basic concept of graph theory

In mathematics and computer science, connectivity is one of the basic concepts of graph theory: it asks for the minimum number of elements that need to be removed to separate the remaining nodes into two or more isolated subgraphs. It is closely related to the theory of network flow problems. The connectivity of a graph is an important measure of its resilience as a network.

<span class="mw-page-title-main">Polytree</span>

In mathematics, and more specifically in graph theory, a polytree is a directed acyclic graph whose underlying undirected graph is a tree. In other words, if we replace its directed edges with undirected edges, we obtain an undirected graph that is both connected and acyclic.

In the mathematical discipline of graph theory, a feedback vertex set (FVS) of a graph is a set of vertices whose removal leaves a graph without cycles. Equivalently, each FVS contains at least one vertex of any cycle in the graph. The feedback vertex set number of a graph is the size of a smallest feedback vertex set. The minimum feedback vertex set problem is an NP-complete problem; it was among the first problems shown to be NP-complete. It has wide applications in operating systems, database systems, and VLSI chip design.

<span class="mw-page-title-main">Feedback arc set</span> Edges that hit all cycles in a graph

In graph theory and graph algorithms, a feedback arc set or feedback edge set in a directed graph is a subset of the edges of the graph that contains at least one edge out of every cycle in the graph. Removing these edges from the graph breaks all of the cycles, producing a directed acyclic graph, an acyclic subgraph of the given graph. The feedback arc set with the fewest possible edges is the minimum feedback arc set and its removal leaves the maximum acyclic subgraph; weighted versions of these optimization problems are also used. If a feedback arc set is minimal, meaning that removing any edge from it produces a subset that is not a feedback arc set, then it has an additional property: reversing all of its edges, rather than removing them, produces a directed acyclic graph.

In graph theory, Schnyder's theorem is a characterization of planar graphs in terms of the order dimension of their incidence posets. It is named after Walter Schnyder, who published its proof in 1989.

<span class="mw-page-title-main">Intersection graph</span> Graph representing intersections between given sets

In graph theory, an intersection graph is a graph that represents the pattern of intersections of a family of sets. Any graph can be represented as an intersection graph, but some important special classes of graphs can be defined by the types of sets that are used to form an intersection representation of them.

<span class="mw-page-title-main">Pseudoforest</span> Graph with one cycle per component

In graph theory, a pseudoforest is an undirected graph in which every connected component has at most one cycle. That is, it is a system of vertices and edges connecting pairs of vertices, such that no two cycles of consecutive edges share any vertex with each other, nor can any two cycles be connected to each other by a path of consecutive edges. A pseudotree is a connected pseudoforest.

In the study of graph algorithms, an implicit graph representation is a graph whose vertices or edges are not represented as explicit objects in a computer's memory, but rather are determined algorithmically from some other input, for example a computable function.

<span class="mw-page-title-main">Series-parallel partial order</span>

In order-theoretic mathematics, a series-parallel partial order is a partially ordered set built up from smaller series-parallel partial orders by two simple composition operations.

In mathematics, in the areas of order theory and combinatorics, Mirsky's theorem characterizes the height of any finite partially ordered set in terms of a partition of the order into a minimum number of antichains. It is named for Leon Mirsky (1971) and is closely related to Dilworth's theorem on the widths of partial orders, to the perfection of comparability graphs, to the Gallai–Hasse–Roy–Vitaver theorem relating longest paths and colorings in graphs, and to the Erdős–Szekeres theorem on monotonic subsequences.

<span class="mw-page-title-main">Sumner's conjecture</span>

Sumner's conjecture states that every orientation of every -vertex tree is a subgraph of every -vertex tournament. David Sumner, a graph theorist at the University of South Carolina, conjectured in 1971 that tournaments are universal graphs for polytrees. The conjecture was proven for all large by Daniela Kühn, Richard Mycroft, and Deryk Osthus.

References

  1. 1 2 Griggs, Jerrold R.; Li, Wei-Tian; Lu, Linyuan (2010), Diamond-free families, arXiv: 1010.5311 , Bibcode:2010arXiv1010.5311G .
  2. Allender, Eric; Lange, Klaus-Jörn (1996), "StUSPACE(log n) ⊆ DSPACE(log2n/log log n)", Algorithms and Computation, 7th International Symposium, ISAAC '96, Osaka, Japan, December 16–18, 1996, Proceedings, Lecture Notes in Computer Science, vol. 1178, Springer-Verlag, pp. 193–202, doi:10.1007/BFb0009495 .
  3. Furnas, George W.; Zacks, Jeff (1994), "Multitrees: enriching and reusing hierarchical structure", Proc. SIGCHI conference on Human Factors in Computing Systems (CHI '94), pp. 330–336, doi:10.1145/191666.191778, S2CID   18710118 .
  4. McGuffin, Michael J.; Balakrishnan, Ravin (2005), "Interactive visualization of genealogical graphs", IEEE Symposium on Information Visualization, Los Alamitos, California, US: IEEE Computer Society, p. 3, doi:10.1109/INFOVIS.2005.22, S2CID   15449409 .
  5. Jung, H. A. (1978), "On a class of posets and the corresponding comparability graphs", Journal of Combinatorial Theory, Series B, 24 (2): 125–133, doi: 10.1016/0095-8956(78)90013-8 , MR   0491356 .