Rook's graph | |
---|---|
Vertices | nm |
Edges | nm(n + m)/2 −nm |
Diameter | 2 |
Girth | 3 (if max(n, m) ≥ 3) |
Chromatic number | max(n, m) |
Spectrum | {m + n− 2, m− 2, n− 2, −2} |
Properties | |
Table of graphs and parameters |
In graph theory, a rook's graph is an undirected graph that represents all legal moves of the rook chess piece on a chessboard. Each vertex of a rook's graph represents a square on a chessboard, and there is an edge between any two squares sharing a row (rank) or column (file), the squares that a rook can move between. These graphs can be constructed for chessboards of any rectangular shape. Although rook's graphs have only minor significance in chess lore, they are more important in the abstract mathematics of graphs through their alternative constructions: rook's graphs are the Cartesian product of two complete graphs, and are the line graphs of complete bipartite graphs. The square rook's graphs constitute the two-dimensional Hamming graphs.
Rook's graphs are highly symmetric, having symmetries taking every vertex to every other vertex. In rook's graphs defined from square chessboards, more strongly, every two edges are symmetric, and every pair of vertices is symmetric to every other pair at the same distance in moves (making the graph distance-transitive). For rectangular chessboards whose width and height are relatively prime, the rook's graphs are circulant graphs. With one exception, the rook's graphs can be distinguished from all other graphs using only two properties: the numbers of triangles each edge belongs to, and the existence of a unique 4-cycle connecting each nonadjacent pair of vertices.
Rook's graphs are perfect graphs. In other words, every subset of chessboard squares can be colored so that no two squares in a row or column have the same color, using a number of colors equal to the maximum number of squares from the subset in any single row or column (the clique number of the induced subgraph). This class of induced subgraphs are a key component of a decomposition of perfect graphs used to prove the strong perfect graph theorem, which characterizes all perfect graphs. The independence number and domination number of a rook's graph both equal the smaller of the chessboard's width and height. In terms of chess, the independence number is the maximum number of rooks that can be placed without attacking each other; the domination number is the minimum number needed to attack all unoccupied board squares. Rook's graphs are well-covered graphs, meaning that placing non-attacking rooks one at a time can never get stuck until a set of maximum size is reached.
An n × m rook's graph represents the moves of a rook on an n × m chessboard. [1] Its vertices represent the squares of the chessboard, and may be given coordinates (x, y), where 1 ≤ x ≤ n and 1 ≤ y ≤ m. Two vertices with coordinates (x1, y1) and (x2, y2) are adjacent if and only if either x1 = x2 or y1 = y2. (If x1 = x2, the vertices share a file and are connected by a vertical rook move; if y1 = y2, they share a rank and are connected by a horizontal rook move.) [1]
The squares of a single rank or file are all directly connected to each other, so each rank and file forms a clique—a subset of vertices forming a complete graph. The whole rook's graph for an n × m chessboard can be formed from these two kinds of cliques, as the Cartesian product of graphs Kn ◻ Km. [2] Because the rook's graph for a square chessboard is the Cartesian product of equal-size cliques, it is an example of a Hamming graph. Its dimension as a Hamming graph is two, and every two-dimensional Hamming graph is a rook's graph for a square chessboard. [3] Square rook's graphs are also called "Latin square graphs"; applied to a Latin square, its edges describe pairs of squares that cannot contain the same value. [4] The Sudoku graphs are rook's graphs with some additional edges, connecting squares of a Sudoku puzzle that should have unequal values. [5]
Geometrically, the rook's graphs can be formed by sets of the vertices and edges (the skeletons) of a family of convex polytopes, the Cartesian products of pairs of neighborly polytopes. [6] For instance, the 3-3 duoprism is a four-dimensional shape formed as the Cartesian product of two triangles, and has a 3 × 3 rook's graph as its skeleton. [7]
Moon (1963) and Hoffman (1964) observe that the rook's graph (or equivalently, as they describe it, the line graph of the complete bipartite graph ) has all of the following properties:
They show that except in the case , these properties uniquely characterize the rook's graph. That is, the rook's graphs are the only graphs with these numbers of vertices, edges, triangles per edge, and with a unique 4-cycle through each two non-adjacent vertices. [8] [9]
When , these conditions may be abbreviated by stating that an rook's graph is a strongly regular graph with parameters . These parameters describe the number of vertices, the number of edges per vertex, the number of triangles per edge, and the number of shared neighbors for two non-adjacent vertices, respectively. [1] Conversely, every strongly regular graph with these parameters must be an rook's graph, unless . [8] [9]
When , there is another strongly regular graph, the Shrikhande graph, with the same parameters as the rook's graph. [10] The Shrikhande graph obeys the same properties listed by Moon and Moser. It can be distinguished from the rook's graph in that the neighborhood of each vertex in the Shrikhande graph is connected to form a -cycle. In contrast, in the rook's graph, the neighborhood of each vertex forms two triangles, one for its rank and another for its file, without any edges from one part of the neighborhood to the other. [11] Another way of distinguishing the rook's graph from the Shrikhande graph uses clique cover numbers: the rook's graph can be covered by four cliques (the four ranks or the four files of the chessboard) whereas six cliques are needed to cover the Shrikhande graph. [10]
Rook's graphs are vertex-transitive, meaning that they have symmetries taking every vertex to every other vertex. This implies that every vertex has an equal number of edges: they are -regular. The rook's graphs are the only regular graphs formed from the moves of standard chess pieces in this way. [12] When , the symmetries of the rook's graph are formed by independently permuting the rows and columns of the graph, so the automorphism group of the graph has elements. When , the graph has additional symmetries that swap the rows and columns, so the number of automorphisms is . [13]
Any two vertices in a rook's graph are either at distance one or two from each other, according to whether they are adjacent or nonadjacent respectively. Any two nonadjacent vertices may be transformed into any other two nonadjacent vertices by a symmetry of the graph. When the rook's graph is not square, the pairs of adjacent vertices fall into two orbits of the symmetry group according to whether they are adjacent horizontally or vertically, but when the graph is square any two adjacent vertices may also be mapped into each other by a symmetry and the graph is therefore distance-transitive. [14]
When and are relatively prime, the symmetry group of the rook's graph contains as a subgroup the cyclic group that acts by cyclically permuting the vertices. Therefore, in this case, the rook's graph is a circulant graph. [15]
Square rook's graphs are connected-homogeneous, meaning that every isomorphism between two connected induced subgraphs can be extended to an automorphism of the whole graph. [16]
A rook's graph can also be viewed as the line graph of a complete bipartite graph Kn,m — that is, it has one vertex for each edge of Kn,m, and two vertices of the rook's graph are adjacent if and only if the corresponding edges of the complete bipartite graph share a common endpoint. [2] [17] In this view, an edge in the complete bipartite graph from the ith vertex on one side of the bipartition to the jth vertex on the other side corresponds to a chessboard square with coordinates (i, j). [1]
Any bipartite graph is a subgraph of a complete bipartite graph, and correspondingly any line graph of a bipartite graph is an induced subgraph of a rook's graph. [18] The line graphs of bipartite graphs are perfect: in them, and in any of their induced subgraphs, the number of colors needed in any vertex coloring is the same as the number of vertices in the largest complete subgraph. Line graphs of bipartite graphs form an important family of perfect graphs: they are one of a small number of families used by Chudnovsky et al. (2006) to characterize the perfect graphs and to show that every graph with no odd hole and no odd antihole is perfect. [19] In particular, rook's graphs are themselves perfect.
Because a rook's graph is perfect, the number of colors needed in any coloring of the graph is just the size of its largest clique. The cliques of a rook's graph are the subsets of a single row or a single column, and the largest of these have size max(m, n), so this is also the chromatic number of the graph. An n-coloring of an n×n rook's graph may be interpreted as a Latin square: it describes a way of filling the rows and columns of an n×n grid with n different values in such a way that the same value does not appear twice in any row or column. [20] In the same way, a coloring of a rectangular rook's graph corresponds to a Latin rectangle. [21] Although finding an optimal coloring of a rook's graph is straightforward, it is NP-complete to determine whether a partial coloring can be extended to a coloring of the whole graph (this problem is called precoloring extension). Equivalently, it is NP-complete to determine whether a partial Latin square can be completed to a full Latin square. [22]
a | b | c | d | e | f | g | h | ||
8 | 8 | ||||||||
7 | 7 | ||||||||
6 | 6 | ||||||||
5 | 5 | ||||||||
4 | 4 | ||||||||
3 | 3 | ||||||||
2 | 2 | ||||||||
1 | 1 | ||||||||
a | b | c | d | e | f | g | h |
An independent set in a rook's graph is a set of vertices, no two of which belong to the same row or column of the graph; in chess terms, it corresponds to a placement of rooks no two of which attack each other. Perfect graphs may also be described as the graphs in which, in every induced subgraph, the size of the largest independent set is equal to the number of cliques in a partition of the graph's vertices into a minimum number of cliques. In a rook's graph, the sets of rows or the sets of columns (whichever has fewer sets) form such an optimal partition. The size of the largest independent set in the graph is therefore min(m, n). [1]
Rook's graphs are well-covered graphs: every independent set in a rook's graph can be extended to a maximum independent set, and every maximal independent set in a rook's graph has the same size, min(m, n). [23]
The domination number of a graph is the minimum cardinality among all dominating sets. On the rook's graph a set of vertices is a dominating set if and only if their corresponding squares either occupy, or are a rook's move away from, all squares on the m×n board. For the m×n board the domination number is min(m, n). [24]
On the rook's graph a k-dominating set is a set of vertices whose corresponding squares attack all other squares (via a rook's move) at least k times. A k-tuple dominating set on the rook's graph is a set of vertices whose corresponding squares attack all other squares at least k times and are themselves attacked at least k− 1 times. The minimum cardinality among all k-dominating and k-tuple dominating sets are the k-domination number and the k-tuple domination number, respectively. On the square board, and for even k, the k-domination number is nk/2 when n ≥ (k2− 2k)/4 and k < 2n. In a similar fashion, the k-tuple domination number is n(k + 1)/2 when k is odd and less than 2n. [25]
Every rook's graph contains a Hamiltonian cycle. [26] However, these cycles may involve moves between squares that are far apart within a single row or column of the chessboard. Instead, the study of "rook's tours", in the mathematics of chess, has generally concentrated on a special case of these Hamiltonian cycles where the rook is restricted to move only to adjacent squares. These single-step rook's tours only exist on boards with an even number of squares. They play a central role in the proof of Gomory's theorem that, if two squares of opposite colors are removed from a standard chessboard, the remaining squares can always be covered by dominoes. [27] They are featured alongside knight's tours in the first work to discuss chess-piece tours, the 9th century Sanskrit Kavyalankara of Rudrata. [28]
The spectrum of a rook's graph (the eigenvalues of its adjacency matrix) consists of the four eigenvalues , , , and . Because these are all integers, rook's graphs are integral graphs. There are only three classes of graphs (and finitely many exceptional graphs) that can have four eigenvalues with one of the four being ; one of the three classes is the class of rook's graphs. For most combinations of and , the rook's graph is spectrally unique: no other graph has the same spectrum. In particular this is true when or , or when the two numbers and sum to at least 18 and do not have the form . [29]
The graphs for which the neighbors of each vertex induce a rook's graph have been called locally grid. Examples include the Johnson graphs , for which the neighbors of each vertex form a rook's graph. Other examples are known, and for some rook's graphs, a complete classification is known. For instance, there are two graphs whose neighborhoods are all rook's graphs: they are the Johnson graph , and the complement graph of a rook's graph. [30]
In the mathematical field of graph theory, a bipartite graph is a graph whose vertices can be divided into two disjoint and independent sets and , that is, every edge connects a vertex in to one in . Vertex sets and are usually called the parts of the graph. Equivalently, a bipartite graph is a graph that does not contain any odd-length cycles.
In the mathematical field of graph theory, a Hamiltonian path is a path in an undirected or directed graph that visits each vertex exactly once. A Hamiltonian cycle is a cycle that visits each vertex exactly once. A Hamiltonian path that starts and ends at adjacent vertices can be completed by adding one more edge to form a Hamiltonian cycle, and removing any edge from a Hamiltonian cycle produces a Hamiltonian path. The computational problems of determining whether such paths and cycles exist in graphs are NP-complete; see Hamiltonian path problem for details.
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.
In graph theory, a clique is a subset of vertices of an undirected graph such that every two distinct vertices in the clique are adjacent. That is, a clique of a graph is an induced subgraph of that is complete. Cliques are one of the basic concepts of graph theory and are used in many other mathematical problems and constructions on graphs. Cliques have also been studied in computer science: the task of finding whether there is a clique of a given size in a graph is NP-complete, but despite this hardness result, many algorithms for finding cliques have been studied.
In the mathematical field of graph theory, a complete bipartite graph or biclique is a special kind of bipartite graph where every vertex of the first set is connected to every vertex of the second set.
In the mathematical field of graph theory, an edge-transitive graph is a graph G such that, given any two edges e1 and e2 of G, there is an automorphism of G that maps e1 to e2.
In graph theory, a perfect graph is a graph in which the chromatic number equals the size of the maximum clique, both in the graph itself and in every induced subgraph. In all graphs, the chromatic number is greater than or equal to the size of the maximum clique, but they can be far apart. A graph is perfect when these numbers are equal, and remain equal after the deletion of arbitrary subsets of vertices.
In graph theory, the perfect graph theorem of László Lovász states that an undirected graph is perfect if and only if its complement graph is also perfect. This result had been conjectured by Berge, and it is sometimes called the weak perfect graph theorem to distinguish it from the strong perfect graph theorem characterizing perfect graphs by their forbidden induced subgraphs.
In the mathematical discipline of graph theory, the line graph of an undirected graph G is another graph L(G) that represents the adjacencies between edges of G. L(G) is constructed in the following way: for each edge in G, make a vertex in L(G); for every two edges in G that have a vertex in common, make an edge between their corresponding vertices in L(G).
In graph theory, a cograph, or complement-reducible graph, or P4-free graph, is a graph that can be generated from the single-vertex graph K1 by complementation and disjoint union. That is, the family of cographs is the smallest class of graphs that includes K1 and is closed under complementation and disjoint union.
In graph theory, a circulant graph is an undirected graph acted on by a cyclic group of symmetries which takes any vertex to any other vertex. It is sometimes called a cyclic graph, but this term has other meanings.
In the mathematical area of graph theory, Kőnig's theorem, proved by Dénes Kőnig, describes an equivalence between the maximum matching problem and the minimum vertex cover problem in bipartite graphs. It was discovered independently, also in 1931, by Jenő Egerváry in the more general case of weighted graphs.
In graph theory, the hypercube graphQn is the graph formed from the vertices and edges of an n-dimensional hypercube. For instance, the cube graph Q3 is the graph formed by the 8 vertices and 12 edges of a three-dimensional cube. Qn has 2n vertices, 2n – 1n edges, and is a regular graph with n edges touching each vertex.
In graph theory, an adjacent vertex of a vertex v in a graph is a vertex that is connected to v by an edge. The neighbourhood of a vertex v in a graph G is the subgraph of G induced by all vertices adjacent to v, i.e., the graph composed of the vertices adjacent to v and all edges connecting vertices adjacent to v.
In graph theory, an area of mathematics, a claw-free graph is a graph that does not have a claw as an induced subgraph.
Clique complexes, independence complexes, flag complexes, Whitney complexes and conformal hypergraphs are closely related mathematical objects in graph theory and geometric topology that each describe the cliques of an undirected graph.
In graph theory, a well-covered graph is an undirected graph in which the minimal vertex covers all have the same size. Here, a vertex cover is a set of vertices that touches all edges, and it is minimal if removing any vertex from it would leave some edge uncovered. Equivalently, well-covered graphs are the graphs in which all maximal independent sets have equal size. Well-covered graphs were defined and first studied by Michael D. Plummer in 1970.
In graph theory, a skew partition of a graph is a partition of its vertices into two subsets, such that the induced subgraph formed by one of the two subsets is disconnected and the induced subgraph formed by the other subset is the complement of a disconnected graph. Skew partitions play an important role in the theory of perfect graphs.
In graph theory, a branch of mathematics, a map graph is an undirected graph formed as the intersection graph of finitely many simply connected and internally disjoint regions of the Euclidean plane. The map graphs include the planar graphs, but are more general. Any number of regions can meet at a common corner, and when they do the map graph will contain a clique connecting the corresponding vertices, unlike planar graphs in which the largest cliques have only four vertices. Another example of a map graph is the king's graph, a map graph of the squares of the chessboard connecting pairs of squares between which the chess king can move.
The independence complex of a graph is a mathematical object describing the independent sets of the graph. Formally, the independence complex of an undirected graph G, denoted by I(G), is an abstract simplicial complex (that is, a family of finite sets closed under the operation of taking subsets), formed by the sets of vertices in the independent sets of G. Any subset of an independent set is itself an independent set, so I(G) is indeed closed under taking subsets.