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How many nonisomorphic rooted trees are there with six vertices?

Short Answer

Expert verified

Therefore, we have 20 nonisomorphic rooted trees with six vertices.

Step by step solution

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01

General form

Definition of rooted tree: A rooted tree is a tree in which one vertex has been designated as the root and every edge is directed away from the root.

Definition isomorphic and nonisomorphic: Two graphs\({{\bf{G}}_{\bf{1}}}{\bf{ = }}\left( {{{\bf{V}}_{\bf{1}}}{\bf{,}}{{\bf{E}}_{\bf{1}}}} \right)\) and \({{\bf{G}}_{\bf{2}}}{\bf{ = }}\left( {{{\bf{V}}_{\bf{2}}}{\bf{,}}{{\bf{E}}_{\bf{2}}}} \right)\)are isomorphic if there exists a one-to-one and onto functions\({\bf{f:}}{{\bf{V}}_{\bf{1}}} \to {{\bf{V}}_{\bf{2}}}\) such that \(\left( {{\bf{a,b}}} \right) \in {{\bf{G}}_{\bf{1}}}\) if and only if \(\left( {{\bf{f}}\left( {\bf{a}} \right){\bf{,f}}\left( {\bf{b}} \right)} \right) \in {{\bf{G}}_{\bf{2}}}\) for all a and b in \({{\bf{V}}_1}\). such a function f is called an isomorphism.Two simple graphs that are not isomorphic are called nonisomorphic.

02

Evaluate the nonisomorphic rooted tree

A nonisomorphic rooted tree with 6 vertices has height 1, 2, 3, 4, or 5.

Case (1): Height 5

There is only one possible nonisomorphic rooted tree with height 5, which is the rooted tree that represents a Path of length 5. The tree is shown below.

Case (2): Height 4

There are 4 possible nonisomorphic rooted tree with height 4 (whose longest path has length 4), because we need to attach the leaf of the rooted tree with a path of length 5 to one of the top four vertices.

Note: we can’t attach it to the 5th vertex, as that would result in tree with height 4.

The trees are shown below.

03

Evaluate the nonisomorphic rooted trees

Case (3):Height 3

There are 8 possible nonisomorphic rooted tree with height 3 (whose longest path has length 3), because if we start from a path with length 3, then we can attach the last two vertices to the same vertex of the top three vertices, we could attach the last two vertices to a different vertex of the top three vertices and we can attach the last two vertices in a path of length 2 to one of the top two vertices.

That is, \({\bf{3 + 3 + 2 = 8}}\).

The trees are shown below.

Case (4): Height 2

There are 6 possible nonisomorphic rooted tree with height 3 (whose longest path has length 3), because if we start from a path with length 2, then we can attach the last three vertices to the same vertex of the top two vertices, we could attach the two of the last two vertices to one of the top two vertices and remaining vertex to the other vertex among the top two vertices and we can attach two of the remaining three vertices as a path of length 2 to the root and then the remaining vertex can be attached to the root of a vertex at level 1.

That is, \(2{\bf{ + }}2{\bf{ + 2 = }}6\).

The trees are shown below.

Case (5): Height 1

There is only one possible nonisomorphic rooted tree with height 1 (whose longest path has length 1), because 5 vertices have to all be connected to the root.

The tree is shown below.

Conclusion: So, the total of nonisomorphic we note that the trees with 6 vertices are 20. That is, \({\bf{1 + 4 + 8 + 6 + 1 = 20}}\).

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Most popular questions from this chapter

Find the height of \({{\bf{B}}_{\bf{k}}}\). Prove that your answer is correct.

a. Describe Kruskal's algorithm and Prim's algorithm for finding minimum spanning trees.

b. Illustrate how Kruskal's algorithm and Prim's algorithm are used to find a minimum spanning tree, using a weighted graph with at least eight vertices and \(15\) edges.

Show that a subgraph \({\bf{T = }}\left( {{\bf{V,F}}} \right)\) of the graph \({\bf{G = }}\left( {{\bf{V,E}}} \right)\) is an arborescence of G rooted at r if and only if T contains r, T has no simple circuits, and for every vertex \({\bf{v}} \in {\bf{V}}\) other than r, \({\bf{de}}{{\bf{g}}^ - }\left( {\bf{v}} \right){\bf{ = 1}}\) in T.

Sollin's algorithm produces a minimum spanning tree from a connected weighted simple graph \({\bf{G = (V,E)}}\) by successively adding groups of edges. Suppose that the vertices in \({\bf{V}}\) are ordered. This produces an ordering of the edges where \({\bf{\{ }}{{\bf{u}}_{\bf{0}}}{\bf{,}}{{\bf{v}}_{\bf{0}}}{\bf{\} }}\) precedes \({\bf{\{ }}{{\bf{u}}_{\bf{1}}}{\bf{,}}{{\bf{v}}_{\bf{1}}}{\bf{\} }}\) if \({{\bf{u}}_{\bf{0}}}\) precedes \({{\bf{u}}_{\bf{1}}}\) or if \({{\bf{u}}_{\bf{0}}}{\bf{ = }}{{\bf{u}}_{\bf{1}}}\) and \({{\bf{v}}_{\bf{0}}}\) precedes \({{\bf{v}}_{\bf{1}}}\). The algorithm begins by simultaneously choosing the edge of least weight incident to each vertex. The first edge in the ordering is taken in the case of ties. This produces a graph with no simple circuits, that is, a forest of trees (Exercise \({\bf{24}}\) asks for a proof of this fact). Next, simultaneously choose for each tree in the forest the shortest edge between a vertex in this tree and a vertex in a different tree. Again the first edge in the ordering is chosen in the case of ties. (This produces a graph with no simple circuits containing fewer trees than were present before this step; see Exercise \({\bf{24}}\).) Continue the process of simultaneously adding edges connecting trees until \({\bf{n - 1}}\) edges have been chosen. At this stage a minimum spanning tree has been constructed.

Show that the addition of edges at each stage of Sollin’s algorithm produces a forest.

Show that if \(G\) is a weighted graph with distinct edgeweights, then for every simple circuit of \(G\), the edge of maximum weight in this circuit does not belong to anyminimum spanning tree of \(G\).

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