Proof about min spanning tree property

In summary, the conversation discusses the relationship between the cut property and the existence of a lightest edge in some cutset of a graph. The cut property states that if the weight of an edge in a cutset is smaller than all other edges in the cutset, then it belongs to all minimum spanning trees (MSTs) of the graph. The conversation then explores the possibility of a cutset in which the edge e is not the lightest, and suggests finding a special partition of vertices using the given information of the graph, the MST, and e.
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Homework Statement


(a) If e is part of some MST of G, then it must be a lightest edge in some cutset of G.

Homework Equations


Cut property

The Attempt at a Solution


When the cutset has just one edge then yes it's true obviously. I am think I can do this by contradiction. Assuming e_i is part of some MST of G and e_i is not the lightest edge in any cutset. If this is true then, in every cutset, there exists an edge e_k such that e_k>e_i. I don't know how to go from here

The cut property says For any cut C of the graph, if the weight of an edge in the cut-set of C is strictly smaller than the weights of all other edges of the cut-set of C, then this edge belongs to all MSTs of the graph.

It doesn't say anything about the larger edges in the cut
 
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It's a bit hard to give help on this without giving the whole thing away. Still, I'll try.

Since the problem says 'for some cutset in G', it seems likely that there are some (possibly many, possibly even most) cutsets containing e in which e is not the lightest edge. So we might like to look for special cutsets (in which e does have the desired property), which is the same as looking for special partitions of the vertices. The other piece of info we have is that e is in a minimal spanning tree (MST), call that T.

So, in the interests of finding a special partition of the vertices, using the info given, can you think of a partition of the vertices that is uniquely defined as a function of only G, T and e, without requiring any additional choices (which would necessarily be arbitrary)?
 
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FAQ: Proof about min spanning tree property

What is a minimum spanning tree?

A minimum spanning tree (MST) is a subset of a graph that connects all vertices together with the minimum possible total edge weight. It is a widely used data structure in computer science and has applications in various fields such as network design, clustering, and optimization.

What is the property of a minimum spanning tree?

The main property of a minimum spanning tree is that it connects all vertices in a graph with the minimum possible total edge weight. This means that the total weight of all edges in the MST is less than or equal to the total weight of any other spanning tree in the same graph.

How is the proof of minimum spanning tree property done?

The proof of minimum spanning tree property is typically done using the cut property and the cut-and-paste argument. The cut property states that for any cut in a graph, the minimum weight edge crossing the cut must be a part of the minimum spanning tree. The cut-and-paste argument involves replacing edges in a spanning tree with other edges from the graph, while maintaining the total weight of the tree.

Why is the minimum spanning tree property important?

The minimum spanning tree property is important because it allows us to find the most efficient way to connect all vertices in a graph. This has practical applications in various fields such as transportation networks, telecommunications, and resource allocation. It also serves as the basis for various algorithms such as Prim's and Kruskal's algorithm for finding the minimum spanning tree.

Can the minimum spanning tree property be applied to directed graphs?

No, the minimum spanning tree property is only applicable to undirected graphs. In directed graphs, instead of spanning trees, we have directed spanning trees which have different properties and cannot be reduced to a minimum weight problem. However, there are other minimum cost problems that can be solved in directed graphs, such as the shortest path problem.

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