Proving Connectedness of Cycle Graphs: An Alternative Approach

In summary, the conversation discusses the proof of the connectedness of a cycle graph using induction and whether there are any other methods. The definition of a cycle graph is also debated, with different examples given. The importance of induction in the proof is emphasized, as well as the potential for transfinite models to complicate the proof. The conversation also touches on the definition of a cyclic graph and its relation to induction.
  • #1
buddyholly9999
74
0
I remember when I was taking discrete analysis of data structures and we had to prove certain graph theory properties.

I'll give a specific example, prove that the cycle graph, [tex]C_n[/tex], is connected for all n.

From what I remember, it was induction we used to prove this...what I want to know is if there is any other way?

Oh yeah...I think this topic goes under general math...didn't see no graph theory categories..
 
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  • #2
It depends on just what your definition of the "cycle graph" is... but I would expect that induction must be used. (but not necessarily explicitly -- e.g. maybe you could use a theorem that requires induction for its proof)
 
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  • #3
A cycle graph is a graph on n nodes containing a single cycle through all nodes.

The reason I bring this up is because I think I saw something the other day that said if every vertex of a graph G had something like at least (n-1)/2 degrees then it was connected.
 
  • #4
A cycle graph is a graph on n nodes containing a single cycle through all nodes
Then it depends on what you take as the definition of "cycle". :smile:

Are you comfortable with things like ordinal numbers? If so, I could explain to you why I think that induction will be necessary.



The reason I bring this up is because I think I saw something the other day that said if every vertex of a graph G had something like at least (n-1)/2 degrees then it was connected.
Suppose that it's disconnected. How big can the smallest connected component be?
 
  • #5
Come on now...you know what the typical C_n refers to...shall I change my example to the Wheel graph? or perhaps the path graph?

I would like to know (using ordinal numbers) why exactly induction would absolutely be necessary if that's what you want to show me.
 
  • #6
Come on now...you know what the typical C_n refers to...shall I change my example to the Wheel graph? or perhaps the path graph?
Well, yes. Actually, there are boundary cases I'm not sure about -- for example, I can give reasons why we should consider the infinite graph:

... --> * --> * --> * --> ...

a cyclic graph, and reasons why we shouldn't. That's why I'm harping on the precise definition.


For example, I might define a cyclic graph to consist of, for some n > 2:

A sequence of vertices [itex]v_i (1 \leq i \leq n)[/itex].
Edges between [itex]v_i[/itex] and [itex]v_{i+1}[/itex] ([itex]1 \leq i leq n[/itex]), and also between [itex]v_1[/itex] and [itex]v_n[/itex], and no others.


If I reject induction, then I cannot restrict myself to the integers. The above definition makes sense if I plug in any ordinal number greater than 2. If I used [itex]2\omega[/itex], for example, the graph [itex]C_{2\omega}[/itex] would look like:

[itex]2\omega[/itex] --> 1 --> 2 --> 3 --> 4 --> ...
[itex]\omega[/itex] --> [itex]\omega + 1[/itex] -->
[itex]\omega + 2[/itex] --> ...


Other definitions of a cyclic graph might need more interesting transfinite models than ordinals, but I'm pretty sure they will exist.

The point being that induction is a key property of the natural numbers; if you don't invoke it, then you can't rule out various transfinite messes like the one above.



Of course, other definitions of cyclic don't have that problem. I might define a cyclic graph to be a connected graph where every vertex has degree 2. With this definition, there's no trouble showing cyclic graphs are connected. :smile:

(Notice that you can derive an inductive principle from it, though! This definition is essentially equivalent to induction)
 
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  • #7
Am I being incredibly dumb here, but since there is a single cycle through all edges then there is only one path component so it is connected? (Note, all graphs have finitely many edges in my world unless explicitly stated otherwise.)
 

Related to Proving Connectedness of Cycle Graphs: An Alternative Approach

1. What is graph theory?

Graph theory is a branch of mathematics that studies the properties of networks, which are represented by mathematical structures called graphs. A graph consists of a set of vertices (or nodes) and a set of edges that connect these vertices. Graph theory is used to model and analyze real-world systems such as social networks, transportation networks, and computer networks.

2. What is connectedness in graph theory?

Connectedness refers to the property of a graph where every vertex in the graph is connected to at least one other vertex. In other words, there exists a path between every pair of vertices in a connected graph. A graph can be either connected or disconnected, depending on whether it satisfies this property or not.

3. What is the minimum number of edges required for a connected graph?

The minimum number of edges required for a connected graph depends on the number of vertices in the graph. For a graph with n vertices, the minimum number of edges required is n-1. This is known as the minimum number of edges for a tree, which is a type of connected graph with no cycles.

4. How is connectedness related to the concept of paths in a graph?

In a connected graph, there exists a path between every pair of vertices. This means that we can travel from one vertex to another by following a sequence of edges. The number of edges in a path is known as its length. Therefore, the existence of paths between all pairs of vertices is a key property of connectedness in a graph.

5. Can a graph be both connected and disconnected?

No, a graph cannot be both connected and disconnected at the same time. A graph is either connected, meaning there exists a path between every pair of vertices, or disconnected, meaning there exists at least one pair of vertices that are not connected by a path. There is no overlap between these two types of graphs.

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