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  • PROFESSOR: So welcome to this week.

  • We're going to talk about trees mainly.

  • We're going to talk about some very special ones,

  • spanning trees.

  • But before we do this, you will go

  • through a whole bunch of definitions

  • and look at examples to explain how it works.

  • So let's talk about walks and paths.

  • So you've already seen a bit of graph theory.

  • We've talked about graph colorings and so on.

  • But now we're going to talk about special types of graphs,

  • and special structures within such graphs.

  • Well, let's start with the first definition.

  • How do we define a walk?

  • Well, a walk is something very simple.

  • You walk from one vertex in the graph over an edge

  • to a next vertex, to a next vertex, and so on.

  • So how do we define this?

  • A walk is a sequence of vertices that are connected by edges.

  • So for example, we may have something

  • that looks like a first vertex.

  • That we call the start.

  • And an edge that goes to a second vertex.

  • We continue like this until the end,

  • say, at vk, which we call the end of the walk.

  • And if you look at this, we say this

  • is a walk from v0 all the way to vk.

  • It has exactly k edges.

  • And we say that the length is actually equal to k.

  • So this is a very basic notion.

  • And what we are really interested in

  • is actually paths.

  • And paths are special types of walks

  • in which all those vertices are actually

  • different from one another.

  • But let's first give an example of a graph

  • that you will study throughout the whole lecture, especially

  • when we come to spanning trees.

  • So let's have a look at the following graph.

  • So let this be a graph.

  • And for example, we can have a walk that

  • goes from this particular edge.

  • Say we call this v0.

  • It goes over this edge over here.

  • Suppose I want to end over here.

  • Well, I can go many ways in this particular one.

  • I can go for this edge.

  • I may go over here.

  • I may go all the way to this part over here.

  • I may return if I want to.

  • And I finally, I take this edge for example back to--

  • over this edge, I will end in the last vertex vk.

  • So what we notice here is that we

  • have a walk that actually gets to this particular vertex,

  • and then returns to this vertex.

  • So for a few other edges, and then goes all the way to vk.

  • So if you talk about the path, then we really

  • want all the difference vertices not to occur twice.

  • So let's define this so the destination is

  • that a path is actually a walk.

  • Is a walk where all edges, where all vertices,

  • vi's, are different.

  • In this particular case-- well for example,

  • if you strip off this part over here,

  • you will get a path from v0 to here, to here, to here.

  • And all these vertices on the path on this walk

  • are different.

  • And therefore it is a path.

  • This also shows us something.

  • It is possible to construct from a walk a path.

  • As you can see, we started off with this particular walk.

  • And we just deleted, essentially,

  • a part where we sort of came back to the same vertex again.

  • And when we delete all those kinds of parts,

  • you will end up with a path.

  • So can we formalize this a little bit better?

  • Then we get the next lemma.

  • I call this lemma one.

  • And let's see whether we can prove this.

  • So we want to show that if there exists a walk from, say,

  • a vertex u to-- well, maybe I should not use arrows.

  • That's confusing-- from u to v. Then there

  • also exists a path from u to v.

  • So how can we prove this?

  • Do you have any ideas?

  • So what kind of proof techniques can we use here?

  • And maybe one of the principles that we have seen?

  • AUDIENCE: [INAUDIBLE] but I have an idea

  • about how you could show this.

  • It's basically if you visit one vertex-- let's

  • you go 1, 2, 3, 4, 5, 3, 6.

  • You can walk from 1 to 6.

  • Then we just take out the 4, you just go 1, 2, 3, 6.

  • PROFESSOR: Right.

  • So what did we do there?

  • We essentially had a walk.

  • And then we cut out a smaller parts here

  • that recurs in a sense.

  • And we have shortened the path, we have shortened the walk

  • to a smaller path.

  • So what we've used here is we can sort of take out

  • parts of the walk just like we did over here

  • until the walk gets shorter, and shorter, and shorter.

  • So maybe one of the things that we may consider

  • is a walk of shortest length.

  • And we know that this is possible.

  • Oops, sorry about that.

  • So let's prove this.

  • So for example, suppose there exists such a walk from u

  • to v. Then we know by the ordering principle

  • that there exists a walk of minimum length.

  • So that's what we're going to use here.

  • And then we're going to essentially go

  • in the same direction as what you were talking about

  • because we're going to show that it's not possible to delete

  • anything more.

  • Because otherwise, if you could do that,

  • the walk would get shorter.

  • And that's not possible, because by the well ordering principle,

  • we simply consider that there exists a walk of minimal length

  • that we are interested in.

  • We will show that this particular walk is actually

  • going to be a path.

  • So let's see how we can do this.

  • So let's do walk be equal to-- well, it starts in v0.

  • It's equal to u.

  • There's an edge to, say, v1.

  • It goes all the way up to vk, which is the last vertex, v.

  • So what are we going to prove?

  • We're going to prove that this is actually a path.

  • And since this is a walk of minimal length,

  • well suppose it is not a path.

  • So we are going to use contradiction.

  • Well if it's not a path, then by our definitions over here,

  • there must be two vertices that are actually

  • the same, just like in here.

  • So we go from v0 to, say, this particular vertex, or this one.

  • And then we come back to this one,

  • and then all the way to vk.

  • So if it is not a path, then two of those

  • must be equal to one another.

  • And then we are going to use this trick.

  • We're going to take out this part.

  • We get the shorter walk.

  • But that contradicts that our walk is minimal length.

  • So that's sort of the proof technique that we're doing.

  • OK.

  • Let's do this.

  • So first, let's consider a few cases.

  • If k equals 0, then that's pretty obvious.

  • We have only a single vertex u that is connected by a 0 length

  • path to itself.

  • So this is fine.

  • For k equals 1, we have just a single edge.

  • And then we're done too.

  • That's a path as well.

  • So let's consider the case where k is at least two.

  • Well, suppose it's a walk.

  • It's not a path.

  • So we are going to assume the opposite.

  • If it's not a path, then we concluded

  • that two of those vi's must be equal to one another.

  • So there exits an i unequal to j such that vertex vi equals vj.

  • Ah, but now we have a walk that goes

  • from v0 all the way to, say, vi, which is equal to vj.

  • And then we go all the way up to vk which is equal to v.

  • So essentially, we have created a shorter walk.