Okay. So to this point we've proven the 
correctness of Prim's minimum spanning sheet algorithm under an assumption, 
under an assumption that the cut property is true. 
So, the purpose of this video was to supply the missing proof to convince you 
of this cut property. Let me remind you where we stand. 
So through all the minimum spanning tree videos, we're assuming distinct edge 
costs. All of this can be extended to edge costs 
with ties. In particular, there's a version of the 
cut property when the edges have ties, but we're just going to focus on the main 
ideas which were exposed already with distinct edge costs. 
So what does the cut property say? Well, it's meant to be a guarantee that 
an edge is safe to include on, in your tree so far. 
So it justifies an iteration of a greedy algorithm like Prim's algorithm. 
Specifically, consider an edge of a graph, and suppose you can find some cut 
A, B. So that, amongst all the edges that are 
crossing this cut, E is the cheapest. So E, the edge E has to not just cross 
this cut, but it has to be cheaper than any edge 
that crosses this cut. If you can find just one cut of this 
form, so that E is the cheapest crossing edge, 
then it's definitely not a mistake to include E in your tree. 
You definitely want it. It is in the MST. 
So this is a non-trivial claim and, let's turn to the proof. 
At a high level, the plan will be not that different than the correctness of 
our greedy scheduling algorithm for minimizing the weighted sum of the 
completion times. That is, we're going to use an exchange 
argument embedded in a proof by contradiction. 
[COUGH] The type of contradiction will be of the same form. 
We'll start with an optimal solution. Suppose it doesn't have the property that 
we want it to have, and then we do an exchange to make it 
even better, contradicting the assumption that this solution is optimal. 
So specifically, if we argue by contradiction we assume, that the cup 
property is false. So let's just make sure we understand 
what that means. If the cup property is false, then 
there's a graph and there's an edge, which actually is the cheapest crossing 
some cut, and yet, that edge does not belong to the minimum cost spanning tree 
T star. The plan then is to exchange this missing 
edge E with some edge that isn't a tree T star, which is more expensive, thereby 
getting a better spanning tree providing the contradiction. 
So, this idea currently is a little bit hand-wavy. 
To really execute it, we have to specify which edge we're going to exchange the 
edge E with. That's a subtle point and we'll develop 
it over the next couple of slides. So let's begin with a sort of first cut 
attempt at an exchange argument. So what's the world look like? 
Well, we have some cut of a graph. So at one blob, the vertices is A and 
then the rest of the vertices are in this blob B. 
this is the cut for which edge E is the cheapest. 
And by our assumption in this proof by contradiction, this cheapest edge E does 
not belong to the minimum spanning tree T star. 
That said, I claim while T star may not have this 
edge E to cross in this cut, it better possess some other edge crossing this cut 
A, D. So why is that true? 
Well, suppose the opposite, suppose in fact T star did not have any edge 
crossing this cut A, B, well then, T star wouldn't be 
connected. It wouldn't span all the vertices, 
right? Remember our proof of empty cut lemma, so 
if you had this empty cut and there's no way to have a path from one side to the 
other side. Okay? 
But that's spanning trees have to have paths between each pair of vertices. 
So T star as a spanning tree have to contain something from this cut, by 
assumption it doesn't contain edge E. So it contains some other edge, let's call 
it F, that crosses this cut. Now of course, since E is the cheapest 
edge crossing this cut and F is some other edge crossing this cut, F is 
strictly more expensive than E. And at this point, we seem beautifully 
set up to execute the desired exchange arguement. We have the edge that the 
optimal solutions missing. We have a canvid replacement edge F, which is more 
expensive. So if we swap E and F, hopefully we get a 
new spanning tree that has strictly smaller cost providing the desired 
contradiction. But, things are more settled than they 
were with these scheduling applications. The reason being is that schedules are 
simply sequences of jobs. So whenever you do an exchange of two 
jobs, it's clear you get another schedule. 
But spanning trees and graphs are subtle objects and there's a question, if we 
take a spanning tree and we add one new edge and delete an edge, 
do we get another spanning tree of the graph or not? 
So the following quiz is going to ask you to think about that question carefully. 
Okay. So what we wish that the answer to this quiz was, was either answer A or 
answer C. So A would be the cleanest solution. 
If it were always true that when you take a spanning tree, you take an edge outside 
of the spanning tree and then you swap those two edges, you get a new spanning 
tree, then in fact, our proof of the cut 
property would be done, right? We would just go on that previous slide. 
We would rip out the edge F from the spanning tree. 
We'd plug in the edge E, because E costs less than F, 
we'd get a spanning tree which was cheaper. 
And we'd be done, that would be our contradiction. 
Now if A wasn't true, we'd still be okay if C was true. 
If maybe not every swap yields a new spanning tree, 
but at least if you're swapping in the edge that's the cheapest crossing some 
cut, you get a spanning tree. 
Then we'd also be golden, because in fact, we're only are trying to execute 
the swap, the exchange, using an edge, which is the 
cheapest crossing some cut. If you go back to the previous slide, 
you'll see that was the only case we needed this fact to be true. 
Unfortunately, the correct answer to this quiz is D. 
You need not get a new spanning tree when you execute an exchange, even if you're 
plugging an edge which is the cheapest edge crossing some cut. 
So to understand this better, let me the picture that we had on the previous 
slide. We had our cut A, B, we had our cheapest 
edge E which by assumption does not belong to the spanning three T star, but 
we observed that T star has to contain at least one other edge crossing this cut 
because it's connected and we called that F. 
And we're wondering if swapping E and F yields a new spanning tree or not. 
So, to reason about this, let me just draw you what the rest of the spanning 
tree might look like. So in this picture, this spanning tree T 
star is given by the pink edges. And it's just to this path of five edges 
on the six vertices. So, what happens if we exchange E and F? 
Well unfortunately, something bad happens. 
So we certainly get a new subgraph of five edges, 
after all, we just subtracted one and added one. 
But this new spanning, this new subgraph fails to be a spanning tree. 
It fails on both counts. First of all, it obviously has a cycle 
and it's a four cycle and secondly, it's not connected. 
The upper right vertex is just totally disconnected from the rest of the rest of 
the vertices. So that's no good. 
That's an exchange which just does not produce a feasible solution and it is 
therefore not useful in our proof by contradiction. 
Now, if you just want to salvage some hope from this seemingly promising proof 
plan, we could take solace from the fact that there is not just one pink edge 
crossing the cut A, B. F isn't the only one, there's actually 
this other one on the bottom. so let me call that E prime. 
Now, E being the cheapest edge crossing this cut overall. 
Not only is E cheaper than F, it's cheaper than E prime also. 
So in some sense with our motivation, we could care less which edge we exchange E 
from crossing this cut, because it's cheaper than all of them. 
And we see that at least in this example, swapping with E prime yields a good 
solution, yields a feasible spanning tree. 
So what have we learned? What we've learned is that if we want to 
execute this exchange argument, we cannot blithely exchange with any edge of T star 
that crosses this cut. So the best case scenario, so what we're 
hoping is true that we can always find some suitable edge, like E prime on the 
previous slide. So that when we execute this swap, 
we do in fact, get a spanning tree. And I'm happy to report that we can 
indeed always do this. So what I need to explain is the 
procedure by which we exhibit edge, this edge E Prime, which doesn't get us into 
trouble after we swap, which still gives us a spanning tree after the swap. 
So let me explain the procedure by which we identify this magical edge E prime 
that we can swap with and still be a spanning tree. 
So here's the way to think about it, so we've got this spanning tree T star, 
we've got this edge which is not yet in T star. 
Now, if we just plug E into T star, we're going to get a cycle. 
Why? Well, a spanning tree, remember, it has a 
path between each pair of vertices. So if this new edge, maybe its endpoints are U 
and V. T star already has a path between U and V, so when you plug in this new 
direct edge between U and V, it closes the loop, it gives you a cycle. 
So let's go ahead and call that cycle capital C. 
Let me also redraw the picture from the example on the previous slide so you can 
see what that cycle was in that special case. 
Now, here's the pattern to notice about this cycle capital C, at least in this 
example, which is that the lousy edge, the edge F, for which when we swapped, we 
didn't get a spanning tree, that's off of this capital C. Whereas, the good edge, 
the edge where we could do a swap and get a spanning tree, E prime that's on this 
same cycle capital C. And that turns out to be true in general. 
So, when you add the edge to the spanning tree and you get a new cycle, that cycle 
is what furnishes the candidates for swaps that will give you a new spanning 
tree. So the one lingering concern then, we 
have this cycle. We would, all edges of the cycle are 
going to be good candidates for the swapping. Wee just need to make sure that 
there is some edge that actually crosses this cut A, B like the edge E prime does 
in the picture. But here, we're going to rely on a fact 
from a previous video, the double crossing lemma. 
Remember the double crossing lemma says, that if you have a cycle that crosses a 
cut at least once, then it has to cross it twice. 
All right. So if it'd cross once, then it has to 
loop back around, then in looping back around, it's going to cross it a second 
time. So, in this cycle capital C, we know it 
crosses the cut A, B once, that's because it includes the original 
cheapest edge across the cut E. So, it's got to cross it a second time. 
There's got to be an E prime in the cycle crossing the cut and that's going to 
allow us to do the swap and get a new, cheaper spanning tree completing the 
contradiction. So, just to spell things out in a little 
more detail. So what we do is we first say we use the 
double crossing lemma. So, we have this reported minimum 
spanning tree T star. We have this cheap edge E knot in it. 
We plug E into the spanning tree, we get cycle, we call the cycle capital C. 
The cycle crosses the cut A, B once, through the edge E. 
It crosses it a second time by the double crossing lemma. 
We're going to call that edge E prime. Since E prime crosses the same cut as E, 
we know that E prime is strictly more expensive than E. 
Remember we use the cheapest one crossing this cut, A, 
B. So now what we do is we execute the swap 
with this new edge E prime. So E prime in T star. 
The cheapest edge, E, is not in T star so we can swap them. 
We can take, we can rip E prime out, we can stick E 
in. Now something I want you to think through 
carefully at home, convince yourself this is true, is that because we plucked E 
prime from the cycle, this new tree which I'm going to call capital T, this is a 
spanning tree necessarily. You know, intuitively, the reason being, 
you plug in E and you get this one cycle involving E, and then when you rip out E 
prime, you destroy the cycle. And because it's on a cycle, you don't 
destroy connectivity between any pair of veriticies, there is still one path 
between each pair. But make sure you believe that, convince 
yourself at home. And once you're so convinced, you will 
also realize that we've finished a proof. We've executed our proof by 
contradiction. since E was the cheapest edge crossing 
the cut, and E prime is another edge crossing the cut, 
E is got to be cheaper. Since T differs from T star only in the 
swap of these two edges, it's aggregated cost has gone down and 
that contradicts the purported optimality of T star comp completing the proof of 
the cut property.