Hall's theorem problem (graph theory)

In summary: The Attempt at a SolutionIt's too easy. I think. We are going to have a set A which contains the suits and a set B which contains the piles.Set A={A,2,3,4,5,6,7,8,9,10,j,q,k}Set B={13 piles}The trick to prove this is to know that every element in the set A will always have 4 lines going out no matter where, so lN(A)l >=A because no matter which subset of the set A we pick, every vertex in the set A will
  • #1
TheMathNoob
189
4

Homework Statement


Take a standard deck of cards, and deal them out into 13 piles of 4 cards each. Then, using the marriage theorem, we can show that it is always possible to select exactly 1 card from each pile, such that the 13 selected cards contain exactly one card of each rank (Ace, 2, 3, ..., Queen, King). M

Homework Equations


Halls theorem IN(A)l>= A
If this is true for every subset of A then the bipartite graph has a complete matching

The Attempt at a Solution


It's too easy. I think. We are going to have a set A which contains the suits and a set B which contains the piles.

Set A={A,2,3,4,5,6,7,8,9,10,j,q,k}
Set B={13 piles}

The trick to prove this is to know that every element in the set A will always have 4 lines going out no matter where, so lN(A)l >=A because no matter which subset of the set A we pick, every vertex in the set A will always have 4 neighbors and intuitively the addition of those neighbors will be always greater that the number of vertices or elements in A

As easy as that?
 
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  • #2
TheMathNoob said:
As easy as that?
Unfortunately not.
Given two elements in A, their neighbours in B can overlap, so there will not necessarily be eight neighbours.
You have to find some way of putting a lower bound on the number of neighbours in B that a set ##W\subseteq A## has.
Given we're starting with a ratio of four to one, one would imagine ('intuitively' as you say) that for any W, the neighbours can't overlap so badly that the number of neighbours is less than |W|. But imagining is one thing, and proof is another.
 
  • #3
andrewkirk said:
Unfortunately not.
Given two elements in A, their neighbours in B can overlap, so there will not necessarily be eight neighbours.
You have to find some way of putting a lower bound on the number of neighbours in B that a set ##W\subseteq A## has.
Given we're starting with a ratio of four to one, one would imagine ('intuitively' as you say) that for any W, the neighbours can't overlap so badly that the number of neighbours is less than |W|. But imagining is one thing, and proof is another.
How do they overlap?, each pile can't have more than 4 cards. Can you show an example of why my proof doesn't work?. I would appreciate it.
 
  • #4
Say pile 1 contains two black aces and two black twos, and
pile 2 contains two red aces and two red twos.

Then the set of all neighbours of elements of W={Ace, 2}##\subset##A comprises only two elements {Pile 1, Pile 2} of set B.
 
  • #5
andrewkirk said:
Say pile 1 contains two black aces and two black twos, and
pile 2 contains two red aces and two red twos.

Then the set of all neighbours of elements of W={Ace, 2}##\subset##A comprises only two elements {Pile 1, Pile 2} of set B.
I am trying to understand your point. Yes, they overlap and in this case the number of neighbors of the set {Ace,2} is 8, so the inequality is satisfied. Each box contains 4 slots. I am not saying that each suit must perfectly math each box. That would be silly. Each box can be seen as a component of the graph.
 
  • #6
TheMathNoob said:
I am trying to understand your point. Yes, they overlap and in this case the number of neighbors of the set {Ace,2} is 8, so the inequality is satisfied.
E
TheMathNoob said:
I am trying to understand your point. Yes, they overlap and in this case the number of neighbors of the set {Ace,2} is 8, so the inequality is satisfied. Each box contains 4 slots. I am not saying that each suit must perfectly math each box. That would be silly. Each box can be seen as a component of the graph.
andrewkirk said:
Say pile 1 contains two black aces and two black twos, and
pile 2 contains two red aces and two red twos.

Then the set of all neighbours of elements of W={Ace, 2}##\subset##A comprises only two elements {Pile 1, Pile 2} of set B.
I don't know if in this case we can consider each component as a vertex and allow edge repetitions among components.
 
  • #7
andrewkirk said:
Say pile 1 contains two black aces and two black twos, and
pile 2 contains two red aces and two red twos.

Then the set of all neighbours of elements of W={Ace, 2}##\subset##A comprises only two elements {Pile 1, Pile 2} of set B.
Correct Andrewirk, I saw my mistake. I am just wondering if we can do this by considering the lower bound as you stated. For example, the minimum number of neighbors of each label has to be 1. If we do this to every subset of A, we will notice that lN(A)l =A for the lower bound. But I am still worried because the theorem doesn't say that the matching will cover both sides of the graph. This is what it says:
 
  • #8
TheMathNoob said:
I am still worried because the theorem doesn't say that the matching will cover both sides of the graph.
In general that would be a problem, but not in this case.
Why? Because sets A and B have the same number of elements, and one side - assume wlog it is A - is covered by the matching. Since every element in A is at one end of an edge in the matching, and an element of B is at the other end, and the definition of a 'matching' requires that every element of B is at the end of at most one matching, what can we conclude about the coverage of B?
 
  • #9
andrewkirk said:
In general that would be a problem, but not in this case.
Why? Because sets A and B have the same number of elements, and one side - assume wlog it is A - is covered by the matching. Since every element in A is at one end of an edge in the matching, and an element of B is at the other end, and the definition of a 'matching' requires that every element of B is at the end of at most one matching, what can we conclude about the coverage of B?
Quite so. But in any case, the theorem does not conclude there is a matching for "at least one side". The conditions are not symmetric. The side that is guaranteed a matching is prescribed.
 
  • #10
haruspex said:
Quite so. But in any case, the theorem does not conclude there is a matching for "at least one side". The conditions are not symmetric. The side that is guaranteed a matching is prescribed.
I don't get it. It gives a necessary and sufficient condition for finding a matching that covers at least one side of the graph.
 
  • #11
TheMathNoob said:
I don't get it. It gives a necessary and sufficient condition for finding a matching that covers at least one side of the graph.
As haruspex said, the theorem is asymmetric. It says, that, IF one side of the graph obeys the condition ##|W|\leq |N_G(W)|## (using the notation from this wiki page) then there is a matching that covers THAT side of the graph. It doesn't just say the matching covers one of the two sides, unspecified.
 
  • #12
andrewkirk said:
As haruspex said, the theorem is asymmetric. It says, that, IF one side of the graph obeys the condition ##|W|\leq |N_G(W)|## (using the notation from this wiki page) then there is a matching that covers THAT side of the graph. It doesn't just say the matching covers one of the two sides, unspecified.
So can't we do this by using hall's theorem?
 
  • #13
TheMathNoob said:
So can't we do this by using hall's theorem?
Hall's theorem will certainly give you the result you need, in either of two ways.
You are asked to show that all ranks can be matched by selections of piles. To get that result directly from Hall you need to show that every subset of the ranks spans at least as many piles.
If, instead, you were to show that every subset of piles spans at least as many ranks, you would then need to use Andrew's observation in post #8 to flip it around to the result you need.
 

1. What is Hall's theorem problem in graph theory?

Hall's theorem problem is a mathematical concept in graph theory that deals with bipartite graphs, which are graphs that can be divided into two sets of vertices such that every edge connects a vertex from one set to a vertex from the other set. The theorem states that a bipartite graph has a perfect matching (a matching where every vertex is incident to exactly one edge) if and only if for every subset of vertices in one set, the number of vertices it is connected to in the other set is at least as large as the subset itself.

2. What is the significance of Hall's theorem in graph theory?

Hall's theorem is significant because it provides a necessary and sufficient condition for the existence of a perfect matching in a bipartite graph. It has a wide range of applications, including in computer science, economics, and biology.

3. How is Hall's theorem proved?

Hall's theorem can be proved using the method of mathematical induction. The theorem is first proved for a graph with only two vertices in one set, and then it is shown that if the theorem holds for a graph with n vertices, it also holds for a graph with n+1 vertices. This process is then repeated until the entire graph is covered.

4. Can Hall's theorem be applied to non-bipartite graphs?

No, Hall's theorem only applies to bipartite graphs. If a graph is not bipartite, there is no guarantee that there will be a perfect matching that satisfies the condition stated in the theorem.

5. Are there any real-life applications of Hall's theorem?

Yes, there are many real-life applications of Hall's theorem. For example, it is used in job matching algorithms to ensure that every job applicant is matched with a job that satisfies their preferences. It is also used in the analysis of supply chains and network flow problems. Additionally, Hall's theorem has been used in evolutionary biology to study the evolution of mutualistic relationships between species.

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