A proof of Dilworth Theorem? - Looking for feedbacks

In summary, Dilworth's theorem states that every poset whose width is greater than two is the union of at least two chains.
  • #1
Kolmin
66
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It is the very first time I try such a long shot, attempting to prove a well-known theorem (small one, but still not completely obvious).

I would be really grateful to anyone ready to give a feedback (contents or style doesn't matter - they are both important).

PS: Obviously I am not sure I actually proved! :smile:
 
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  • #2
Kolmin said:
It is the very first time I try such a long shot, attempting to prove a well-known theorem (small one, but still not completely obvious).

I would be really grateful to anyone ready to give a feedback (contents or style doesn't matter - they are both important).

PS: Obviously I am not sure I actually proved! :smile:

Theorem (Dilworth, 1950):
Every poset whose width is ##n## is equal to the union of ##n## chains.

Proof:
We let ##R## be a partial order relation over a set and we let ##P## be an arbitrary poset with width ##w(P)## equal to ##n##.
We proceed on induction over ##w(P)##.
i) Base case:
We assume that ##w(P)## is equal to 2. This means that there are two elements member of ##P##, say ##x_1## and ##x_2##, that are ##R-incomparable##.
We let ##p## be an arbitrary element of ##P## and let ##C_i## be a chain subset of ##P## whose elements are all the elements of ##P## that are ##R-comparable## to ##x_i## (with ##i=1,2##).
To prove the sufficient condition we proceed by contradiction by assuming that ##p## is an arbitrary member of ##P## and that it is not a member of both ##C_1## and ##C_2##. This last assumption implies that we have ##\neg pRx_i## and ##\neg x_iRp## (with ##i=1,2##), but this means that ##p## is ##R-incomparable## to both ##x_1## and ##x_2##. Hence ##w(P)## has to be more than 2, contradicting our assumption.
The necessary condition is immediate.
Thus, the base case is proven.
ii) Inductive step:
We assume that ##w(P)=n## implies ##P= \bigcup_{i=1}^{n} C_i##, and we assume that ##w(P)## is equal to ##n+1##. We let ##p## be an arbitrary element of ##P## and ##C_i## be the ##i##-th chain, subset of ##P##, whose elements are all the elements of ##P## that are ##R-comparable## to ##x_i## (with ##i=1,\dots, n+1##).
To prove the sufficient condition we proceed by contradiction by assuming that ##p## is an arbitrary member of ##P## and that ##p## is not a member of any of the ##n+1## chains previously defined.
We define ##P'=P/\{x_i\}## as ##P## minus an arbitrary element ##x_i## member of ##w(P)## (with ##i=1,\dots,n+1##). By construction the width ##w(P’)## is equal to ##n##. We assume that ##P'= \bigcup_{i=1}^{n} C_i##. This means that for every element ##p## of ##P’## there exist ##n## chains such that ##p## is a member of ##P’## if and only if ##p## is a member of at least one of the ##n##chains. Thus, we assume that ##p## is a member of at least one of the ##n## chains. However, this contradicts our assumption that ##p## is not a member of any of the ##n+1## chains that are equal to the union of the ##n## chains and the arbitrary ##x_i## element taken from ##P## to construct ##P’##. Hence, the sufficient condition is proven.
The necessary condition is immediate.
Thus, by the inductive step the theorem is proven.
 
  • #3
It's not obvious that the Ci are chains - e.g. {A>C, A>D, B>C} may present some difficulties for n=2.

Did you find another approach?
 

FAQ: A proof of Dilworth Theorem? - Looking for feedbacks

What is Dilworth Theorem and why is it important in mathematics?

Dilworth Theorem is a fundamental result in combinatorics that provides a necessary and sufficient condition for the existence of a partition of a finite set into a given number of chains. It is important in mathematics because it has many applications in areas such as graph theory, optimization, and computer science.

What is the proof of Dilworth Theorem and how does it work?

The proof of Dilworth Theorem is based on the concept of antichains, which are subsets of a set that do not contain any comparable elements. It uses mathematical induction and the concept of maximum antichains to show that the maximum number of antichains in a finite set is equal to the minimum number of chains needed to partition the set.

Can you give an example of how Dilworth Theorem is used in real-world problems?

One example of how Dilworth Theorem is used in real-world problems is in scheduling tasks with precedence constraints. The tasks can be represented as a directed acyclic graph and Dilworth Theorem can be used to find the minimum number of time slots needed to complete all the tasks without violating any of the constraints.

Are there any variations or extensions of Dilworth Theorem?

Yes, there are several variations and extensions of Dilworth Theorem, such as the Dual Dilworth Theorem, which provides a necessary and sufficient condition for the existence of a partition into a given number of independent sets in a finite set.

Is there an easy way to remember or visualize Dilworth Theorem?

One way to remember Dilworth Theorem is to think of it as a balancing act between antichains and chains. The maximum number of antichains represents the weight on one side, while the minimum number of chains represents the weight on the other side. When these two are equal, the set is balanced and can be partitioned into the desired number of chains.

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