Smallest Set Containing All n-point Sets

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In summary: But I'm not sure whether there exists a closed form for this. In summary, the smallest set that can contain an n-point subset P of the real line is the set [0,1] U {2}.
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jgm340
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I've been thinking about this. Suppose you have an n-point set P in Rm which has the property that for any two points x, y in P, ||x - y|| < 2. If we fix n, what can we say about the smallest set S in Rm that contains P, allowing for both translations and orthogonal transformations of S?

If we start in R2, the answer is not what you'd expect! As illustrated in this picture, P must be able to fit inside of any 2 by 2 square after only translation:
attachment.php?attachmentid=26839&stc=1&d=1278316407.png

That is, if I were to have a square hoola-hoop, I could swing it around P. However, for n > 2, the intersection of all those squares would not necessarily fit inside a circle of diameter 2.

For n=2, the smallest set would be something like [0,1] U {2}.
For n=3, I think the smallest set would be {x = (x1, x2) : ||x - (0,1)|| < 2, x1 < 0, x2 < 0} U {x = (x2,x2) : x1 = 0, -1 < x2 < 1}

Any thoughts?
 

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I'm not sure what exactly you mean by "translations" and "orthogonal transformation".

If you have an n-point subset P of R^m, take max{||x - y||, x, y from P} = diam(P) = r = d(x0, y0) (for some x0, y0 in P), and then the closed ball B(x0, r) around x with radius r contains the set P.
 
  • #3
radou said:
I'm not sure what exactly you mean by "translations" and "orthogonal transformation".

If you have an n-point subset P of R^m, take max{||x - y||, x, y from P} = diam(P) = r = d(x0, y0) (for some x0, y0 in P), and then the closed ball B(x0, r) around x with radius r contains the set P.

Yes, but that's not the smallest. :wink:
Take the intersection of the balls about x0 and y0. This would also necessarily contain P.

About the "translations and orthogonal transformations" business: I'm looking for a closed form for a set S which must "be able to contain" P. By "be able to contain", I mean that for any P, we ought to find some transformation T (involving only rotations, reflections, and translations) such that P is contained in T(S).
 

What is the "Smallest Set Containing All n-point Sets" problem?

The "Smallest Set Containing All n-point Sets" problem is a mathematical problem that seeks to find the smallest possible set that contains all possible n-point sets. This problem has applications in fields such as computer science, graph theory, and combinatorics.

Why is the "Smallest Set Containing All n-point Sets" problem important?

This problem has practical applications in various fields such as data compression, storage optimization, and network design. It also has theoretical implications in the field of discrete mathematics.

How is the "Smallest Set Containing All n-point Sets" problem solved?

The problem can be solved using various algorithms such as the greedy algorithm, the exhaustive search algorithm, and the dynamic programming algorithm. The choice of algorithm depends on the specific problem and its constraints.

What are some real-world examples of the "Smallest Set Containing All n-point Sets" problem?

One example is in computer networking, where the problem can be applied to determine the minimum number of routers needed to connect all possible networks. Another example is in data compression, where the problem can be used to find the smallest set of symbols that can represent all possible data sequences.

Are there any limitations or challenges to solving the "Smallest Set Containing All n-point Sets" problem?

Yes, the problem can become increasingly complex and computationally expensive as the number of points increases. Additionally, the problem may have multiple optimal solutions, making it difficult to determine the most efficient one. The problem may also have practical limitations, such as the physical constraints of a network or the storage capacity of a computer system.

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