Is the Set of Integer Outputs of sin(x) Sequentially Compact in ℝ?

In summary, the conversation discusses whether the set of the image of sin(x) and x is an integer greater than one is sequentially compact. It is determined that the set is bounded and closed, making it compact. However, there are some concerns about the set being discrete and its closure being equal to the whole interval. It is concluded that the set is not compact on the Reals, according to Heine-Borel theorem.
  • #1
MidgetDwarf
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Hi. Someone showed me a problem today regarding sequentially compact sets in ℝ.

Ie., is the set of the image of sin(x) and x is an integer greater than one, sequentially compact? Yes or no.

What is obvious is that we know that this set is a subset of [-1,1], which is bounded. So therefore the set in question must be bounded. However, when thinking about whether the set is closed, is where we ran into issues.

My idea was to use the fact that a set is closed iff it contains all of its boundary points. We know that since, the argument of the sin function must be an integer. Then the points in this set are 'discrete', and so every point in this set is actually a boundary point. Therefore the set is closed, and consequently compact.

But this seems a little off. So I suggested to argue that the complement of the set was open., and see what happens. but there another issue here.

I think an easier approach, to argue the correct way, is to just graph the demon, and look at its behavior. The problem is that I tried graphing it into matlab, but I am unsure of how to do this by only showing the integer outputs. Can someone share the graph.
 
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  • #2
It is not compact because ##1## is not in this set (since ##sin(x)=1## only when ##x=\pi/2+2n\pi## for integer ##n## and all of these values are irrational) but it is a limit point of this set. In general, if ##a/b## is irrational, then the multiples of ##a## are dense in ##[0,b]## mod 1.

MidgetDwarf said:
We know that since, the argument of the sin function must be an integer. Then the points in this set are 'discrete', and so every point in this set is actually a boundary point. Therefore the set is closed, and consequently compact.

The image of a discrete set under a continuous map need not be discrete.
 
  • #3
I guess you can also argue it's not closed , since it's dense in [-1,1] ( I believe by equidistribution theorem; if x is Irratiinal, then for n integer, {nx ( mod 1)} is dense in [0,1]), so that its closure would equal the whole interval. Thus, not being closed and bounded, it's not compact on the Reals, by Heine-Borel.
 
  • #4
Iirc, compactness and sequential compactness are equivalent on metric spaces, here the Reals.
 

1. What does it mean for a set to be sequentially compact?

Sequential compactness is a property of a set in mathematics that means every sequence in the set has a convergent subsequence. In other words, the set contains all its limit points.

2. How is sequential compactness different from compactness?

While compactness is a property that applies to all types of sets, sequential compactness only applies to metric spaces. Additionally, compactness requires that every open cover of the set has a finite subcover, while sequential compactness only requires that every sequence in the set has a convergent subsequence.

3. Is the set of integer outputs of sin(x) sequentially compact in ℝ?

Yes, the set of integer outputs of sin(x) is sequentially compact in ℝ. This is because any sequence of integers will eventually converge to a limit point in the set, since sin(x) has infinitely many zeroes on the interval [0,π].

4. What is the importance of sequential compactness in mathematics?

Sequential compactness is an important property in mathematics because it allows us to prove important theorems and make useful generalizations. For example, the Bolzano-Weierstrass theorem, which states that every bounded sequence in ℝ has a convergent subsequence, relies on the sequential compactness of ℝ.

5. How can sequential compactness be used in real-world applications?

Sequential compactness has many real-world applications in fields such as physics, engineering, and economics. For example, it can be used to prove the existence of solutions to certain differential equations, or to show that a system will eventually reach a stable equilibrium.

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