Prove that sup(ST) = sup(S)sup(T)

  • Thread starter Mr Davis 97
  • Start date
In summary: I'm looking for?If you let ##a = (\sup S + \sup T - \epsilon)##, then clearly ##\epsilon ' = \epsilon a## can be made as close to zero as you wish, since ##a > 0## and ##\epsilon## can get as close to zero as we wish, as long as ##\epsilon < \sup S + \sup T##.
  • #1
Mr Davis 97
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Homework Statement


Prove the following: Suppose S and T are non-empty, bounded subsets of (0,+∞) and let ST be the set, ST = {st: s∈S and t∈T}. Then sup(ST) = sup(S) sup(T)
.
Hint: Notice that if 0 < y < sup(S)sup(T), then there exists r ∈ (0,1) such that y = (rsup(S))(rsup(T)). After finding such r, consider the inequalities rsup(S) < sup(S) and rsup(T)< sup(T).

Homework Equations

The Attempt at a Solution


First, we know that ##\sup (S) \sup (T)## is an upper bound of ##ST##, because we have individually ##\forall s \in S ~ s \le \sup S## and ##\forall t \in T ~ t \le \sup T##, which taken together impleies that ##\forall st \in ST ~ st \le \sup (S) \sup (T)##.

Second, we need to show that if ##b < \sup (S) \sup (T)##, then ##b## is not an upper bound. Here is where I'm stuck. Is there is where I use the hint? I don't really see how the hint can be used...

I think I might have the second part. By definition of the supremum, we know that ##\forall \epsilon \exists s \in S ## where ##\sup (S) - \epsilon < s##. Also, we have ##\forall \epsilon \exists t \in T ## where ##\sup (T) - \epsilon < t##. Combining these two statements, we have that ##(\sup T - \epsilon)(\sup S - \epsilon) = \sup T \sup S - \epsilon ' < st##. Since we already showed that \sup T \sup S, this shows that it is the supremum. Is this correct?
 
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  • #2
I also do not find the hint helpful. But I think you're on a promising track here:
Mr Davis 97 said:
we have that ##(\sup T - \epsilon)(\sup S - \epsilon) ...##.
If you expand that product you will get an expression that should be able to be made arbitrarily close to ##\sup S\sup T##, via suitable choice of ##\epsilon##.
 
  • #3
andrewkirk said:
I also do not find the hint helpful. But I think you're on a promising track here:

If you expand that product you will get an expression that should be able to be made arbitrarily close to ##\sup S\sup T##, via suitable choice of ##\epsilon##.
What I did was let ##\epsilon ' = \epsilon (\sup T +\sup S) - \epsilon ^2##. How could I show that this could be any positive real number?
 
  • #4
Mr Davis 97 said:
What I did was let ##\epsilon ' = \epsilon (\sup T +\sup S) - \epsilon ^2##. How could I show that this could be any positive real number?
You don't need to. All you need do is show that ##\epsilon'## can be made arbitrarily small.
 
  • #5
andrewkirk said:
You don't need to. All you need do is show that ##\epsilon'## can be made arbitrarily small.
Well. if ##\epsilon (\sup T + \sup S) - \epsilon ^2 > 0## then ##\epsilon < \sup T + \sup S##. Does this show that ##\epsilon '## can be made arbitrarily small? As long as ##\epsilon \in (0, \sup T + \sup S)##, then ##\epsilon '## is positive.
 
  • #6
Mr Davis 97 said:
Well. if ##\epsilon (\sup T + \sup S) - \epsilon ^2 > 0## then ##\epsilon < \sup T + \sup S##.
That's heading off track. We have a formula that expresses ##\epsilon'## in terms of ##\epsilon## and ##\epsilon## is universally quantified so we can make it as close to 0 as we wish. I'm sure if you look at the formula for ##\epsilon'## you'll soon see how to make it as close to 0 as you need by choosing ##\epsilon## small enough. If you can make ##\epsilon'## as small as you wish then you can make ##st## as close to ##\sup S\sup T## as you wish, so there cannot be an upper bound below ##\sup S\sup T##.
 
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  • #7
andrewkirk said:
That's heading off track. We have a formula that expresses ##\epsilon'## in terms of ##\epsilon## and ##\epsilon## is universally quantified so we can make it as close to 0 as we wish. I'm sure if you look at the formula for ##\epsilon'## you'll soon see how to make it as close to 0 as you need by choosing ##\epsilon## small enough. If you can make ##\epsilon'## as small as you wish then you can make ##st## as close to ##\sup S\sup T## as you wish, so there cannot be an upper bound below ##\sup S\sup T##.
Okay, I'm pretty much done with the proof now. I just have one question. How could I prove that ##\epsilon ' = \epsilon (\sup S + \sup T - \epsilon)## could in fact get as close to zero as I wish? I mean, it's intuitively clear. If we let ##a = (\sup S + \sup T - \epsilon)##, then clearly ##\epsilon ' = \epsilon a## can be made as close to zero as I wish, since ##a > 0## and ##\epsilon## can get as close to zero as we wish, as long as ##\epsilon < \sup S + \sup T##. Is this enough to prove it, or is there something more formal that I have to do?
 
  • #8
Mr Davis 97 said:
Okay, I'm pretty much done with the proof now. I just have one question. How could I prove that ##\epsilon ' = \epsilon (\sup S + \sup T - \epsilon)## could in fact get as close to zero as I wish?
A strategy that usually works in these cases - where the control variable ##\epsilon## occurs more than once in the formula whose value one is trying to make small - is to try to show that the formula is ##\leq## a formula that is ##constant \times \epsilon##. Can you see a way to do that with the above?

The proof would take the form of letting ##\eta>0## be the number that we want to make ##\epsilon'## smaller than. Then say 'assume ##\epsilon <## [some formula involving ##\sup S,\sup T,\eta##]' and then work through the inequalities to prove that ##\epsilon'<\eta## if ##s,t## are within ##\epsilon## of ##\sup S,\sup T## respectively..

Choosing the constraint on ##\epsilon## carefully can result in a proof that doesn't contain any hand-waving and that is shorter and more intuitive than one that does.
 

1. What does it mean for sup(ST) to equal sup(S)sup(T)?

When we say that sup(ST) is equal to sup(S)sup(T), it means that the supremum (or least upper bound) of the set formed by the product of two sets, S and T, is equal to the product of their respective supremums. In other words, the largest value that can be obtained by multiplying elements from both S and T is equal to the product of the largest values in S and T individually.

2. Can you provide an example to illustrate this equation?

Sure, let's say we have two sets, S = {2, 4, 6} and T = {3, 5, 7}. The supremum of S is 6 and the supremum of T is 7. The product of these two sets, ST, would be {6, 12, 18, 10, 20, 30, 14, 28, 42}. The supremum of ST is 42, which is equal to 6 x 7, the product of the supremums of S and T.

3. Is there a mathematical proof for this equation?

Yes, there is a proof for this equation, which relies on the properties of supremum and the definition of the product of sets. It involves showing that the supremum of the product set, ST, is both an upper bound and the least upper bound for the set, which is equivalent to the product of the supremums of S and T.

4. Does this equation hold true for all sets S and T?

Yes, this equation holds true for all sets S and T, as long as both sets are non-empty and bounded above. This means that there exists a maximum value for both S and T, and thus, a maximum value for their product set, ST.

5. How is this equation relevant in the field of science?

This equation is relevant in fields such as physics, chemistry, and engineering, where concepts of supremum and product sets are commonly used. It can help in solving optimization problems and in understanding the relationship between two sets of data. It also has applications in probability and statistics, as well as in computer science and algorithm design.

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