Minimum value on an open continuous function

In summary, the problem is asking to prove that a continuous function on (a,b) with limits of infinity at both endpoints must have a minimum on the interval. One approach to this is to consider different regions of the function and use the continuity of f to make a statement about the function in the "not close to a or b" region. Another helpful strategy is to try to construct a function that goes to infinity at a and b, but does not have a minimum on (a,b).
  • #1
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Homework Statement



Suppose that f is a continuous function on (a,b) and [itex]lim_{x \rightarrow a^{+}} f(x) = lim_{x \rightarrow b^{-}} f(x) = \infty.[/itex] prove that f has a minimum on all of (a,b)



The Attempt at a Solution



I have not tried an actual attempt yet. The only think I can think of doing is making two sequences that approach a common point on the domain of f. One sequence starting at a, and the other starting at b. Then show that the range of these sequences is decreasing and tends to the same value. This seems a bit too complicated to me for such a problem.

I am interested in where to start. Logically, it makes sense to me that there should be a minimum. I just don't know how to explain it using math.

Thanks.
 
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  • #2
A good way to think about these problems is that you have a couple different regions: if x is close to a, or close to b, then you know f(x) is really big. If f is not close to either of those, all you really know is that f is continuous. So you need to use something (probably a theorem) involving the continuity of f to make a statement about f in this region that I have vaguely described as "not close to a or b". You of course should make that description mathematically more precise first!
 
  • #3
If you start at a and travel towards b, you will have that ##f(x) < lim_{x \rightarrow a^+}f(x) = \infty##. Yet by the time you get back to ##b^-## you are back at ## \infty ##. How did that happen?

If you are not sure where the continuity fits in, try constructing a function which goes to ## \infty## at a and b, but does not have a minimum on (a,b).
 

FAQ: Minimum value on an open continuous function

What is the definition of a minimum value on an open continuous function?

A minimum value on an open continuous function is the smallest value that the function takes on within a certain interval of its domain. This means that there are no smaller values that the function can attain within that specific interval.

How is the minimum value on an open continuous function different from the minimum value on a closed continuous function?

The minimum value on an open continuous function is the smallest value within a given interval, while the minimum value on a closed continuous function is the smallest value that the function takes on within its entire domain. The open interval allows for the function to take on smaller values outside of the given interval, while the closed interval includes all values within the domain.

Is it possible for an open continuous function to not have a minimum value?

Yes, it is possible for an open continuous function to not have a minimum value. This can happen if the function has a horizontal asymptote or if the function continues to decrease indefinitely without reaching a minimum value within the given interval.

How can the minimum value on an open continuous function be found mathematically?

The minimum value on an open continuous function can be found by taking the derivative of the function and setting it equal to zero. Then, solving for the value of x that satisfies this equation will give the x-coordinate of the minimum value point. Plugging this value into the original function will give the corresponding y-coordinate of the minimum value.

What is the significance of the minimum value on an open continuous function?

The minimum value on an open continuous function can provide important information about the behavior and characteristics of the function. It can indicate the lowest point on the graph, the location of a local minimum, and the rate of change of the function. It can also be used to solve optimization problems in real-world applications.

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