Riemann integration in R^n

In summary, by using the fact that continuous functions are sign preserving and the compactness of A, we can show that if there exists some a in A with f(a) > 0, then the integral over A of f is also positive. Furthermore, by using the relevant theorem and the fact that we only need one point where f is positive, we can extend this result to bounded and integrable functions on closed rectangles.
  • #1
snipez90
1,101
5

Homework Statement


a) Let A in R^n be compact, and let f: A -> R be continuous and also non-negative. Show that if there exists some a in A with f(a) > 0, then [itex]\int_{A}f > 0[/itex]
b) Now let A in R^n be a closed rectangle, and suppose f: A -> R be bounded and integrable. Show that if f(x) > 0 for all x in A, then [itex]\int_{A}f > 0.[/itex]

2. Relevant theorems
A function is Riemann integrable iff its set of discontinuities has measure zero.

The Attempt at a Solution


a) For this, all we need is the fact that continuous functions are sign preserving right (of course f is integrable)? Specifically we can find a [itex]\delta > 0[/itex] such that for all x in the ball of radius [itex]\delta,[/itex] [itex]|f(x) - f(a)| < f(a) \Rightarrow f(x) > 0.[/itex] Then we can choose our partition so that some subrectangle, say S_i is contained in the ball. Hence the supremum (or infimum, I don't think it matters) of f over this subrectangle is actually equal to f(y) for some y in S_i due to compactness, so the upper sum (or lower sum) is > 0 (> 0 contribution from f over S_i, f is nonnegative elsewhere), so we are done. Does this work?

b) I'm less sure about this one, but I think it follows from a) since we can find infinitely many points on A at which f is continuous (due to the relevant theorem), and we really only need one point. Again sups and infs are achieved due to compactness which follows from Heine-Borel.

Thanks
 
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  • #2
for your post! Your approach for part a) seems correct. Since f is continuous and non-negative, we can find a small enough ball around a such that f(x) is always positive in this ball. Then, as you mentioned, we can choose a partition that contains this ball and the upper sum will be positive due to the contribution from this subrectangle.

For part b), I think your reasoning is correct. By the relevant theorem, we can find infinitely many points where f is continuous, and therefore, we can find a ball around each of these points such that f(x) is always positive in this ball. Then, we can choose a partition that contains all of these balls and the upper sum will be positive due to the contributions from each subrectangle. Therefore, the overall integral must also be positive.
 

1. What is Riemann integration in R^n?

Riemann integration in R^n is a mathematical concept that extends the concept of integration from one-dimensional spaces to n-dimensional spaces. It involves finding the area under a function in n-dimensional space by breaking it down into smaller, simpler parts and summing them up.

2. How is Riemann integration different from other types of integration?

Riemann integration is different from other types of integration, such as Lebesgue integration, in that it focuses on partitioning the domain of integration into smaller intervals and approximating the area under the function using rectangles. This makes it easier to calculate the integral in higher dimensions.

3. What are the benefits of using Riemann integration in R^n?

Riemann integration in R^n allows for the calculation of integrals in higher dimensions, which is useful in many areas of mathematics and science. It also provides a more intuitive approach to integration, as it involves breaking down the function into smaller parts and summing them up.

4. How is Riemann integration in R^n used in real-world applications?

Riemann integration in R^n is used in various fields, such as physics, engineering, and economics, to calculate the volume or mass of objects in higher dimensions. It is also used in image processing and computer graphics to calculate areas and volumes of objects in 3D space.

5. What are some challenges of using Riemann integration in R^n?

One challenge of Riemann integration in R^n is that as the number of dimensions increases, the number of partitions needed to accurately calculate the integral also increases, making the computation more complex. Additionally, Riemann integration may not be applicable for certain types of functions, such as discontinuous functions or functions with infinite discontinuities.

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