A Question on Lebesgue Decomposition

In summary, on the interval [0,1], m does not have a Lebesgue decomposition with respect to μ, as shown by the contradiction arising from choosing a non-measurable set E. This contradicts the conditions required for a Lebesgue decomposition, proving that it does not exist.
  • #1
haljordan45
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Homework Statement



Let μ be the counting measure and m be the Lebesgue measure. Then show that on the interval [0,1] m has no Lebesgue decomposition with respect to μ.

Homework Equations



If such a decomposition exists, then the following holds true where X is the whole space, E is a subset of X, and Xs is the singular subset of the space:

1. m=ma+ms where ma is absolutely continuous and ms is singular
2. ma(E)=∫Efdμ
3. ms(X-Xs)=μ(Xs)=0

The Attempt at a Solution



I know how to show that μ has no Lebesgue decomposition with respect to m, but can't seem to figure out this direction. I'm assuming that I need to pick a set E that contradicts 3 above, but I'm at a loss.
 
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  • #2


To show that m has no Lebesgue decomposition with respect to μ, we need to find a set E such that 3 above is not satisfied. One way to do this is to choose a set E that is not measurable with respect to μ. Let E be a non-measurable subset of [0,1]. Then, by definition of the Lebesgue measure, m(E) = 0 since E is not measurable. However, if we assume that m has a Lebesgue decomposition with respect to μ, then we must have m(E) = ma(E) + ms(E). Since m(E) = 0, this implies that ma(E) = -ms(E). But since ma is absolutely continuous with respect to μ, we must have ma(E) = 0. This would imply that ms(E) = 0, which contradicts the fact that E is a non-measurable set. Therefore, we have shown that on the interval [0,1], m has no Lebesgue decomposition with respect to μ.
 

1. What is Lebesgue decomposition?

Lebesgue decomposition is a mathematical concept in measure theory that allows for the decomposition of a more complex measure into simpler, mutually exclusive measures.

2. How is Lebesgue decomposition different from other decomposition methods?

Lebesgue decomposition differs from other decomposition methods, such as the Radon-Nikodym theorem, in that it does not require one measure to be absolutely continuous with respect to another. This allows for a more general and flexible decomposition.

3. What are the applications of Lebesgue decomposition?

Lebesgue decomposition has applications in various fields, including mathematical analysis, probability theory, and statistics. It is particularly useful in understanding the structure of complex measures and their relationships to simpler measures.

4. Can Lebesgue decomposition be extended to higher dimensions?

Yes, Lebesgue decomposition can be extended to higher dimensions, such as three-dimensional space. This is known as the Lebesgue decomposition theorem for vector measures.

5. Are there any limitations to Lebesgue decomposition?

While Lebesgue decomposition is a powerful tool, it does have some limitations. It may not always be possible to find a unique decomposition for a given measure, and the decomposition may not be unique in some cases. Additionally, the decomposition may not always be intuitive or easy to interpret.

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