Differentiation of Measures - Key Proof
We prove that if is absolutely continuous, then .
Step 1 (F' exists a.e.): Since is absolutely continuous, it has bounded variation. By Lebesgue's theorem on monotone functions, is differentiable almost everywhere.
Step 2 (F' is integrable): We show . For any partition :
where is the total variation. As the partition refines, this sum approaches (by definition of Lebesgue integral for the derivative). Thus is integrable.
Step 3 (Main equality): Define . We must show for all .
By the first part of FTC, is absolutely continuous and a.e.
Define . Then:
- a.e.
Step 4 (Zero derivative implies constant): We must show that if is absolutely continuous on with and a.e., then for all .
For any and , by absolute continuity there exists such that for any finite collection of disjoint intervals with :
Step 5: Cover by intervals so small that on most of each interval (possible since a.e.). Using absolute continuity and the fact that a.e., we deduce:
Thus for all , so .
Key insights in the proof:
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Absolute continuity is essential: The proof crucially uses both parts of absolute continuity: differentiability a.e. and the ability to recover the function from its derivative.
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Measure zero sets: The fact that outside a measure-zero set is sufficient because integration ignores measure-zero sets.
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Comparison to Riemann integral: For Riemann integration, the FTC requires continuous derivatives. Lebesgue integration allows to be merely integrable, greatly expanding applicability.
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Monotone case first: The proof for monotone functions (which is simpler) uses the Vitali covering lemma. The general case for absolutely continuous functions builds on this.
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Connection to measures: The theorem can be rephrased as: the Radon-Nikodym derivative of the measure with respect to Lebesgue measure is almost everywhere.
This theorem completes the circle: differentiation and integration are inverse operations in the Lebesgue setting, with absolutely continuous functions playing the role of "primitives."