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Simple functions with finite-measure support are dense in for
Statement
Let be a measure space and let . Then every element of can be approximated in by simple functions whose supports have finite measure.
Facts & Assumptions
Given: A measure space, an exponent , and .
Every measurable function admits dominated simple approximations (Every measurable function admits simple approximations dominated by its absolute value).
Dominated convergence applies in (Dominated convergence).
Elements of are almost-everywhere classes, so one may choose a measurable representative when making pointwise constructions (The space as the quotient by null functions).
Proof
Choose a measurable representative of by [L3]. For each [L1, L3, given, choose, construct] , [L1] gives a simple function with and for every . Define Then each is simple and .
Since is integrable, [step 1.1, algebra] so every has finite-measure support. Also for every : if then eventually both sides are , and if then for all large . Finally whose right-hand side is integrable.
Applying [L2] to gives [L2, step 2.1] So the simple functions with finite-measure support are dense in .
Depends on
Used by
- The regular representation of the real line as a multiplicity-one integral of characters Example
- C_c(X) is dense in Lᵖ(mu) for a Radon measure Theorem
- Complex finite-simple and smooth compact-support density for finite p Theorem
- Finite linear combinations of box indicators are dense in Lᵖ(ℝⁿ) for 1 ≤ p < ∞ Theorem
- If μ is sigma-finite and A is countably generated, then Lᵖ(μ) is separable for 1 ≤ p < ∞ Theorem
Dependency tree · two levels
19 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- John K. Hunter, Measure Theory (standard reference, not scraped)