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If is sigma-finite and is countably generated, then is separable for
Statement
Assume the Axiom of Countable Choice.
Let be a sigma-finite measure space with countably generated sigma-algebra, and let . Then is separable.
Facts & Assumptions
Given: The Axiom of Countable Choice, a sigma-finite countably generated measure space, and an exponent .
Simple functions with finite-measure support are dense in (Simple functions with finite-measure support are dense in for ).
Finite-measure sets are approximable by a countable generating algebra (Finite-measure sets are approximable in measure by sets from a countable generating algebra, A countable generator of a sigma-algebra yields a countable algebra of sets).
The quotient is the space in question, and separability means the existence of a countable dense subset (The space as the quotient by null functions, Separability: the existence of an at most countable dense subset).
Proof
Let be the countable algebra from [L2], and let [L2, L3, given, algebra] be the set of all finite linear combinations with and satisfying for every . Because both the coefficient set and the finite-measure members of are countable, is countable.
To prove density, start with and . By [L1, L2, given, choose, algebra] [L1], choose a finite-support simple function with . For each , [L2] gives with and arbitrarily small, and each coefficient can be approximated by . The resulting lies in and satisfies .
Then [L3, step 1.1, step 1.2] So is countable and dense in ; by [L3], the space is separable.
Depends on
- Simple functions with finite-measure support are dense in $L^p(\mu)$ for $1 \le p < \infty$
- A countable generator of a sigma-algebra yields a countable algebra of sets
- Finite-measure sets are approximable in measure by sets from a countable generating algebra
- Finite, sigma-finite, and semifinite measures
- Separability: the existence of an at most countable dense subset
- The space $L^p(\mu)$ as the quotient by null functions
Used by
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Sources
- Richard L. Wheeden and Antoni Zygmund, Measure and Integral: An Introduction to Real Analysis (standard reference, not scraped)