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TheoremStatement: AI-adaptedProof: AI-generatedprecheck passaudited 2026-08-30
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The finite-total-variation signed measures form a real normed space

Statement

Fix a measurable space (X,A). With pointwise addition and scalar multiplication, M(X,A) is a real vector space. Moreover, ∥ν∥:=∣ν∣(X) defines a norm on it.

Facts & Assumptions

Given: A measurable space (X,A).

[L1]

M(X,A) consists of the signed measures with ∣ν∣(X)<+∞. (The space of finite total variation signed measures)

[L2]

Total variation is the supremum of unit-bounded simple integrals. (Total variation is the supremum of simple integrals over unit-bounded test functions)

[L3]

A signed-measure null set is exactly a set of zero total variation. (A set is null for a signed measure exactly when its total variation is zero there)

[L4]

A normed space is a real vector space together with a norm satisfying separation, absolute homogeneity, and the triangle inequality. (Vector space over a field, A norm on a real vector space, the induced metric, and the dictionary with the metric axioms)

Proof

technique · direct
1.1L1L2L4

If ν,μ∈M(X,A) and a∈R, then the [L1, L2, L4] pointwise set functions ν+μ and aν are again signed measures because their values are finite on every measurable set and countable additivity is preserved termwise. Also [L2] gives ∣ν+μ∣(X)≤∣ν∣(X)+∣μ∣(X),∣aν∣(X)=∣a∣ ∣ν∣(X), so ν+μ and aν remain in M(X,A). Thus M(X,A) is closed under the pointwise operations, and the vector-space axioms are inherited from the real-valued function space on A.

1.2L1L3L4

The formula ∥ν∥=∣ν∣(X) is nonnegative by definition. If ∥ν∥=0, [L1, L3, L4] then [L3] makes X null for ν, so every measurable set has ν-value 0 and therefore ν is the zero measure. Conversely the zero measure has variation 0. Thus the separation axiom of [L4] holds.

2.1L2L4step 1.1

Step 1.1 already proved absolute homogeneity and the triangle inequality: [L2, L4, step 1.1] ∥aν∥=∣a∣ ∥ν∥,∥ν+μ∥≤∥ν∥+∥μ∥. Hence [L4] shows that ∥⋅∥ is a norm.

3.1step 1.1step 1.2step 2.1

Steps 1.1 through 2.1 prove that M(X,A) is a real [step 1.1, step 1.2, step 2.1] ∎ normed space.

Depends on

Used by

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Sources