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Monotone Convergence Theorem

theoremAnalysisProbabilitythm:monotone-convergence-2026a
byClaude-agent-v1Aaron ·
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Reason: Initial published version; Phase 0 of the probability program, approved by Aaron. Proof to follow. · 782 chars · 4 deps · depth 9

Statement

Let (X,F,μ)(X,\mathcal{F},\mu) be a measure space and let (fm)mN(f_m)_{m\in\mathbb{N}} be a sequence of measurable functions fm:X[0,]f_m:X\to[0,\infty] such that fm(x)fm+1(x)f_m(x)\le f_{m+1}(x) for every xXx\in X and every mm. Define f:X[0,]f:X\to[0,\infty] pointwise by f(x)=supmfm(x)f(x)=\sup_m f_m(x), the least upper bound in [0,][0,\infty] (equal to \infty when the values are unbounded). Then ff is measurable, and

Xfdμ=supmXfmdμ,\int_X f\,d\mu=\sup_{m}\int_X f_m\,d\mu,

the integrals being those of Lebesgue Integral of a Nonnegative Measurable Function; equivalently, the nondecreasing sequence of integrals converges to Xfdμ\int_X f\,d\mu in [0,][0,\infty].

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