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Lebesgue Integral for Simple Functions

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Measure SpacesSimple Functions and Approximation+1 more→→Lebesgue Integral for Non-Negative Functions
integration lebesgue-integral

Core Idea

For a simple function φ = Σᵢ aᵢ 𝟙ₐᵢ, define ∫φ dμ = Σᵢ aᵢ μ(Aᵢ). This definition is well-defined (independent of representation) and linear. It extends to non-negative functions by taking limits of simple approximations.

Explainer

From your study of simple functions and approximation, you know that a simple function is a finite linear combination of indicator functions of measurable sets: φ = Σᵢ aᵢ 𝟙_{Aᵢ}, where each Aᵢ is a measurable set and each aᵢ is a real number. Think of it as a staircase function — it takes finitely many values, each on a measurable region. The Lebesgue integral of such a function has a natural geometric meaning: it is the sum of (height × measure of base) over each step. That is, ∫φ dμ = Σᵢ aᵢ μ(Aᵢ), where μ(Aᵢ) is the measure (generalized "length" or "size") of the set where φ equals aᵢ.

The first technical hurdle is well-definedness: the same simple function can be written in many different ways. For instance, the function that equals 1 on [0, 1] can be split as 1 · 𝟙_{[0,½]} + 1 · 𝟙_{(½,1]}, or kept as 1 · 𝟙_{[0,1]}. You need the integral to give the same answer regardless of which representation you use. Proving well-definedness requires showing that the sum Σᵢ aᵢ μ(Aᵢ) is the same for any partition of the domain into measurable sets on which φ is constant — a consequence of the additivity of the measure μ you studied when learning measure spaces.

Linearity follows directly from the definition: ∫(αφ + βψ) dμ = α∫φ dμ + β∫ψ dμ for any simple functions φ, ψ and constants α, β. This is the key algebraic fact that makes the integral well-behaved. It also gives the first half of a crucial monotonicity property: if φ ≤ ψ everywhere, then ∫φ dμ ≤ ∫ψ dμ — larger functions integrate to larger values.

The reason for building the integral on simple functions first is strategic: every non-negative measurable function can be approximated from below by an increasing sequence of simple functions. You proved this in the simple-functions approximation topic. The Lebesgue integral for a general non-negative function is then defined as the supremum of the integrals of all simple functions lying beneath it. This construction — define on a tractable class, verify key properties, then extend by limits — is the central pattern of measure theory, and you will see it repeated when the integral is extended to signed and complex-valued functions.

Practice Questions 5 questions

Prerequisite Chain

Understanding Zero → The Number Zero → Counting to Five → Counting to 10 → Counting to 20 → Counting a Set of Objects Up to 20 → Cardinality: The Last Number Counted → Matching Numerals to Quantities → Subitizing Small Quantities → Addition Within 10 → Number Bonds to 10 → Addition Within 20 → Doubles and Near Doubles → Doubles Facts Within 10 → Near Doubles Facts Within 20 → Mental Math Strategies for Addition → Mental Math: Adding and Subtracting Tens → Addition Within 100 → Repeated Addition as Multiplication → Multiplication as Equal Groups → Multiplication: Arrays → Basic Multiplication Facts (0s, 1s, 2s, 5s, 10s) → Multiplication Facts Within 100 → Division as Equal Sharing → Division as Grouping (Measurement Division) → Division: Grouping (Repeated Subtraction) Model → Division: Fair Sharing Model → Division as Equal Sharing → Division as Grouping → Basic Division Facts → Division Facts Within 100 → Multiplication and Division Fact Families → Relationship Between Multiplication and Division → Division Facts as Inverse of Multiplication → Remainders and Quotients in Division → Division Word Problems → Multi-Step Word Problems → Solving Multi-Step Word Problems → Multiplication Word Problems → Division Word Problems → Introduction to Long Division → Factors and Multiples → Prime and Composite Numbers → Equivalent Fractions → Relating Fractions and Decimals → Decimal Place Value → Integers and the Number Line → Comparing and Ordering Integers → Absolute Value → Adding Integers → Subtracting Integers → Multiplying Integers → Introduction to Exponents → Order of Operations → Integer Order of Operations → Variable Expressions → The Distributive Property → Variables and Expressions Review → Introduction to Polynomials → Adding and Subtracting Polynomials → Multiplying Polynomials → Factorial → Permutations → Combinations → Counting Principles: Addition and Multiplication Rules → Introduction to Graph Theory → Propositional Logic Foundations → Logical Equivalences → Set Operations: Union, Intersection, and Complement → Cartesian Products and Relations → Partial Orders → Binary Relations → Equivalence Relations → Injective, Surjective, and Bijective Functions → Cardinality and Countability → Sigma-Algebras and Measurable Sets → Measurable Sets and σ-Algebra Properties → Measure Spaces → Measurable Functions → Simple Functions and Approximation → Lebesgue Integral for Simple Functions

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