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Lebesgue Integral for Non-Negative Functions

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Core Idea

For non-negative measurable f, define ∫f dμ = sup{∫φ dμ : φ simple, φ ≤ f}. This definition is monotone: f ≤ g implies ∫f ≤ ∫g. The integral may be infinite but is always defined.

Explainer

You already know how to integrate simple functions — those that take only finitely many values on measurable sets. A simple function looks like a staircase: constant on each of finitely many pieces. Integrating it is easy: multiply each constant value by the measure of the set where it achieves that value, then sum. The Lebesgue integral for non-negative functions extends this to every non-negative measurable function by a single elegant move: approximate from below.

The key idea is the supremum definition: ∫f dμ = sup{∫φ dμ : φ simple, 0 ≤ φ ≤ f}. You take all the simple functions that underestimate f everywhere, integrate each one, and then take the least upper bound of all those numbers. If f is itself simple, this recovers the simple function integral. If f is a smooth curve, it approximates f from below with ever-finer staircases. The supremum captures the "total area" even when no single simple function achieves it.

This definition handles two important edge cases cleanly. First, it is always defined — the supremum of a set of non-negative numbers is either a finite non-negative number or +∞, never undefined. A function like 1/√x near 0 may have infinite integral; that's allowed and just equals +∞. Second, it is monotone: if f ≤ g everywhere, then every simple function below f is also below g, so the supremum for f is ≤ the supremum for g. This monotonicity is the engine behind the Monotone Convergence Theorem you'll see next.

Why restrict to non-negative functions first? Because non-negative functions have a clean order structure: if φ ≤ f, then more of φ means more of f. Negative values break this — you could have a function that is sometimes large-positive and sometimes large-negative, and the cancellations make "approximating from below" ambiguous. The general Lebesgue integral (for functions that can be negative) is built on top of this: split f into its positive part f⁺ = max(f, 0) and negative part f⁻ = max(−f, 0), integrate both as non-negative functions, and subtract — but only when at least one is finite to avoid ∞ − ∞.

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 → Lebesgue Integral for Non-Negative Functions

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