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Riesz Representation Theorem (Hilbert)

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Dual Spaces and Bounded Linear FunctionalsOrthogonality in Hilbert Spaces+1 moreBessel's Inequality and Parseval's Identity
hilbert-spaces duality

Core Idea

Every bounded linear functional f on a Hilbert space H has the form f(x) = ⟨x, y⟩ for a unique y ∈ H. This natural isomorphism H ≅ H* is special to Hilbert spaces and fails in general Banach spaces.

Explainer

From your study of dual spaces and bounded functionals, you know that H* — the dual of a Hilbert space H — is the space of all bounded linear maps f: H → ℝ (or ℂ). These are the "measurements" you can make: each f takes a vector and returns a number, linearly and continuously. The abstract question is: what do all possible bounded functionals look like? The Riesz Representation Theorem answers this completely — every bounded functional is just an inner product with a fixed vector.

The geometric intuition comes from your understanding of orthogonality in Hilbert spaces. A bounded linear functional f: H → ℝ has a kernel — the closed subspace of all x with f(x) = 0. If f is not identically zero, its kernel has a one-dimensional orthogonal complement. Any vector y in that complement, appropriately normalized, satisfies f(x) = ⟨x, y⟩ for all x. In other words, "measuring x with f" is equivalent to "projecting x onto the direction y." The inner product already computes the projection, so inner products and bounded functionals are the same thing.

More carefully: fix a nonzero bounded functional f. The kernel ker(f) is a closed subspace, so by your orthogonal decomposition results, H = ker(f) ⊕ ker(f)^⊥. The orthogonal complement is one-dimensional — pick any unit vector z in it. Every x ∈ H decomposes as x = (x − f(x)/f(z) · z) + f(x)/f(z) · z. The first part lies in ker(f), the second is a scalar multiple of z. Setting y = f(z)·z̄ (conjugated in the complex case), you get f(x) = ⟨x, y⟩. Uniqueness follows because if ⟨x, y⟩ = ⟨x, y'⟩ for all x, then y = y'.

The consequence is the isomorphism H ≅ H*: the map y ↦ ⟨·, y⟩ is a bijection from H onto H*. This is why Hilbert spaces are called self-dual — a Hilbert space "knows" its own dual. This fails in general Banach spaces: the dual of Lp is Lq (with 1/p + 1/q = 1), which is a different space unless p = 2. The inner product is the special structure that collapses this distinction. For applications — including quantum mechanics, where states live in L² and observables are bounded functionals — this self-duality is indispensable: every observable corresponds to a unique state vector, and vice versa.

Practice Questions 5 questions

Prerequisite Chain

Understanding ZeroThe Number ZeroCounting to FiveCounting to 10Counting to 20Counting a Set of Objects Up to 20Cardinality: The Last Number CountedMatching Numerals to QuantitiesSubitizing Small QuantitiesAddition Within 10Number Bonds to 10Addition Within 20Doubles and Near DoublesDoubles Facts Within 10Near Doubles Facts Within 20Mental Math Strategies for AdditionMental Math: Adding and Subtracting TensAddition Within 100Repeated Addition as MultiplicationMultiplication as Equal GroupsMultiplication: ArraysBasic Multiplication Facts (0s, 1s, 2s, 5s, 10s)Multiplication Facts Within 100Division as Equal SharingDivision as Grouping (Measurement Division)Division: Grouping (Repeated Subtraction) ModelDivision: Fair Sharing ModelDivision as Equal SharingDivision as GroupingBasic Division FactsDivision Facts Within 100Multiplication and Division Fact FamiliesRelationship Between Multiplication and DivisionDivision Facts as Inverse of MultiplicationRemainders and Quotients in DivisionDivision Word ProblemsMulti-Step Word ProblemsSolving Multi-Step Word ProblemsMultiplication Word ProblemsDivision Word ProblemsIntroduction to Long DivisionFactors and MultiplesPrime and Composite NumbersEquivalent FractionsRelating Fractions and DecimalsDecimal Place ValueIntegers and the Number LineComparing and Ordering IntegersAbsolute ValueAdding IntegersSubtracting IntegersMultiplying IntegersIntroduction to ExponentsOrder of OperationsInteger Order of OperationsVariable ExpressionsThe Distributive PropertyVariables and Expressions ReviewIntroduction to PolynomialsAdding and Subtracting PolynomialsMultiplying PolynomialsFactorialPermutationsCombinationsCounting Principles: Addition and Multiplication RulesIntroduction to Graph TheoryPropositional Logic FoundationsLogical EquivalencesDe Morgan's LawsNegation of Quantified StatementsProof by ContradictionTopological Spaces: Definition and ExamplesOpen Sets in Topological SpacesNeighborhoods and Open SetsOpen Sets in Topological SpacesBasis for a TopologyMetric TopologyCompleteness in Metric SpacesBanach SpacesBounded Linear OperatorsThe Operator NormDual Spaces and Bounded Linear FunctionalsWeak ConvergenceWeak* ConvergenceReflexive SpacesRiesz Representation Theorem (Hilbert)

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