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Eigenfunction Expansions and Sturm-Liouville Theory

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Fourier Series: Definition and CoefficientsSeparation of Variables for Partial Differential Equations+1 moreSpectral Theory for Elliptic Operators
pde sturm-liouville eigenfunction spectral orthogonal-expansion

Core Idea

Sturm-Liouville theory generalizes Fourier series by showing that a wide class of second-order boundary value problems -(p(x)y')' + q(x)y = λw(x)y produce an orthogonal basis of eigenfunctions for an appropriate function space. Any sufficiently well-behaved function can be expanded in this eigenbasis, just as functions can be expanded in sines and cosines. This framework unifies the separation of variables technique: when a PDE is separated, the spatial part typically yields a Sturm-Liouville problem whose eigenfunctions provide the building blocks for the solution.

Explainer

Sturm-Liouville theory provides the spectral framework that underlies the separation of variables method for PDEs. When we separate variables in the heat equation on a finite interval, the spatial part satisfies X'' + λX = 0 with boundary conditions—the simplest Sturm-Liouville problem. Its eigenfunctions sin(nπx/L) form an orthogonal basis, and the solution is a Fourier sine series with time-dependent coefficients that decay exponentially. Sturm-Liouville theory shows this is not a coincidence but a general phenomenon.

A regular Sturm-Liouville problem has the form -(p(x)y')' + q(x)y = λw(x)y on [a,b] with separated boundary conditions, where p > 0, w > 0, and all coefficients are continuous. The operator L[y] = -(py')' + qy is self-adjoint with respect to the weighted inner product ⟨f,g⟩ = ∫f(x)g(x)w(x)dx. Self-adjointness guarantees that all eigenvalues are real, eigenfunctions for distinct eigenvalues are orthogonal, and the eigenvalues form an unbounded increasing sequence. The eigenfunctions form a complete orthonormal basis for L²([a,b], w).

The completeness of the eigenfunctions means that any square-integrable function f can be expanded as f(x) = Σ c_n φ_n(x), where the coefficients are c_n = ⟨f, φ_n⟩/⟨φ_n, φ_n⟩. This expansion converges in the L² sense, and under additional smoothness assumptions on f, it converges uniformly. This is the generalized Fourier series, and it reduces to ordinary Fourier series when p = w = 1 and q = 0. Different choices of p, q, and w yield expansions in Legendre polynomials (spherical geometry), Bessel functions (cylindrical geometry), and other classical families.

Singular Sturm-Liouville problems arise when p vanishes at an endpoint, the interval is infinite, or the coefficients are unbounded. These require more delicate analysis but remain tractable. The Bessel equation and Legendre equation are singular Sturm-Liouville problems, and their eigenfunction expansions (Fourier-Bessel series and Legendre series) are essential for solving PDEs in cylindrical and spherical coordinates. The general spectral theorem for unbounded self-adjoint operators in Hilbert spaces provides the rigorous foundation for these expansions, connecting Sturm-Liouville theory to functional analysis.

Practice Questions 4 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 IntegersDividing IntegersUnit RatesProportionsPercent ConceptConverting Between Fractions, Decimals, and PercentsOperations with Rational NumbersTwo-Step EquationsSolving Multi-Step EquationsEquations with Variables on Both SidesAngle Pairs: Complementary, Supplementary, and VerticalParallel Lines and TransversalsCorresponding AnglesAlternate Interior AnglesTriangle Angle Sum TheoremExterior Angle TheoremTriangle Inequality TheoremSimilar Triangles: AA SimilaritySimilar Triangles: SSS and SAS SimilarityProportions in Similar TrianglesRight Triangle Trigonometry IntroductionSine, Cosine, and Tangent RatiosTrigonometric Ratios ReviewRadian MeasureConverting Between Degrees and RadiansThe Unit CircleGraphing Sine and CosineGraphing Tangent and Reciprocal Trigonometric FunctionsDerivatives of Trigonometric FunctionsAntiderivativesIndefinite IntegralsBasic Integration RulesRiemann SumsDefinite Integral DefinitionFundamental Theorem of Calculus Part 1Fundamental Theorem of Calculus Part 2U-SubstitutionSeparable Equations (Intro)Separable Differential EquationsIntegrating Factor Method for First-Order Linear ODEsFirst-Order Linear Ordinary Differential EquationsSecond-Order Linear Homogeneous Differential EquationsCharacteristic Equation Method for Linear ODEsRepeated Roots and Reduction of OrderWronskian and Linear IndependenceMethod of Undetermined CoefficientsHigher-Order Linear Differential EquationsSystems of First-Order Linear Differential EquationsSeparation of Variables for Partial Differential EquationsEigenfunction Expansions and Sturm-Liouville Theory

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