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Monic orthogonal polynomials satisfy a three-term recurrence
Statement
Let be moment data from Positive-measure Gaussian quadrature moment data with , and let be the monic orthogonal polynomials of Monic orthogonal polynomials exist uniquely through the quadrature order. For put For put . These numbers are defined, , and . The recurrence is and, for , Only moments through degree are used.
Facts & Assumptions
Given: The stated moment data and monic orthogonal family.
Positive-measure Gaussian quadrature moment data: moments through degree are finite.
The polynomial moment pairing is a real inner product: the moment pairing is symmetric, bilinear, and positive definite on each such space.
Monic orthogonal polynomials exist uniquely through the quadrature order: each is monic of degree and orthogonal to every polynomial of smaller degree.
Degree inequalities for sums and products over a commutative ring: a sum with cancellation of top coefficients has degree bounded by the largest remaining degree; the leading coefficient of a product is the product of leading coefficients.
The Lebesgue integral is linear on and The reals form a field: the displayed polynomial integrals are linear and real division by a nonzero norm is defined.
Proof
For , and have degrees at most and , both at most . Thus the moments in and are finite by [F1]. Since is nonzero, [F2] gives , so is defined; for , the same positivity for gives .
The polynomials form a basis for the polynomials of degree at most : their distinct degrees and unit leading coefficients permit successive subtraction of the top term. Because has degree at most by cancellation of the leading term, write it in this basis.
For , symmetry of the real pairing gives , since has degree at most . As the basis in step 1.2 is orthogonal and each squared norm is positive by [F2], the expansion has no term for . Its coefficient is .
For , the coefficient is Indeed, has degree at most , so it is orthogonal to by [F3].
The expansion in step 1.2 therefore has only the displayed and, when , terms. Rearranging it yields the stated recurrence for every .
Depends on
- Positive-measure Gaussian quadrature moment data
- The polynomial moment pairing
- The polynomial moment pairing is a real inner product
- Monic orthogonal polynomials exist uniquely through the quadrature order
- The polynomial ring over a commutative ring as finitely supported coefficient sequences with convolution
- Degree inequalities for sums and products over a commutative ring
- The Lebesgue integral is linear on $L^1(\mu)$
- The reals form a field
Used by
- Certified Gaussian nodes and weights by Golub–Welsch Algorithm
- The two-node Gauss–Legendre rule is exact through degree three Example
- Certified Golub–Welsch intervals contain the Gaussian nodes and weights Theorem
- Consecutive Gaussian orthogonal polynomials and Jacobi truncations strictly interlace Theorem
- Gaussian weights equal the total mass times a Jacobi eigenvector's first-coordinate square Theorem
- The Jacobi matrix spectrum is the set of Gauss nodes Theorem
Dependency tree · two levels
39 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- John A. Gubner, Gaussian Quadrature and the Eigenvalue Problem, §§2–5, 2020 (standard reference, not scraped)
- MATH 373 Lecture Notes, Lecture 14: Gaussian Quadrature, §§10.2–10.5 (standard reference, not scraped)
- Walter Gautschi, The Interplay Between Classical Analysis and (Numerical) Linear Algebra, §2.1 (standard reference, not scraped)