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Monic orthogonal polynomials exist uniquely through the quadrature order

Statement

Let (a,b,m,r,μ) be moment data as in Positive-measure Gaussian quadrature moment data, with m≥1 and r≥2m−1. For each j=0,…,m there is a unique monic real polynomial pj of degree j such that ∫[a,b]pj(x)q(x) dμ(x)=0 for every real polynomial q of degree less than j. For j=0, this means p0=1 and the orthogonality condition is vacuous. The j=m polynomial uses moments only through degree 2m−1; its squared norm is asserted only when the moment datum has order 2m.

Facts & Assumptions

Given: Moment data (a,b,m,r,μ) with r≥2m−1.

[F1]

Positive-measure Gaussian quadrature moment data: μ is finite and positive, its relative support has at least m+1 points, and every absolute moment through order 2m−1 is finite.

[F2]

The polynomial moment pairing is a real inner product: for k=m−1, the coefficient-vector pairing ⟨c,d⟩μ=∫PcPd dμ is a real inner product.

[F3]

Gram–Schmidt turns every finite independent list into an orthonormal list with the same successive spans: Gram–Schmidt applied to a finite independent list in an inner product space gives an orthonormal list with the same successive spans.

[F5]

Rank-nullity: dim⁡FV=nullity⁡T+rank⁡T: for a linear map from a finite-dimensional vector space to itself, trivial kernel implies full-dimensional image and hence surjectivity.

[F6]

The Lebesgue integral is linear on L1(μ): finite polynomial expansions may be integrated term by term whenever the displayed moments are finite.

[F7]

Formal real polynomials, evaluation, degree, leading coefficient, and monic polynomials and A finite coefficient vector has a canonical polynomial representative: a coefficient vector represents a formal polynomial; a nonzero highest coefficient determines its degree and leading coefficient.

[F8]

The reals form a field: every nonzero real coefficient has a multiplicative inverse.

Proof

1.1F2F3F4F7F8construct

By [F2], the pairing on the coefficient space Rm for degrees at most m−1 is an inner product. The list e0,…,em−1 is independent by [F4], so [F3] gives orthonormal coefficient vectors u0,…,um−1 whose first j+1 vectors span the same space as e0,…,ej. The polynomial Puj therefore has degree exactly j: it lies in the span of 1,x,…,xj but not in the span through degree j−1. Dividing by its nonzero leading coefficient, which is invertible by [F8], gives a monic pj, orthogonal to every polynomial of degree less than j.

1.2F1F2F4F5algebra

Put Gik=∫xi+k dμ for 0≤i,k<m, and bi=∫xi+m dμ. All entries are finite by [F1]. The matrix G represents the inner product of [F2] in the standard basis. If Gc=0, then cTGc=⟨c,c⟩μ=0, so [F2] gives c=0. Thus the linear map G:Rm→Rm has trivial kernel; [F5] makes it surjective. There is therefore a unique coefficient vector c solving Gc=−b.

2.1F1F2F6F7step 1.2algebraconstruct

Define pm(X)=Xm+∑k=0m−1ckXk. Its leading coefficient is 1, and the ith equation of Gc=−b gives ∫pm(x)xi dμ(x)=0 for each i<m. Linearity [F6] extends this equality to every polynomial of degree less than m. If another monic polynomial had the same orthogonality, its difference from pm would have degree at most m−1 and pair to zero with itself; positive definiteness [F2] makes that difference zero.

3.1step 1.1step 1.2step 2.1∎

Step 1.1 gives the unique monic polynomials below degree m, and steps 1.2–2.1 give the unique degree-m polynomial using only moments through 2m−1. This proves the assertion for every j=0,…,m.

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