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DefinitionDefinition: AI-adaptedProof: Not applicablePipeline-generated
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Legendre weighted spectral-Sobolev scale and projection

Definition

For s≥0, define HLs as the completion of finite Legendre sums p=∑n=0McnPn in the coefficient norm

∥p∥HLs2=∑n=0M(1+n(n+1))s22n+1∣cn∣2.

The coefficients are unique because the polynomials have distinct degrees by Legendre polynomials have explicit norms and weighted derivative orthogonality. At s=0 this norm is exactly the unweighted L2([−1,1]) norm on finite sums, by the same lemma; its completion is denoted LL2. Define the degree-N orthogonal projection on finite sums by

ΠNu=∑n=0NcnPn.

It extends to the coefficient completion by truncation. This explicitly coefficient-defined scale uses the Legendre weight 1 on [−1,1]; no equivalence with an unweighted derivative-based Sobolev norm is asserted here.

For fixed s≥0, x↦xs is nondecreasing on (0,∞): its derivative is sxs−1≥0 by Continuity and derivatives of positive-base real powers and real powers are positive by Real powers for positive bases, with the zero-base positive-exponent convention and The exponential is positive and satisfies exp⁡(−x)=1/exp⁡(x), so the mean-value theorem The mean value theorem, as the case g(x)=x of Cauchy's: for f continuous on [a,b] with a<b and differentiable on (a,b) there is c∈(a,b) with f(b)−f(a)=f′(c)(b−a) applies. Thus the spectral factors (1+n(n+1))s are positive and nondecreasing with n; the full weights wn below need not be nondecreasing.

For wn=(1+n(n+1))s22n+1>0, the coefficient map (cn)↦(wncn) is an isometry onto real ℓ2. Thus the coefficient model of HLs is exactly {(cn)n≥0:∑n≥0(1+n(n+1))s22n+1∣cn∣2<∞}. Finite-support sequences are dense by truncation, and completeness of ℓ2 from The real square-summable sequence space is complete makes this the completion.

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