Aliasing estimate for ultraspherical rectangular collocation

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Let pn(x;λ)p_n(x;\lambda) be the degree-nn ultraspherical polynomial, let P=(x1,…,xn)P=(x_1,\ldots,x_n) be its roots, and write

Fn(μλ)Pλ→P=[a1a2⋯],\mathbf F_n(\mu_\lambda)\mathbf P_{\lambda\to P}=\begin{bmatrix}\mathbf a_1&\mathbf a_2&\cdots\end{bmatrix},

where aj=ej\mathbf a_j=\mathbf e_j for j=1,…,nj=1,\ldots,n. Here nn and jj are positive integers, and ∥⋅∥ℓ2\|\cdot\|_{\ell^2} denotes the Euclidean norm of the column vector.

Aliasing estimate. There exists c(λ)>0c(\lambda)>0 such that

∥aj∥ℓ2≤c(λ)\|\mathbf a_j\|_{\ell^2}\leq c(\lambda)

for all n,jn,j.

The preceding proposition gives a Frobenius-norm estimate growing linearly with the number of aliased columns; this claim would provide a uniform columnwise bound instead. The supplied text does not state whether the estimate has been proved or disproved.

References

Primary source

Thomas Trogdon, “The ultraspherical rectangular collocation method and its convergence”, arXiv:2401.03608 (2024).

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