English

Exponential polynomials and identification of polygonal regions from Fourier samples

Classical Analysis and ODEs 2025-10-15 v2 Numerical Analysis Metric Geometry Numerical Analysis

Abstract

Consider the set E(D,N)E(D, N) of all bivariate exponential polynomials f(ξ,η)=j=1npj(ξ,η)e2πi(xjξ+yjη), f(\xi, \eta) = \sum_{j=1}^n p_j(\xi, \eta) e^{2\pi i (x_j\xi+y_j\eta)}, where the polynomials pjC[ξ,η]p_j \in \mathbb{C}[\xi, \eta] have degree <D<D, nNn\le N and where xj,yjT=R/Zx_j, y_j \in \mathbb{T} = \mathbb{R}/\mathbb{Z}. We find a set AZ2A \subseteq \mathbb{Z}^2 that depends on NN and DD only and is of size O(D2NlogN)O(D^2 N \log N) such that the values of ff on AA determine ff. Notice that the size of AA is only larger by a logarithmic quantity than the number of parameters needed to write down ff. We use this in order to prove some uniqueness results about polygonal regions given a small set of samples of the Fourier Transform of their indicator function. If the number of different slopes of the edges of the polygonal region is k\le k then the region is determined from a predetermined set of Fourier samples that depends only on kk and the maximum number of vertices NN and is of size O(k2NlogN)O(k^2 N \log N). In the particular case where all edges are known to be parallel to the axes the polygonal region is determined from a set of O(NlogN)O(N \log N) Fourier samples that depends on NN only. Our methods are non-constructive.

Keywords

Cite

@article{arxiv.2409.01432,
  title  = {Exponential polynomials and identification of polygonal regions from Fourier samples},
  author = {Mihail N. Kolountzakis and Emmanuil Spyridakis},
  journal= {arXiv preprint arXiv:2409.01432},
  year   = {2025}
}

Comments

16 pages, 7 figures