Uniform spectral convergence of Euclidean graph approximations on the Sierpiński gasket

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Let SG\mathrm{SG} be the Sierpiński gasket with Laplacian L\mathcal{L}. Consider the rescaled averaging Laplacian and the rescaled graph Laplacian at random sample points, both defined using the Euclidean metric on SG\mathrm{SG}. Euclidean spectral convergence conjecture. With a proper choice of normalization and alignment, their eigenvalues and eigenfunctions converge uniformly to those of L\mathcal{L} as n→∞n\to\infty and ϵ(n)→0\epsilon(n)\to0. The conjecture leaves the optimal behavior of ϵ(n)\epsilon(n) for the most accurate convergence unknown and is motivated by numerical investigations and comparison with the cellular semimetric.

References

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Bernard Akwei, Bobita Atkins, Rachel Bailey, Ashka Dalal, Natalie Dinin, Jonathan Kerby-White, Tess McGuinness, Tonya Patricks, Luke Rogers, Genevieve Romanelli, Yiheng Su and Alexander Teplyaev, “Convergence, optimization and stability of singular eigenmaps”, arXiv:2406.19510 (2024).

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