Optimal triangulations for piecewise linear approximations of non-convex variable products
Robert Burlacu, Lukas Hager, Robert Hildebrand

TL;DR
This paper determines the optimal triangulation density for piecewise linear approximations of indefinite quadratic functions, showing that allowing variable deviations at vertices significantly improves approximation efficiency.
Contribution
It proves the global optimality of variable deviation triangulations and refutes prior conjectures, revealing lower triangle densities than previously achieved.
Findings
Allowing vertex deviations reduces triangle density by 25% compared to constant deviation methods.
Optimal triangulations for indefinite quadratic functions are significantly more efficient than for definite ones.
Among parallelogram tilings, the constant-deviation construction is proven optimal under continuity constraints.
Abstract
We show optimal triangulations for piecewise linear (PWL) approximations of indefinite quadratic functions over the plane. Optimal triangulations have minimum triangle density while allowing a PWL approximation that fulfills a prescribed error bound measured in the L-infinity norm. In 2000, Pottmann et al. proved optimal triangulations for PWL interpolations and conjectured that these are also optimal for general PWL approximations. This conjecture was refuted in 2018 by Atariah et al., who allowed a constant deviation at the vertices of the triangles and decreased the triangle density by roughly 3%, though they left open whether their construction was optimal. In this paper, we resolve this open question: allowing varying deviations at vertices reduces the optimal triangle density by 25% compared to Atariah et al., and we prove this is globally optimal. We thus show that the potential…
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