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Periodic multilinear interpolation is convex and L-infinity contractive
Statement
For the periodic tensor interpolant of Periodic tensor grids and multilinear interpolation, every value is a convex combination of the corner data. Consequently nonnegative data remain nonnegative, the interpolant lies between the minimum and maximum corner values, and for any node arrays , These conclusions hold at every foot, with no displacement-to-cell-size restriction.
Facts & Assumptions
Given: The periodic grid, a lifted query point , and finite real node arrays .
Periodic tensor grids and multilinear interpolation: the coordinate fractions satisfy and the corner weights are , with wrapped node indices.
Proof
Each factor and is nonnegative, so every . Summing over all binary vectors factorizes as . Thus is a convex combination of its corner data, even when wrapping makes two corner indices coincide.
If at every node, each summand in the interpolant is nonnegative, so its value is nonnegative; the same convex-combination identity bounds it by the minimum and maximum corner data.
At each , [F1] and the triangle inequality give . Taking the supremum over proves the stated contraction; no estimate in this argument uses the displacement size.
Depends on
Used by
- A constant-speed foot can cross many cells in one stable update Example
- Positive partition of unity and interpolation error for periodic multilinear interpolation Lemma
- Tensor multilinear interpolation has a second-derivative error bound Lemma
- Periodic semi-Lagrangian error is controlled by local foot and interpolation defects Theorem
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Sources
- European Centre for Medium-Range Weather Forecasts, Numerical Methods, Meteorological Training Course Lecture Series, 2002 (standard reference, not scraped)
- Lukas Einkemmer and Alexander Ostermann, On the error propagation of semi-Lagrange and Fourier methods for advection problems, Computers & Mathematics with Applications 69 (2015), 170–179 (standard reference, not scraped)