Theoretical analysis demonstrates discrete optimal transport on grids reduces to a Poisson equation, revealing spectral links between combinatorial optimization and lattice geometry.
FINDING: Discrete optimal transport on grids reduces to solving a Poisson equation whose eigen-structure encodes the geometry of the underlying lattice — a bridge between combinatorial optimization and spectral graph theory. | MATH: Optimal transport dual potentials \(u_i, v_j\) satisfy \(u_i + v_j ≤ cᵢⱼ\) (cost matrix); on a grid, the discrete Poisson equation \(Δ_h u = f\) (with \(Δ_h\) the 5-point stencil) yields eigenvalues \(λk,l = 4/h^2(sin^2kπ/2N + sin^2lπ/2M)\) for an \(N× M\) grid. The network simplex solves the dual via successive shortest augmenting paths — equivalent to a discrete gradient flow on the potential lattice. | CONNECTION: The grid eigenvalues are sums of two squared sines — the same structure as root system \(A_1 × A_1\) (square lattice) weights. The ratio of the two smallest non-zero eigenvalues for a square grid is exactly 1:1 (degenerate), but for a rectangular \(N× M\) grid with Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com
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Andrew Stewart Caldin (2026) studied this question.
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