{ "id": "1909.09046", "version": "v1", "published": "2019-09-19T15:24:12.000Z", "updated": "2019-09-19T15:24:12.000Z", "title": "On the Wasserstein Distance between Classical Sequences and the Lebesgue Measure", "authors": [ "Louis Brown", "Stefan Steinerberger" ], "categories": [ "math.CA", "cs.NA", "math.FA", "math.NA", "math.NT" ], "abstract": "We discuss the classical problem of measuring the regularity of distribution of sets of $N$ points in $\\mathbb{T}^d$. A recent line of investigation is to study the cost ($=$ mass $\\times$ distance) necessary to move Dirac measures placed in these points to the uniform distribution. We show that Kronecker sequences satisfy optimal transport distance in $d \\geq 3$ dimensions. This shows that for differentiable $f: \\mathbb{T}^d \\rightarrow \\mathbb{R}$ and badly approximable vectors $\\alpha \\in \\mathbb{R}^d$, we have $$ \\ | \\int_{\\mathbb{T}^d} f(x) dx - \\frac{1}{N} \\sum_{k=1}^{N} f(k \\alpha) \\ | \\leq c_{\\alpha} \\frac{ \\| \\nabla f\\|^{(d-1)/d}_{L^{\\infty}}\\| \\nabla f\\|^{1/d}_{L^{2}} }{N^{1/d}}.$$ We note that the result is uniformly true for a sequence instead of a set. Simultaneously, it refines the classical integration error for Lipschitz functions, $\\| \\nabla f\\|_{L^{\\infty}} N^{-1/d}$. We obtain a similar improvement for numerical integration with respect to the regular grid. The main ingredient is an estimate involving Fourier coefficients of a measure; this allows for existing estimates to be conviently `recycled'. We present several open problems.", "revisions": [ { "version": "v1", "updated": "2019-09-19T15:24:12.000Z" } ], "analyses": { "keywords": [ "lebesgue measure", "wasserstein distance", "classical sequences", "sequences satisfy optimal transport distance", "kronecker sequences satisfy optimal transport" ], "note": { "typesetting": "TeX", "pages": 0, "language": "en", "license": "arXiv", "status": "editable" } } }