Quartic Fekete points on every real simplex

Primarily AI-generated textHuman understanding: no partsmath.NA — Numerical Analysis

Contributed by Yunpeng Li ↗

Version 1 / Nov 06, 2026 / CC BY 4.0

Abstract

We prove that on every real simplex Bos's quartic interpolation nodes uniquely maximize the absolute Vandermonde determinant, up to ordering, among all configurations of the prescribed size. In dimension four the squared Euclidean norm of the cardinal vector exceeds one at the centroid. We bound its excess by products of the cardinal polynomials for tetrahedral face centers. These products also measure correlations between columns of the evaluation matrix, which give the required loss in the determinant. An elementary consequence of the same corrected squared-norm estimate is Bos's fourth-power bound in every dimension, with equality exactly at the nodes. The corrected estimate follows from cubic perturbations, reduction to at most two distinct positive coordinate values, and coefficient monotonicity in their multiplicities. All polynomial bounds are given explicitly. The common base case is the tetrahedral Fej\'er bound previously stated by Panda and Pal in equivalent optimal-design form. We give an independent proof of that bound and determine all its equality points.

References

  1. L. Bos, Bounding the Lebesgue function for Lagrange interpolation in a simplex, J. Approx. Theory 38 (1983), 43--59. doi:10.1016/0021-9045(83)90140-5 (https://doi.org/10.1016/0021-9045(83)90140-5).DOI
  2. L. Bos, Some remarks on the Fejér problem for Lagrange interpolation in several variables, J. Approx. Theory 60 (1990), 133--140. doi:10.1016/0021-9045(90)90078-5 (https://doi.org/10.1016/0021-9045(90)90078-5).DOI
  3. L. Bos, On certain configurations of points in Rn\R^n which are unisolvent for polynomial interpolation, J. Approx. Theory 64 (1991), 271--280. doi:10.1016/0021-9045(91)90063-G (https://doi.org/10.1016/0021-9045(91)90063-G).DOI
  4. L. Bos, On Fekete points for a real simplex, Indag. Math. (N.S.) 34 (2023), 274--293. doi:10.1016/j.indag.2022.11.003 (https://doi.org/10.1016/j.indag.2022.11.003). Preprint version: arXiv:2205.06498v1 (https://arxiv.org/html/2205.06498v1).arXivDOI
  5. S. Boyd and L. Vandenberghe, Convex Optimization , Cambridge University Press, Cambridge, 2004. Authors' online edition (https://stanford.edu/~boyd/cvxbook/).link
  6. L. Fejér, Bestimmung derjenigen Abszissen eines Intervalles, für welche die Quadratsumme der Grundfunktionen der Lagrangeschen Interpolation im Intervalle ein möglichst kleines Maximum besitzt, Ann. Scuola Norm. Super. Pisa Cl. Sci. (2) 1 (1932), 263--276. Numdam (https://www.numdam.org/article/ASNSP_1932_2_1_3_263_0.pdf).link
  7. J. Garloff, The Bernstein algorithm, Interval Comput. (1993), no. 2, 154--168. Journal PDF (https://interval.louisiana.edu/reliable-computing-journal/1993/interval-computations-1993-2-pp-154-168.pdf).link
  8. R. A. Horn and C. R. Johnson, Matrix Analysis , 2nd ed., Cambridge University Press, Cambridge, 2013. doi:10.1017/CBO9781139020411 (https://doi.org/10.1017/CBO9781139020411).DOI
  9. W. James and C. Stein, Estimation with quadratic loss, in Proc. Fourth Berkeley Symp. Math. Statist. Probab. , vol. 1, University of California Press, Berkeley, 1961, 361--379. Paper (https://www.math.tau.ac.il/~yekutiel/eBayes/james_stein_1961.pdf).link
  10. J. Kiefer and J. Wolfowitz, The equivalence of two extremum problems, Canad. J. Math. 12 (1960), 363--366. doi:10.4153/CJM-1960-030-4 (https://doi.org/10.4153/CJM-1960-030-4).DOI
Show all 16 referencesShow fewer references
  1. A. Orlitsky, N. P. Santhanam, K. Viswanathan and J. Zhang, On modeling profiles instead of values, in Proceedings of the Twentieth Conference on Uncertainty in Artificial Intelligence , AUAI Press, 2004, 426--435. arXiv:1207.4175 (https://arxiv.org/abs/1207.4175).arXiv
  2. M. K. Panda and M. Pal, D-optimal designs for quartic polynomial model for mixture experiment with three and four ingredients, Calcutta Stat. Assoc. Bull. 78 (2026), no. 1, 79--88. Published online 15 September 2025. doi:10.1177/00080683251366118 (https://doi.org/10.1177/00080683251366118).DOI
  3. V. Powers and B. Reznick, A new bound for Pólya's theorem with applications to polynomials positive on polyhedra, J. Pure Appl. Algebra 164 (2001), 221--229. doi:10.1016/S0022-4049(00)00155-9 (https://doi.org/10.1016/S0022-4049(00)00155-9).DOI
  4. C. Riener, On the degree and half-degree principle for symmetric polynomials, J. Pure Appl. Algebra 216 (2012), 850--856. doi:10.1016/j.jpaa.2011.08.012 (https://doi.org/10.1016/j.jpaa.2011.08.012). Preprint with the cited numbering (https://arxiv.org/html/1001.4464v2).DOI
  5. M. A. Taylor, B. A. Wingate and R. E. Vincent, An algorithm for computing Fekete points in the triangle, SIAM J. Numer. Anal. 38 (2000), 1707--1720. doi:10.1137/S0036142998337247 (https://doi.org/10.1137/S0036142998337247).DOI
  6. V. Timofte, On the positivity of symmetric polynomial functions. Part I: General results, J. Math. Anal. Appl. 284 (2003), 174--190. doi:10.1016/S0022-247X(03)00301-9 (https://doi.org/10.1016/S0022-247X(03)00301-9).DOI

Version history

  1. v1 · 28 pagesSubmitted by Yunpeng LiInitial depositCurrentNov 06, 2026