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Algebro-combinatorial generalizations of the Victoir method for constructing weighted designs

Hiroshi Nozaki, Masanori Sawa

TL;DR

The paper addresses the problem of constructing small weighted $t$-designs in high dimensions for product measures by generalizing Victoir's method within Euclidean polynomial spaces. It develops a formal algebro-combinatorial reduction framework that allows orthogonal arrays with arbitrary levels to replace structured point sets while preserving the $t$-design property, and extends this to various combinatorial structures and association schemes. Key contributions include an explicit construction of equi-weighted $5$-designs with $O(d^4)$ points for Gaussian and equilibrium measures, a general existence theorem for Gaussian $t$-designs with $N< q^{t} d^{t-1}$, and corollaries that improve Milman-type isometric embedding results. The results provide explicit, scalable designs and connect design theory with isometric embedding phenomena in finite-dimensional Banach spaces, offering a path toward broader multivariate and unitary design analogues.

Abstract

A weighted $t$-design in $\mathbb{R}^d$ is a finite weighted set that exactly integrates all polynomials of degree at most $t$ with respect to a given probability measure. A fundamental problem is to construct weighted $t$-designs with as few points as possible. Victoir (2004) proposed a method to reduce the size of weighted $t$-designs while preserving the $t$-design property by using combinatorial objects such as combinatorial designs or orthogonal arrays with two levels. In this paper, we give an algebro-combinatorial generalization of both Victoir's method and its variant by the present authors (2014) in the framework of Euclidean polynomial spaces, enabling us to reduce the size of weighted designs obtained from the classical product rule. Our generalization allows the use of orthogonal arrays with arbitrary levels, whereas Victoir only treated the case of two levels. As an application, we present a construction of equi-weighted $5$-designs with $O(d^4)$ points for product measures such as Gaussian measure $π^{-d/2} e^{-\sum_{i=1}^d x_i^2} dx_1 \cdots dx_d$ on $\mathbb{R}^d$ or equilibrium measure $π^{-d} \prod_{i=1}^d (1-x_i^2)^{-1/2} dx_1 \cdots dx_d$ on $(-1,1)^d$, where $d$ is any integer at least 5. The construction is explicit and does not rely on numerical approximations. Moreover, we establish an existence theorem of Gaussian $t$-designs with $N$ points for any $t \geq 2$, where $N< q^{t}d^{t-1}=O(d^{t-1})$ for fixed sufficiently large prime power $q$. As a corollary of this result, we give an improvement of a famous theorem by Milman (1988) on isometric embeddings of the classical finite-dimensional Banach spaces.

Algebro-combinatorial generalizations of the Victoir method for constructing weighted designs

TL;DR

The paper addresses the problem of constructing small weighted -designs in high dimensions for product measures by generalizing Victoir's method within Euclidean polynomial spaces. It develops a formal algebro-combinatorial reduction framework that allows orthogonal arrays with arbitrary levels to replace structured point sets while preserving the -design property, and extends this to various combinatorial structures and association schemes. Key contributions include an explicit construction of equi-weighted -designs with points for Gaussian and equilibrium measures, a general existence theorem for Gaussian -designs with , and corollaries that improve Milman-type isometric embedding results. The results provide explicit, scalable designs and connect design theory with isometric embedding phenomena in finite-dimensional Banach spaces, offering a path toward broader multivariate and unitary design analogues.

Abstract

A weighted -design in is a finite weighted set that exactly integrates all polynomials of degree at most with respect to a given probability measure. A fundamental problem is to construct weighted -designs with as few points as possible. Victoir (2004) proposed a method to reduce the size of weighted -designs while preserving the -design property by using combinatorial objects such as combinatorial designs or orthogonal arrays with two levels. In this paper, we give an algebro-combinatorial generalization of both Victoir's method and its variant by the present authors (2014) in the framework of Euclidean polynomial spaces, enabling us to reduce the size of weighted designs obtained from the classical product rule. Our generalization allows the use of orthogonal arrays with arbitrary levels, whereas Victoir only treated the case of two levels. As an application, we present a construction of equi-weighted -designs with points for product measures such as Gaussian measure on or equilibrium measure on , where is any integer at least 5. The construction is explicit and does not rely on numerical approximations. Moreover, we establish an existence theorem of Gaussian -designs with points for any , where for fixed sufficiently large prime power . As a corollary of this result, we give an improvement of a famous theorem by Milman (1988) on isometric embeddings of the classical finite-dimensional Banach spaces.
Paper Structure (12 sections, 23 theorems, 89 equations)

This paper contains 12 sections, 23 theorems, 89 equations.

Key Result

Theorem 2.5

A Euclidean polynomial space $(\Omega, \rho)$ satisfies that $Z(\Omega,r)={\rm Pol}(\Omega,r)$ for any $r \geq 0$.

Theorems & Definitions (52)

  • Definition 2.1: Polynomial space
  • Definition 2.2: Euclidean and spherical polynomial space
  • Example 2.3
  • Example 2.4
  • Theorem 2.5: G1, G2
  • Theorem 2.6: G1, G2
  • Remark 2.7
  • Corollary 2.8
  • Definition 2.9: Weighted $t$-design
  • Example 2.10: Spherical design
  • ...and 42 more