Searcharxiv⌕ Search

arXiv · 2609.32526

Almost norming vertices for homogeneous polynomials on the cube

Abstract

Let $m\geq1$ be fixed. We consider the space $\mathcal{P}_m(\mathbb{R}^n)$ of real $m$-homogeneous polynomials on $\mathbb{R}^n$, endowed with the standard Gaussian measure $γ_{m,n}$ associated with the Bombieri norm. We study how well the norm of a typical polynomial on the unit ball of $\ell_\infty^n$, namely the cube $[-1,1]^n$, can be recovered from its values at the vertices. For $P\in\mathcal{P}_m(\mathbb{R}^n)$, set \[ M(P)=\max_{x\in[-1,1]^n}|P(x)|, \qquad V(P)=\max_{\varepsilon\in\{-1,1\}^n}|P(\varepsilon)|. \] If $P_n$ is chosen according to $γ_{m,n}$, we prove that the relative loss \[ 1-\frac{V(P_n)}{M(P_n)} \] is of order at most $n^{-1/2}$ in probability. Consequently, for every $0<β<1/2$, \[ γ_{m,n}\left\{ P\in\mathcal{P}_m(\mathbb{R}^n): V(P)\geq (1-n^{-β})M(P) \right\} \longrightarrow1 \] as $n\to\infty$. Thus, with respect to the Bombieri Gaussian measure, the vertices of the cube are asymptotically norming for homogeneous polynomials of fixed degree.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Damián Pinasco, Ignacio Zalduendo. 2026-09-26. Almost norming vertices for homogeneous polynomials on the cube. https://arxiv.org/abs/2609.32526

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Matrix-valued regular functions of a quaternionic variable - a decomposition and some approximation results

A quaternionic matrix-valued regular function is a map $F: Ω\rightarrow M_n(\mathbb{H})$ whose entries are (left) regular functions of a quaternion variable, where $Ω$ is a domain in $\mathbb{H}$. Given any $n \times n$ matrix-valued regular function $F(q)$ over $\mathbb{H}$ having norm at most $1$, we derive a decomposition of $F(q)$ in the form $U \star \begin{bmatrix} ||F(q_0)|| & 0\\0 & G(q)\end{bmatrix} V$ for some constant unitary matrices $U, V$, some vector $q_0$ and an $(n-1) \times (n-1)$ matrix-valued regular function $G(q)$, where $\star$ denotes the star product over $\mathbb{H}$. We use this to deduce that any matrix-valued regular function $F(q)$ having norm at most $1$ can be uniformly approximated by a convex combination of rational unitary functions.

math.FA↗

Classification of bipartite observables I: stable and uniformly stable observables

When two quantum systems are prepared independently and each is driven to an idealized limit, the expectation of a bipartite observable may depend on which system is idealized first. We call an observable stable when it does not. We show that stability is equivalent to two operational properties. First, every idealized preparation of one system can be simulated to arbitrary accuracy, uniformly over all probes, by finite mixtures of actual preparations, provided that the probing system is idealized first. Second, any two idealized preparations have a unique, symmetric independent product. Under a uniform form of stability, we prove, the number of preparations that $n$ adaptive probes can tell apart at a fixed margin is bounded by a polynomial in $n$, and responses can be learned with a bounded number of mistakes; otherwise, at some margin, protocols with $n$ probes tell apart $2^n$ preparations. The swap test, Hong--Ou--Mandel coincidences and discrete equality tests turn out to be uniformly stable, with bounds independent of the dimension, while order comparisons of discrete spectra unbounded above are unstable. The proofs rest on the classical fact that a single double limit condition appears, under different names, in topology (Grothendieck), functional analysis (Krivine--Maurey), algebra (Arens), probability (Simons) and combinatorics (Pták), and in model theory as Shelah's stability, where the independent product corresponds to Harrington's lemma. Model theory thus serves as a Rosetta stone, pairing each physical question with its mathematical formulation.

math.FA↗