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Higher traces of linear maps on finite-dimensional normed spaces

Tomasz Kania

TL;DR

The paper studies how higher traces $\lambda_k(A)=\operatorname{tr}(\Lambda^kA)$ can be realized as averages of matrix coefficients over unit spheres in the exterior power space. It introduces an isotropy condition $T_\eta=I_V$ (with $T_\eta=n_k\int_{S_V} w\otimes w^*\,d\eta(w)$) that exactly characterizes when the trace-average formula holds for all linear maps $A$, and identifies two robust isotropy mechanisms: cone measures (always isotropic) and hypersurface measures under finite-group orthogonal $2$-design symmetry. The work also provides explicit counterexamples illustrating limitations of the hypersurface measure, develops a quantitative anisotropy tensor $\mathcal{A}_X$ linking trace deviations to geometric anisotropy, and analyzes $\alpha$-cone measures, showing isotropy at $\alpha=1$ for convex bodies and a first-order obstruction for $\alpha\neq1$ tied to degree-2 spherical harmonics. Overall, it unifies and extends classical trace-average results to arbitrary norms and exterior powers, with clear geometric and group-theoretic criteria for when the averages reproduce the exact traces.

Abstract

We prove a unified trace-average formula for the $k$-th higher trace $λ_k(A)=\operatorname{tr}(Λ^k A)$ of a linear operator $A$ on a finite-dimensional normed space. The formula averages the matrix coefficient $w\mapsto\langle(Λ^kA)w, w^*\rangle$ over the unit sphere of $Λ^kX$ against a probability measure $η$; it holds for \emph{all} $A$ if and only if the operator-valued average $T_η=\binom{N}{k}\int w\otimes w^*\operatorname{d}η$ equals the identity. Two natural choices of $η$ satisfy this isotropy: (i) the hypersurface measure when a finite isometry group acts as an orthogonal $2$-design on $Λ^k\mathbb{R}^N$; and (ii) the cone probability measure (no symmetry needed). We also identify a first-order obstruction for hypersurface averages at $k=1$: only degree-$2$ spherical harmonics of the support function contribute.

Higher traces of linear maps on finite-dimensional normed spaces

TL;DR

The paper studies how higher traces can be realized as averages of matrix coefficients over unit spheres in the exterior power space. It introduces an isotropy condition (with ) that exactly characterizes when the trace-average formula holds for all linear maps , and identifies two robust isotropy mechanisms: cone measures (always isotropic) and hypersurface measures under finite-group orthogonal -design symmetry. The work also provides explicit counterexamples illustrating limitations of the hypersurface measure, develops a quantitative anisotropy tensor linking trace deviations to geometric anisotropy, and analyzes -cone measures, showing isotropy at for convex bodies and a first-order obstruction for tied to degree-2 spherical harmonics. Overall, it unifies and extends classical trace-average results to arbitrary norms and exterior powers, with clear geometric and group-theoretic criteria for when the averages reproduce the exact traces.

Abstract

We prove a unified trace-average formula for the -th higher trace of a linear operator on a finite-dimensional normed space. The formula averages the matrix coefficient over the unit sphere of against a probability measure ; it holds for \emph{all} if and only if the operator-valued average equals the identity. Two natural choices of satisfy this isotropy: (i) the hypersurface measure when a finite isometry group acts as an orthogonal -design on ; and (ii) the cone probability measure (no symmetry needed). We also identify a first-order obstruction for hypersurface averages at : only degree- spherical harmonics of the support function contribute.
Paper Structure (6 sections, 10 theorems, 57 equations)

This paper contains 6 sections, 10 theorems, 57 equations.

Key Result

Lemma 2.3

Let $X$ be a finite-dimensional normed space and equip $\Lambda^k X$ with the exterior projective norm.

Theorems & Definitions (22)

  • Example 2.1: Hyperoctahedral group
  • Example 2.2: Low-dimensional geometric groups
  • Lemma 2.3
  • proof
  • Lemma 2.4: Gauss--Green Theorem
  • Proposition 2.5
  • proof
  • Lemma 3.1: Hilbert--Schmidt duality
  • proof
  • Theorem 3.2
  • ...and 12 more