Dirichlet polynomials and entropy

TL;DR

This paper explores the relationship between Dirichlet polynomials, entropy, and a geometric interpretation, establishing a formula connecting entropy with a rectangle-based measure derived from a homomorphism.

Contribution

It introduces a novel homomorphism from Dirichlet polynomials to a rectangle rig, linking entropy to geometric measures and providing a new perspective on entropy calculation.

Findings

The rectangle-area formula $A(d)=L(d)W(d)$ holds for all Dirichlet polynomials.

Entropy of a Dirichlet polynomial can be computed using the homomorphism $h$.

Similar results are established for cross entropy.

Abstract

A Dirichlet polynomial $d$ in one variable ${\mathcal{y}}$ is a function of the form $d({\mathcal{y}})=a_n n^{\mathcal{y}}+\cdots+a_22^{\mathcal{y}}+a_11^{\mathcal{y}}+a_00^{\mathcal{y}}$ for some $n,a_0,\ldots,a_n\in\mathbb{N}$. We will show how to think of a Dirichlet polynomial as a set-theoretic bundle, and thus as an empirical distribution. We can then consider the Shannon entropy $H(d)$ of the corresponding probability distribution, and we define its length (or, classically, its perplexity) by $L(d)=2^{H(d)}$. On the other hand, we will define a rig homomorphism $h\colon\mathsf{Dir}\to\mathsf{Rect}$ from the rig of Dirichlet polynomials to the so-called rectangle rig, whose underlying set is $\mathbb{R}_{\geq0}\times\mathbb{R}_{\geq0}$ and whose additive structure involves the weighted geometric mean; we write $h(d)=(A(d),W(d))$, and call the two components area and width (respectively). The main result of this paper is the following: the rectangle-area formula $A(d)=L(d)W(d)$ holds for any Dirichlet polynomial $d$. In other words, the entropy of an empirical distribution can be calculated entirely in terms of the homomorphism $h$ applied to its corresponding Dirichlet polynomial. We also show that similar results hold for the cross entropy.