# Poissonian Pair Correlation in Higher Dimensions

## TL;DR

This paper extends the concept of Poissonian pair correlation to higher-dimensional tori using Euclidean norms, proving that such sequences are uniformly distributed and linking pair correlation to exponential sum estimates similar to Weyl's criterion.

## Contribution

It establishes that Poissonian pair correlation in higher dimensions with Euclidean norm implies uniform distribution, extending previous results from the infinity norm case.

## Key findings

- Sequences with Euclidean Poissonian pair correlation are uniformly distributed.
- The paper connects pair correlation to exponential sum estimates akin to Weyl's criterion.
- Extension of pair correlation results to higher dimensions using Euclidean norms.

## Abstract

Let $(x_n)_{n=1}^{\infty}$ be a sequence on the torus $\mathbb{T}$ (normalized to length 1). A sequence $(x_n)$ is said to have Poissonian pair correlation if, for all $s>0$, $$ \lim_{N \rightarrow \infty}{ \frac{1}{N} \# \left\{ 1 \leq m \neq n \leq N: |x_m - x_n| \leq \frac{s}{N} \right\}} = 2s.$$ It is known that this implies uniform distribution of the sequence $(x_n)$. Hinrichs, Kaltenb\"ock, Larcher, Stockinger \& Ullrich extended this result to higher dimensions and showed that sequences $(x_n)$ in $[0,1]^d$ that satisfy, for all $s>0$, $$ \lim_{N \rightarrow \infty}{ \frac{1}{N} \# \left\{ 1 \leq m \neq n \leq N: \|x_m - x_n\|_{\infty} \leq \frac{s}{N} \right\}} = (2s)^d.$$ are also uniformly distributed. We prove the same result for the extension by the Euclidean norm: if a sequence $(x_n)$ in $\mathbb{T}^d$ satisfies, for all $s > 0$, $$ \lim_{N \rightarrow \infty}{ \frac{1}{N} \# \left\{ 1 \leq m \neq n \leq N: \|x_m - x_n\|_{2} \leq \frac{s}{N} \right\}} = \omega_d s^d$$ where $\omega_d$ is the volume of the unit ball, then $(x_n)$ is uniformly distributed. Our approach shows that Poissonian Pair Correlation implies an exponential sum estimate that resembles and implies the Weyl criterion.