Weyl's Criterion for Equidistribution

1. Definition and Statement

Definition of Equidistribution Suppose that \(\{x_n\}_{n=1}^\infty\) is a sequence of real numbers in \([0,1]\). We say that the sequence is equidistributed when for any real numbers \(a < b\) in \([0,1]\),
\[{}\lim_{N \rightarrow \infty} \frac{\# \{n \ : \ 1 \leq n \leq N \text{ and } x_n \in [a,b]\}}{N}{}\]
\[{}= b-a.{}\]
Meta (Intuition for Equidistribution)
The idea is that in the long run, the number of terms of the sequence which belong to \([a,b]\) is exactly proportional to the length of the interval \([a,b]\). One can think of this as saying that the sequence tends to spend equal portions of the time belonging to intervals of equal size.

Example of Equidistribution The sequence
\[{}0, 0, 1,{}\]
\[{}0, \frac{1}{2}, 1,{}\]
\[{}0, \frac{1}{3}, \frac{2}{3}, 1,{}\]
\[{}0, \frac{1}{4}, \frac{2}{4}, \frac{3}{4}, 1, \ldots{}\]
is equidistributed in \([0,1]\). The idea of proof is that the number of integers \(k\) for which \(k/m\) belongs to \([a,b]\) is always \(m(b-a)\) to within an error of at most \(\pm 1\). The quantity \(\# \{n \ : \ 1 \leq n \leq N \text{ and } x_n \in [a,b]\}\) can be successfully estimated by looking first at those \(N\) which correspond to a full number of “sweeps” across \([0,1]\) (i.e., \(N = (m+1)(m+2)/2\) for some positive integer \(m\)) and comparing all other \(N\) to the nearest \(N\) of this special sort. For this special \(N\),
\[{}\# \{n \ : \ 1 \leq n \leq N \text{ and } x_n \in [a,b]\}{}\]
\[{} = (0 + \cdots + m)(b-a){}\]
\[{} = N(b-a) - m(b-a){}\]
up to an error of at most \(m+1\) points. The calculation works out because \(m/N\) tends to \(0\) as \(m \rightarrow \infty\).
Proving that a sequence is equidistributed is no small task. The first key observation is to note that saying that a sequence \(\{x_n\}_{n=1}^\infty \subset [0,1]\) is equidistributed is in fact equivalent to the assertion that the formula
\[ \lim_{N \rightarrow \infty} \frac{1}{N} \sum_{n=1}^n f(x_n) = \int_0^1 f(t) dt \tag{1}\]
holds for all \(f\) of the form \(f = \chi_{[a,b]}\) (i.e., the indicator function of \([a,b]\)) for \([a,b] \subset [0,1]\). This is because we may write
\[{}\# \left\{n \ : \ 1 \leq n \leq N \text{ and } x_n \in [a,b] \right\}{}\]
\[{}= \sum_{n=1}^N \chi_{[a,b]}(x_n){}\]
(and because \(b-a = \int_0^1 \chi_{[a,b]}(t) dt\)). It's also important to observe that for any fixed sequence \(\{x_n\}_{n=1}^\infty\), the class of Riemann-integrable functions satisfying (1) is a vector space (because both sides are linear in \(f\)).
Theorem (Weyl's Criterion)
The sequence \(\{x_n\}_{n=1}^\infty\) is equidistributed in \([0,1]\) if and only if for all integers \(\ell \neq 0\),
\[ \lim_{N \rightarrow \infty} \frac{1}{N} \sum_{n=1}^N e^{2 \pi i \ell x_n} = 0. \]
Proof
Meta (Main Ideas, Part 1)
It's easier to start by showing that \(\{x_n\}_{n=1}^\infty\) is equidistributed if and only if (1) holds for all continuous 1-periodic functions \(f\).

The key observation is a sort of Squeeze Theorem: Suppose \(\{g_j\}_{j=1}^\infty\) and \(\{h_j\}\) are sequences of Riemann-integrable functions on \([0,1]\) satisfying (1) for each \(j\) and having \(\int_0^1 (h_j(t)-g_j(t)) dt \rightarrow 0\) as \(j \rightarrow \infty\). If \(f\) is any function such that \(g_j(x) \leq f(x) \leq h_j(x)\) for each \(j\) and all \(x \in [0,1]\), then \(f\) is Riemann integrable and satisfies (1) as well. To see this, fix any single value of \(j\) large enough so that \(\int_0^1 (h_j(t)-g_j(t)) dt < \frac{\epsilon}{2}\) and then consider all \(N\) large enough that
\[ \left| \frac{1}{N} \sum_{n=1}^N g_j(x_n) - \int_0^1 g_j(t) dt \right| < \frac{\epsilon}{2}\]
and likewise for \(h_j\). Then for all such \(N\),
\[{}- \epsilon + \int_0^1 f(t) dt{}\]
\[{}\leq - \epsilon + \int_0^1 h_j(t) dt{}\]
\[{}< - \frac{\epsilon}{2} + \int_0^1 g_j(t) dt{}\]
\[{}< \frac{1}{N} \sum_{n=1}^N g_j(x_n) {}\]
\[{}\leq \frac{1}{N} \sum_{n=1}^N f(x_n){}\]
and
\[{}\frac{1}{N} \sum_{n=1}^N f(x_n){}\]
\[{}\leq \frac{1}{N} \sum_{n=1}^N h_j(x_n){}\]
\[{}< \frac{\epsilon}{2} + \int_0^1 h_j(t) dt{}\]
\[{}< \epsilon + \int_0^1 g_j(t) dt{}\]
\[{}\leq \epsilon + \int_0^1 f(t) dt.{}\]
Another key observation is that \(\chi_{(a,b)}\) must satisfy (1) when \(0 < a < b < 1\), simply because
\[{}\frac{\# \left\{n \ : \ 1 \leq n \leq N \text{ and } x \in (a,b) \right\}}{N}{}\]
\[{}= 1 - \frac{\# \left\{n \ : \ 1 \leq n \leq N \text{ and } x \in [0,a] \right\}}{N}{}\]
\[{}- \frac{\# \left\{n \ : \ 1 \leq n \leq N \text{ and } x \in [b,1] \right\}}{N}{}\]
and the right-hand side tends to \(1 - a - (1-b)) = b-a\) as \(N \rightarrow \infty\).

Using these facts, we show that for any given sequence \(\{x_n\}_{n=1}^\infty\), the class of functions satisfying (1) contains all indicators of the closed intervals \([a,b] \subset [0,1]\) if and only if it contains all continuous, 1-periodic functions \(f\). By linearity, we may assume that \(f\) is real.

Knowing that indicator functions satisfy (1), let \(\mathcal{P}\) be any partition of \([0,1]\) with an odd number of intervals. We can define \(g_{\mathcal{P}}\) and \(h_{\mathcal P}\) as follows: arrange the intervals \(I_1,I_2,\ldots\) of \(\mathcal{P}\) in order from smallest to largest. Modify the intervals so that \(I_1,I_3,\ldots\) are closed and \(I_2,I_4,\ldots\) are open; now every point of \([0,1]\) belongs to exactly one such interval. We can define
\[ g_{\mathcal P}(x) = \sum_{j} \left[ \inf_{u \in I_j} f(u) \right] \chi_{I_j}(x) \]
and
\[ h_{\mathcal P}(x) = \sum_{j} \left[ \sup_{u \in I_j} f(u) \right] \chi_{I_j}(x). \]
Both \(f\) and \(g\) are finite linear combinations of functions known to satisfy (1). Because \(f\) is continuous on \([0,1]\), it is uniformly continuous and the functions \(g_{\mathcal P}\) and \(h_{\mathcal P}\) will converge uniformly to \(f\) along any sequence of partitions such that the norm of the partitions tends to zero (i.e., the length of the longest interval).
Figure. Approximating Continuous Functions By Step Functions

In the reverse direction, we approximate the indicator function \(\chi_{[a,b]}\) above and below by piecewise linear functions whose integrals are very close to one another. An example is illustrated below assuming that one takes a limit along some sequence of values of \(h\) decreasing to zero.
Figure. Approximating Indicator Functions By Continuous Functions
Meta (Main Ideas, Part 2)

To show sufficiency of the Weyl criterion, we use the fact that continuous functions can be approximated uniformly by trigonometric polynomials. More precisely, if a sequence is known to be equidistributed, then the Weyl criterion holds simply because \(e^{2 \pi i \ell x}\) is itself a continuous 1-periodic function and its integral on \([0,1]\) happens to be \(0\) when \(\ell \in {\mathbb Z} \setminus \{0\}\).

In the converse direction, if it is known that (1) holds for complex exponentials \(e^{2 \pi i \ell x}\) with \(\ell \in {\mathbb Z} \setminus \{0\}\), then it must hold for all \(\ell \in {\mathbb Z}\) (simply because (1) is true for \(f \equiv 1\) regardless of the sequence). Thus all trigonometric polynomials (i.e., finite linear combinations of complex exponentials) satisfy (1). But all continuous 1-periodic functions are uniformly approximable by trigonometric polynomials, so we can apply the Squeeze Theorem result from above (bounding any real \(f\) between \(q(x) - \epsilon\) and \(q(x) + \epsilon\) for a trigonometric polynomial \(q\) which is uniformly \(\epsilon\)-close to \(f\)) to achieve the desired conclusion.
Corollary
Let \(\alpha\) be any real number and let \(x_n\) be the fractional part of \(n \alpha\) for each \(n\). This sequence is equidistributed if and only if \(\alpha\) is irrational.
Proof
The fractional part \(\left<x\right>\) of a real number \(x\) is simply \(x\) minus the largest integer not exceeding \(x\), i.e., \(x - \lfloor x \rfloor\). Because \(e^{2 \pi i \ell x}\) is 1-periodic and because \(\lfloor x \rfloor \in {\mathbb Z}\), it must always be the case that \(e^{2 \pi i \ell \left<x\right>} = e^{2 \pi i \ell x}\) for all real \(x\). This means that
\[ \sum_{n=1}^N e^{2 \pi i \ell \left<n \alpha\right>} = \sum_{n=1}^N e^{2 \pi i n \ell \alpha}. \]
The right-hand side is a finite geometric series whose sum we can compute explicitly:
\[{}\frac{1}{N} \sum_{n=1}^N e^{2 \pi i \ell \left<n \alpha\right>}{}\]
\[{}= \frac{e^{2 \pi i \ell \alpha}}{N} \frac{e^{2 \pi i N \ell \alpha}-1}{e^{2 \pi i \ell \alpha - 1}}{}\]
provided that \(e^{2 \pi i \ell \alpha}\) is not equal to one (which could only happen if \(\ell \alpha\) is an integer, meaning that it only occurs when \(\ell = 0\) or when \(\alpha\) is rational). We see that the numerator remains bounded as a function of \(N\), so the expression tends to zero as \(N \rightarrow \infty\).