  We introduce the concept of a hyperuniformity disorder length that controls
the variance of volume fraction fluctuations for randomly placed windows of
fixed size. In particular, fluctuations are determined by the average number of
particles within a distance $h$ from the boundary of the window. We first
compute special expectations and bounds in $d$ dimensions, and then illustrate
the range of behavior of $h$ versus window size $L$ by analyzing three
different types of simulated two-dimensional pixel pattern - where particle
positions are stored as a binary digital image in which pixels have value
zero/one if empty/contain a particle. The first are random binomial patterns,
where pixels are randomly flipped from zero to one with probability equal to
area fraction. These have long-ranged density fluctuations, and simulations
confirm the exact result $h=L/2$. Next we consider vacancy patterns, where a
fraction $f$ of particles on a lattice are randomly removed. These also display
long-range density fluctuations, but with $h=(L/2)(f/d)$ for small $f$. For a
hyperuniform system with no long-range density fluctuations, we consider
Einstein patterns where each particle is independently displaced from a lattice
site by a Gaussian-distributed amount. For these, at large $L$, $h$ approaches
a constant equal to about half the root-mean-square displacement in each
dimension. Then we turn to grayscale pixel patterns that represent simulated
arrangements of polydisperse particles, where the volume of a particle is
encoded in the value of its central pixel. And we discuss the continuum limit
of point patterns, where pixel size vanishes. In general, we thus propose to
quantify particle configurations not just by the scaling of the density
fluctuation spectrum but rather by the real-space spectrum of $h(L)$ versus
$L$. We call this approach Hyperuniformity Disorder Length Spectroscopy.
