  This paper describes an angular adaptivity algorithm for Boltzmann transport
applications which for the first time shows evidence of $\mathcal{O}(n)$
scaling in both runtime and memory usage, where $n$ is the number of adapted
angles. This adaptivity uses Haar wavelets, which perform structured
$h$-adaptivity built on top of a hierarchical P$_0$ FEM discretisation of a 2D
angular domain, allowing different anisotropic angular resolution to be applied
across space/energy. Fixed angular refinement, along with regular and
goal-based error metrics are shown in three example problems taken from
neutronics/radiative transfer applications. We use a spatial discretisation
designed to use less memory than competing alternatives in general applications
and gives us the flexibility to use a matrix-free multgrid method as our
iterative method. This relies on scalable matrix-vector products using Fast
Wavelet Transforms and allows the use of traditional sweep algorithms if
desired.
