  In this paper we explore the potential improvements in neutrino event
reconstruction that a 3D pixelated readout could offer over a 2D projective
wire readout for liquid argon time projection chambers. We simulate and study
events in two generic, idealized detector configurations for these two designs,
classifying events in each sample with deep convolutional neural networks to
compare the best 2D results to the best 3D results. In almost all cases we find
that the 3D readout provides better reconstruction efficiency and purity than
the 2D projective wire readout, with the advantages of 3D being particularly
evident in more complex topologies, such as electron neutrino charged current
events. We conclude that the use of a 3D pixelated detector could significantly
enhance the reach and impact of future liquid argon TPC experiments physics
program, such as DUNE.
