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In this paper we explore the potential improvements in neutrino eventreconstruction that a 3D pixelated readout could offer over a 2D projectivewire readout for liquid argon time projection chambers. We simulate and studyevents in two generic, idealized detector configurations for these two designs,classifying events in each sample with deep convolutional neural networks tocompare the best 2D results to the best 3D results. In almost all cases we findthat the 3D readout provides better reconstruction efficiency and purity thanthe 2D projective wire readout, with the advantages of 3D being particularlyevident in more complex topologies, such as electron neutrino charged currentevents. We conclude that the use of a 3D pixelated detector could significantlyenhance the reach and impact of future liquid argon TPC experiments physicsprogram, such as DUNE.

Enhancing Neutrino Event Reconstruction with Pixel-Based 3D Readout for Liquid Argon Time Projection Chambers