Vertex reconstruction for a search for neutron-antineutron conversions with HIBEAM

Abstract

The HIBEAM/NNBAR programme (incorporated into the FINESSE/NNBAR programme) at the European Spallation Source is proposed to search for neutrons converting to antineutrons. An important observable is the reconstructed vertex arising from charged particles produced by an antineutron annihilating on a thin target foil and which pass through a time projection chamber. This paper studies track clustering and foil-plane vertex reconstruction for this topology. Both non-machine-learning methods and graph-neural-network methods are tested and compared with each other, including deterministic clustering, trackless projection and a hybrid clustering/graph-neural-network chain with track classification and vertex refinement. We conclude that, for the geometrically simple events in the HIBEAM TPC, classical reconstruction methods perform on-par with machine-learning based methods in terms of vertex coordinate reconstruction. Custom machine-learning based methods can, however, deliver event-shape information that may be important in downstream analyses.