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.
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BibTeX
@misc{burgman2026vertex,
title = {{Vertex reconstruction for a search for neutron-antineutron conversions with HIBEAM}},
author = {Alexander Burgman and Sze Chun Yiu and Yamna Shaikh and David Milstead and Eily Merjy and Lucas Åstrand and Kenneth Österberg and Fredrik Oljemark and Bernhard Meirose and Matthias Holl and Valentina Santoro and Jorge Amaral and Ernesto Kemp and André Nepomuceno and Tiago Quirino and Joshua L. Barrow},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2608.28314},
eprint = {2608.28314},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2608.28314},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Vertex reconstruction for a search for neutron-antineutron conversions with HIBEAM
AU - Alexander Burgman
AU - Sze Chun Yiu
AU - Yamna Shaikh
AU - David Milstead
AU - Eily Merjy
AU - Lucas Åstrand
AU - Kenneth Österberg
AU - Fredrik Oljemark
AU - Bernhard Meirose
AU - Matthias Holl
AU - Valentina Santoro
AU - Jorge Amaral
AU - Ernesto Kemp
AU - André Nepomuceno
AU - Tiago Quirino
AU - Joshua L. Barrow
PY - 2026
DA - 2026/09/21
PB - arXiv
DO - 10.48550/arxiv.2608.28314
UR - https://arxiv.org/abs/2608.28314
AB - 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.
ER -