Ising noise filter: physics-informed filtering for particle detectors
- 1Institute for Nuclear Research of the Russian Academy of Sciences
- 2Moscow Institute of Physics and Technology
Abstract
We present the Ising noise filter, a highly portable, graph-based filtering algorithm for early-stage background suppression in particle accelerators and astrophysical detectors. Standard noise rejection methods relying on track fitting suffer from severe combinatorial explosion. Our method bypasses this by mapping individual detector hits to a network of binary spins and minimizing an energy functional. The entire algorithm reduces to vectorized array operations, making it fast and easy to deploy. The interaction kernels are physics-informed, tailored to the underlying physics and geometry of the experiment. We demonstrate the efficacy of this approach in two distinct experimental regimes. Applied to the Baikal-GVD neutrino telescope the filter yields fast, standard-quality noise rejection with 97% recall for astrophysical neutrinos. For the SPD detector at the NICA collider the filter attains 96.7% precision and 97.4% recall on a toy Monte Carlo sample. Furthermore, when combined with a Peterson–Hopfield network for track finding, our physics-informed coupling improves the TrackML score from 0.5 to 0.91.
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BibTeX
@article{kharuk2026ising,
title = {{Ising noise filter: physics-informed filtering for particle detectors}},
author = {I. Kharuk},
journal = {The European Physical Journal C},
year = {2026},
month = oct,
doi = {10.1140/epjc/s10052-026-16383-8},
url = {https://link.springer.com/article/10.1140/epjc/s10052-026-16383-8},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Ising noise filter: physics-informed filtering for particle detectors
AU - I. Kharuk
PY - 2026
DA - 2026/10/16
JO - The European Physical Journal C
DO - 10.1140/epjc/s10052-026-16383-8
UR - https://link.springer.com/article/10.1140/epjc/s10052-026-16383-8
AB - We present the Ising noise filter, a highly portable, graph-based filtering algorithm for early-stage background suppression in particle accelerators and astrophysical detectors. Standard noise rejection methods relying on track fitting suffer from severe combinatorial explosion. Our method bypasses this by mapping individual detector hits to a network of binary spins and minimizing an energy functional. The entire algorithm reduces to vectorized array operations, making it fast and easy to deploy. The interaction kernels are physics-informed, tailored to the underlying physics and geometry of the experiment. We demonstrate the efficacy of this approach in two distinct experimental regimes. Applied to the Baikal-GVD neutrino telescope the filter yields fast, standard-quality noise rejection with 97% recall for astrophysical neutrinos. For the SPD detector at the NICA collider the filter attains 96.7% precision and 97.4% recall on a toy Monte Carlo sample. Furthermore, when combined with a Peterson–Hopfield network for track finding, our physics-informed coupling improves the TrackML score from 0.5 to 0.91.
SN - 1434-6044
SN - 1434-6052
ER -