Reconstruction of boosted and resolved multi-Higgs-boson events with symmetry-preserving attention networks
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Abstract (arXiv)
The production of multiple Higgs bosons at the CERN LHC provides a direct way to measure the trilinear and quartic Higgs self-interaction strengths as well as potential access to beyond the standard model effects that can enhance production at large transverse momentum pT. The largest event fraction arises from the fully hadronic final state in which every Higgs boson decays to a bottom quark-antiquark pair (bbarb). This introduces a combinatorial challenge known as the jet assignment problem: assigning jets to sets representing Higgs boson candidates. Symmetry-preserving attention networks (SPA-Nets) have been been developed to address this challenge. However, the complexity of jet assignment increases when simultaneously considering both Hrightarrow bbarb reconstruction possibilities, i.e., two "resolved" small-radius jets each containing a shower initiated by a b-quark or one "boosted" large-radius jet containing a merged shower initiated by a bbarb pair. The latter improves the reconstruction efficiency at high pT. In this work, we introduce a generalization to the SPA-Net approach to simultaneously consider both boosted and resolved reconstruction possibilities and unambiguously interpret an event as "fully resolved'', "fully boosted", or in between. We report the performance of baseline methods, the original SPA-Net approach, and our generalized version on nonresonant HH and HHH production at the LHC. Considering both boosted and resolved topologies, our SPA-Net approach increases the Higgs boson reconstruction purity by 57--62% and the efficiency by 23--38% compared to the baseline method depending on the final state.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 6 of its 45 references that are in the map. First posted on arXiv 5 Dec 2024.
Builds on
6 of 45 references.
References · 6
- 2017Attention Is All You Needcited by 60,361
- 2022Particle Transformer for Jet Taggingcited by 98
- 2019ParticleNet: Jet Tagging via Particle Cloudscited by 64
- 2020Permutationless Many-Jet Event Reconstruction with Symmetry Preserving Attention Networkscited by 22
- 2021SPANet: Generalized Permutationless Set Assignment for Particle Physics using Symmetry Preserving Attentioncited by 18
- 2023Reconstruction of Unstable Heavy Particles Using Deep Symmetry-Preserving Attention Networkscited by 7
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Citing papers per year: 2026: 1.
1 paper.
- 2026Pairton: Iterative Reconstruction of Short-Lived Particles14 Aug 2026