Detector-aware merged targets for calorimeter showers improve GNN particle flow reconstruction performance and robustness to topology changes on independent samples.
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2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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Geant4-based study shows shower observables and a ParticleNet GNN improve hadronic energy reconstruction in the longitudinally segmented CRILIN Cherenkov calorimeter, yielding an effective contribution of roughly 1 GeV/E ⊕ 12%/√E ⊕ 2.5% when combined with a realistic HCAL.
citing papers explorer
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Detector-aware target definitions for full-event particle reconstruction
Detector-aware merged targets for calorimeter showers improve GNN particle flow reconstruction performance and robustness to topology changes on independent samples.
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Software compensation of hadronic showers in the longitudinally segmented CRILIN Cherenkov crystal calorimeter
Geant4-based study shows shower observables and a ParticleNet GNN improve hadronic energy reconstruction in the longitudinally segmented CRILIN Cherenkov calorimeter, yielding an effective contribution of roughly 1 GeV/E ⊕ 12%/√E ⊕ 2.5% when combined with a realistic HCAL.