Improved particle-flow event reconstruction with scalable neural networks for current and future particle detectors
Joosep Pata,
Eric Wulff,
Farouk Mokhtar
et al.
Abstract:Efficient and accurate algorithms are necessary to reconstruct particles in the highly granular detectors anticipated at the High-Luminosity Large Hadron Collider and the Future Circular Collider. We study scalable machine learning models for event reconstruction in electron-positron collisions based on a full detector simulation. Particle-flow reconstruction can be formulated as a supervised learning task using tracks and calorimeter clusters. We compare a graph neural network and kernel-based transformer and… Show more
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