A Quantum Graph Neural Network Approach to Particle Track Reconstruction

  title={A Quantum Graph Neural Network Approach to Particle Track Reconstruction},
  author={Cenk Tuysuz and Federico Carminati and Bilge Demirkoz and Daniel Dobos and Fabio Fracas and Kristiane Novotny and Karolos Potamianos and Sofia Vallecorsa and J. R. Vlimant},
  journal={arXiv: Quantum Physics},
Unprecedented increase of complexity and scale of data is expected in computation necessary for the tracking detectors of the High Luminosity Large Hadron Collider (HL-LHC) experiments. While currently used Kalman filter based algorithms are reaching their limits in terms of ambiguities from increasing number of simultaneous collisions, occupancy, and scalability (worse than quadratic), a variety of machine learning approaches to particle track reconstruction are explored. It has been… Expand

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