Quantum
Computing
For a theoretical physicist, quantum computing is going back to the roots of modern physics and season the latter with a contemporary twist. Combining quantum physics with classical machine-learning algorithms to quantum-computing algorithms at gluoNNet has led to the following publications
K. Novotny, C. Tüysüz, C. Rieger, D. Dobos et al. “Hybrid quantum classical graph neural networks for particle track reconstruction“, Quantum Machine Intelligence 3, 29 (2021)
K. Novotny, C. Tüysüz, C. Rieger, D. Dobos et al. “Quantum Track Reconstruction Algorithms for non-HEP applications”, PoS ICHEP2020 (2021) 983 • Contribution to: ICHEP2020, 983
C. Tüysüz, D. Dobos, K. Novotny, K.Potamianos et al. “Particle Track Reconstruction with Quantum Algorithms“, EPJ Web of Conferences 245, 09013 (2020)
C. Tüysüz, D. Dobos, K. Novotny, K.Potamianos et al. “Performance of Particle Tracking Using a Quantum Graph Neural Network”, https://arxiv.org/abs/2012.01379
C. Tüysüz, D. Dobos, K. Novotny, K.Potamianos et al. , “A Quantum Graph Neural Network Approach to Particle Track Reconstruction”, https://arxiv.org/abs/2007.06868
