Quantum Dynamics

Publications of Nicola Pancotti

Journal Article (7)

Journal Article
Pancotti, N.; Scandi, M.; Mitchison, M. T.; Perarnau-Llobet, M.: Speed-Ups to Isothermality: Enhanced Quantum Thermal Machines through Control of the System-Bath Coupling. Physical Review X 10 (3), 031015 (2020)
Journal Article
Pancotti, N.; Giudice, G.; Cirac, J. I.; Garrahan, J. P.; Bañuls, M. C.: Quantum East Model: Localization, Nonthermal Eigenstates, and Slow Dynamics. Physical Review X 10 (2), 021051 (2020)
Journal Article
Glasser, I.; Pancotti, N.; Cirac, J. I.: From Probabilistic Graphical Models to Generalized Tensor Networks for Supervised Learning. IEEE Access 8, pp. 68169 - 68182 (2020)
Journal Article
Pancotti, N.; Knap, M.; Huse, D. A.; Cirac, J. I.; Bañuls, M. C.: Almost conserved operators in nearly many-body localized systems. Physical Review B 97 (9), 094206 (2018)
Journal Article
Glasser, I.; Pancotti, N.; August, M.; Rodríguez, I. D.; Cirac, J. I.: Neural-Network Quantum States, String-Bond States, and Chiral Topological States. Physical Review X 8 (1), 011006 (2018)
Journal Article
Biamonte, J.; Wittek, P.; Pancotti, N.; Rebentrost, P.; Wiebe, N.; Lloyd, S.: Quantum machine learning. Nature 549 (7671), pp. 195 - 202 (2017)
Journal Article
Banchi, L.; Pancotti, N.; Bose, S.: Quantum gate learning in qubit networks: Toffoli gate without time-dependent control. npj Quantum Information 2, 16019 (2016)

Conference Paper (1)

Conference Paper
Glasser, I.; Sweke, R.; Pancotti, N.; Eisert, J.; Cirac, J. I.: Expressive power of tensor-network factorizations for probabilistic modeling. In: Advances in Neural Information Processing Systems, Vol. 32 (Eds. Wallach, H.; Larochelle, H.; Beygelzimer , A.; d'Alché-Buc , F.; Fox, E.). 33rd Conference on Neural Information Processing Systems (NeurIPS), Vancouver, CANADA, December 08, 2019 - December 14, 2019. Neural Information Processing Systems Foundation, Inc. ( NIPS ) (2019)

Thesis - PhD (1)

Thesis - PhD
Pancotti, N.: Methods for Quantum Dynamics, Localization and Quantum Machine Learning. Dissertation, Technische Universität, München (2020)
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