Giacomo Torlai

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Roger G. MelkoFaculty, University of Waterloo & Perimeter Institute; Affiliate, Vector InstituteAdresse e-mail validée de uwaterloo.ca
Juan Felipe Carrasquilla ÁlvarezETH ZürichAdresse e-mail validée de ethz.ch
Giuseppe CarleoAssociate Professor of Physics - EPFL, Lausanne, SwitzerlandAdresse e-mail validée de epfl.ch
Guglielmo MazzolaUniversity of ZurichAdresse e-mail validée de uzh.ch
Matthias TroyerMicrosoft QuantumAdresse e-mail validée de microsoft.com
Leandro AolitaQuantum Research Centre - Technology Innovation InstituteAdresse e-mail validée de tii.ae
Evert van NieuwenburgLeiden UniversityAdresse e-mail validée de lorentz.leidenuniv.nl
Manuel EndresCaltechAdresse e-mail validée de caltech.edu
Gabriele De ChiaraProfessor of Quantum Information, Universitat Autònoma de BarcelonaAdresse e-mail validée de qub.ac.uk
Antonio MezzacapoIBM QuantumAdresse e-mail validée de us.ibm.com
Alexander KeeslingCEO, QuEra Computing IncAdresse e-mail validée de quera.com
Harry LevineQuantum Research Scientist, AWS Center for Quantum ComputingAdresse e-mail validée de amazon.com
Richard KuengJohannes Kepler University Linz, AustriaAdresse e-mail validée de jku.at
Hsin-Yuan Huang (Robert)California Institute of Technology, Google Quantum AIAdresse e-mail validée de caltech.edu
Victor V. AlbertQuICS @ NIST & University of MarylandAdresse e-mail validée de umd.edu
John PreskillRichard P. Feynman Professor of Theoretical Physics, California Institute of TechnologyAdresse e-mail validée de caltech.edu
Bohdan KulchytskyyLead Scientist at 1QB Information Technologies, Inc.Adresse e-mail validée de uwaterloo.ca
Markus GreinerProfessor of Physics, Harvard UniversityAdresse e-mail validée de physics.harvard.edu
Hannes BernienProfessor of Physics, University of Innsbruck & IQOQI, University of ChicagoAdresse e-mail validée de uibk.ac.at
Ahmed OmranSoftware Engineer, GoogleAdresse e-mail validée de google.com

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Giacomo Torlai

AWS Center for Quantum Computing

Adresse e-mail validée de amazon.com

Quantum Hardware Tensor Networks Machine Learning


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Neural-network quantum state tomography G Torlai, G Mazzola, J Carrasquilla, M Troyer, R Melko, G Carleo Nature Physics 14 (5), 447, 2018	1002	2018
Reconstructing quantum states with generative models J Carrasquilla, G Torlai, RG Melko, L Aolita Nature Machine Intelligence 1 (3), 155-161, 2019	365	2019
Learning thermodynamics with Boltzmann machines G Torlai, RG Melko Physical Review B 94 (16), 165134, 2016	313	2016
Provably efficient machine learning for quantum many-body problems HY Huang, R Kueng, G Torlai, VV Albert, J Preskill Science 377 (6613), eabk3333, 2022	283	2022
Neural decoder for topological codes G Torlai, RG Melko Physical review letters 119 (3), 030501, 2017	233	2017
Latent space purification via neural density operators G Torlai, RG Melko Physical review letters 120 (24), 240503, 2018	162	2018
NetKet: A machine learning toolkit for many-body quantum systems G Carleo, K Choo, D Hofmann, JET Smith, T Westerhout, F Alet, EJ Davis, ... SoftwareX 10, 100311, 2019	148	2019
Integrating neural networks with a quantum simulator for state reconstruction G Torlai, B Timar, EPL Van Nieuwenburg, H Levine, A Omran, A Keesling, ... Physical review letters 123 (23), 230504, 2019	144	2019
Machine-Learning Quantum States in the NISQ Era G Torlai, RG Melko Annual Review of Condensed Matter Physics 11, 325-344, 2020	112	2020
Quantum process tomography with unsupervised learning and tensor networks G Torlai, CJ Wood, A Acharya, G Carleo, J Carrasquilla, L Aolita Nature Communications 14 (1), 2858, 2023	109	2023
Precise measurement of quantum observables with neural-network estimators G Torlai, G Mazzola, G Carleo, A Mezzacapo Physical Review Research 2 (2), 022060, 2020	89	2020
How to use neural networks to investigate quantum many-body physics J Carrasquilla, G Torlai PRX Quantum 2 (4), 040201, 2021	78*	2021
Dynamics of the entanglement spectrum in spin chains G Torlai, L Tagliacozzo, G De Chiara Journal of Statistical Mechanics: Theory and Experiment 2014 (06), P06001, 2014	60	2014
Learnability scaling of quantum states: Restricted Boltzmann machines D Sehayek, A Golubeva, MS Albergo, B Kulchytskyy, G Torlai, RG Melko Physical Review B 100 (19), 195125, 2019	51	2019
Wave-function positivization via automatic differentiation G Torlai, J Carrasquilla, MT Fishman, RG Melko, MPA Fisher Physical Review Research 2 (3), 032060, 2020	45	2020
QuCumber: wavefunction reconstruction with neural networks MJS Beach, IJS De Vlugt, A Golubeva, P Huembeli, B Kulchytskyy, X Luo, ... SciPost Physics 7 (1), 009, 2019	42	2019
Demonstrating a long-coherence dual-rail erasure qubit using tunable transmons H Levine, A Haim, JSC Hung, N Alidoust, M Kalaee, L DeLorenzo, ... Physical Review X 14 (1), 011051, 2024	39	2024
Simulating a measurement-induced phase transition for trapped-ion circuits S Czischek, G Torlai, S Ray, R Islam, RG Melko Physical Review A 104 (6), 062405, 2021	33	2021
Violation of Bell's inequalities with preamplified homodyne detection G Torlai, G McKeown, P Marek, R Filip, H Jeong, M Paternostro, ... Physical Review A—Atomic, Molecular, and Optical Physics 87 (5), 052112, 2013	13	2013
Hardware-efficient quantum error correction using concatenated bosonic qubits H Putterman, K Noh, CT Hann, GS MacCabe, S Aghaeimeibodi, RN Patel, ... arXiv preprint arXiv:2409.13025, 2024	11	2024

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