Giacomo Torlai

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Roger G. MelkoFaculty, University of Waterloo & Perimeter Institute; Affiliate, Vector InstituteVerified email at uwaterloo.ca
Juan Felipe Carrasquilla ÁlvarezVector Institute for Artificial Intelligence. Canada CIFAR AI chairVerified email at vectorinstitute.ai
Giuseppe CarleoAssistant Professor of Computational Quantum Science - EPFL, Lausanne, SwitzerlandVerified email at epfl.ch
Guglielmo MazzolaUniversity of ZurichVerified email at uzh.ch
Matthias TroyerMicrosoft QuantumVerified email at microsoft.com
Leandro AolitaQuantum Research Centre - Technology Innovation InstituteVerified email at tii.ae
Evert van NieuwenburgNiels Bohr Institute and QDevVerified email at nbi.ku.dk
Gabriele De ChiaraReader in Quantum Information, Queen's University BelfastVerified email at qub.ac.uk
Antonio MezzacapoIBM Quantum - Watson Research CenterVerified email at us.ibm.com
Manuel EndresCaltechVerified email at caltech.edu
Bohdan KulchytskyySenior Scientist at 1QBitVerified email at uwaterloo.ca
Markus GreinerProfessor of Physics, Harvard UniversityVerified email at physics.harvard.edu
Hannes BernienAssistant Professor, University of ChicagoVerified email at uchicago.edu
Alexander KeeslingCEO, QuEra Computing IncVerified email at quera.com
Ahmed OmranSoftware Engineer, GoogleVerified email at google.com
Harry LevineQuantum Research Scientist, AWS Center for Quantum ComputingVerified email at amazon.com
Richard KuengJohannes Kepler University Linz, AustriaVerified email at jku.at
Hsin-Yuan Huang (Robert)California Institute of TechnologyVerified email at caltech.edu
Victor V. AlbertQuICS @ NIST & University of MarylandVerified email at umd.edu
John PreskillRichard P. Feynman Professor of Theoretical Physics, California Institute of TechnologyVerified email at caltech.edu

Giacomo Torlai

AWS Center for Quantum Computing

Verified email at amazon.com

Quantum Hardware Quantum Engineering Tensor Networks Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Neural-network quantum state tomography G Torlai, G Mazzola, J Carrasquilla, M Troyer, R Melko, G Carleo Nature Physics 14 (5), 447, 2018	716	2018
Learning thermodynamics with Boltzmann machines G Torlai, RG Melko Physical Review B 94 (16), 165134, 2016	274	2016
Reconstructing quantum states with generative models J Carrasquilla, G Torlai, RG Melko, L Aolita Nature Machine Intelligence 1 (3), 155-161, 2019	240	2019
Neural decoder for topological codes G Torlai, RG Melko Physical review letters 119 (3), 030501, 2017	176	2017
Latent space purification via neural density operators G Torlai, RG Melko Physical review letters 120 (24), 240503, 2018	129	2018
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	113	2019
Provably efficient machine learning for quantum many-body problems HY Huang, R Kueng, G Torlai, VV Albert, J Preskill Science 377 (6613), eabk3333, 2022	105	2022
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	87	2019
Machine-Learning Quantum States in the NISQ Era G Torlai, RG Melko Annual Review of Condensed Matter Physics 11, 325-344, 2020	76	2020
Precise measurement of quantum observables with neural-network estimators G Torlai, G Mazzola, G Carleo, A Mezzacapo Physical Review Research 2 (2), 022060, 2020	65	2020
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	50	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	41	2019
Wave-function positivization via automatic differentiation G Torlai, J Carrasquilla, MT Fishman, RG Melko, MPA Fisher Physical Review Research 2 (3), 032060, 2020	35	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	33	2023
How to use neural networks to investigate quantum many-body physics J Carrasquilla, G Torlai PRX Quantum 2 (4), 040201, 2021	33*	2021
QuCumber: wavefunction reconstruction with neural networks MJS Beach, I De Vlugt, A Golubeva, P Huembeli, B Kulchytskyy, X Luo, ... SciPost Physics 7 (1), 009, 2019	33	2019
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	21	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 87 (5), 052112, 2013	12	2013
Augmenting quantum mechanics with artificial intelligence G Torlai University of Waterloo, 2018	6	2018
Schmidt gap in random spin chains G Torlai, KD McAlpine, G De Chiara Physical Review B 98 (8), 085153, 2018	5	2018

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