Juan Felipe Carrasquilla Álvarez

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Roger G. MelkoFaculty, University of Waterloo & Perimeter Institute; Affiliate, Vector InstituteVerified email at uwaterloo.ca
Giacomo TorlaiAWS Center for Quantum ComputingVerified email at amazon.com
Giuseppe CarleoAssistant Professor of Computational Quantum Science - EPFL, Lausanne, SwitzerlandVerified email at epfl.ch
Marcos RigolProfessor of Physics, Penn State UniversityVerified email at phys.psu.edu
Leandro AolitaQuantum Research Centre - Technology Innovation InstituteVerified email at tii.ae
Mohamed Hibat-AllahPSI Fellow, Perimeter Institute for Theoretical PhysicsVerified email at perimeterinstitute.ca
Roeland WiersemaPhD Student, University of Waterloo / Vector InstituteVerified email at uwaterloo.ca
Guglielmo MazzolaUniversity of ZurichVerified email at uzh.ch
Matthias TroyerMicrosoft QuantumVerified email at microsoft.com
Ehsan KhatamiSan Jose State UniversityVerified email at sjsu.edu
Federico BeccaUniversity of TriesteVerified email at units.it
Roman Eduardo Castaneda SepulvedaUniversidad Nacional de ColombiaVerified email at unal.edu.co
Jorge Garcia-SucerquiaProfessor Universidad Nacional de Colombia Sede MedellinVerified email at unal.edu.co
Di LuoMassachusetts Institute of TechnologyVerified email at mit.edu
Lauren E. HaywardTeaching Faculty, Perimeter Institute; Adjunct Assistant Professor, University of WaterlooVerified email at perimeterinstitute.ca
Simon TrebstUniversity of CologneVerified email at thp.uni-koeln.de
Andrea Di CioloCNR - Institute of Nanoscience (Modena, Italy)Verified email at nano.cnr.it
Victor GalitskiProfessor, Joint Quantum Institute, University of MarylandVerified email at umd.edu
Eun-Ah KimProfessor of Physics, Cornell UniversityVerified email at cornell.edu
Peter ChaCornell UniversityVerified email at cornell.edu

Juan Felipe Carrasquilla Álvarez

Vector Institute for Artificial Intelligence. Canada CIFAR AI chair

Verified email at vectorinstitute.ai - Homepage

Theoretical condensed matter physics quantum computing machine learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Machine learning phases of matter J Carrasquilla, RG Melko Nature Physics 13 (5), 431, 2017	1446	2017
Neural-network quantum state tomography G Torlai, G Mazzola, J Carrasquilla, M Troyer, R Melko, G Carleo Nature Physics 14 (5), 447-450, 2018	804	2018
Machine learning phases of strongly correlated fermions K Ch’Ng, J Carrasquilla, RG Melko, E Khatami Physical Review X 7 (3), 031038, 2017	405	2017
Machine learning quantum phases of matter beyond the fermion sign problem P Broecker, J Carrasquilla, RG Melko, S Trebst Scientific reports 7 (1), 8823, 2017	366	2017
Observation of topological phenomena in a programmable lattice of 1,800 qubits AD King, J Carrasquilla, J Raymond, I Ozfidan, E Andriyash, A Berkley, ... Nature 560 (7719), 456-460, 2018	314	2018
Reconstructing quantum states with generative models J Carrasquilla, G Torlai, RG Melko, L Aolita Nature Machine Intelligence 1 (3), 155-161, 2019	277	2019
Machine learning for quantum matter J Carrasquilla Advances in Physics: X 5 (1), 1797528, 2020	201	2020
Recurrent neural network wave functions M Hibat-Allah, M Ganahl, LE Hayward, RG Melko, J Carrasquilla Physical Review Research 2 (2), 023358, 2020	182	2020
Restricted Boltzmann machines in quantum physics RG Melko, G Carleo, J Carrasquilla, JI Cirac Nature Physics 15 (9), 887-892, 2019	179	2019
Exploring entanglement and optimization within the hamiltonian variational ansatz R Wiersema, C Zhou, Y de Sereville, JF Carrasquilla, YB Kim, H Yuen PRX Quantum 1 (2), 020319, 2020	157	2020
Scaling of the gap, fidelity susceptibility, and Bloch oscillations across the superfluid-to-Mott-insulator transition in the one-dimensional Bose-Hubbard model J Carrasquilla, SR Manmana, M Rigol Physical Review A 87 (4), 043606, 2013	98	2013
Neural Gutzwiller-projected variational wave functions F Ferrari, F Becca, J Carrasquilla Physical Review B 100 (12), 125131, 2019	73	2019
Phase diagram of the half-filled one-dimensional -- model T Mishra, J Carrasquilla, M Rigol Physical Review B 84 (11), 115135, 2011	68	2011
Spectral tensor networks for many-body localization A Chandran, J Carrasquilla, IH Kim, DA Abanin, G Vidal Physical Review B 92 (2), 024201, 2015	64	2015
Quantum distillation and confinement of vacancies in a doublon sea L Xia, LA Zundel, J Carrasquilla, A Reinhard, JM Wilson, M Rigol, ... Nature Physics 11 (4), 316-320, 2015	51	2015
Attention-based quantum tomography P Cha, P Ginsparg, F Wu, J Carrasquilla, PL McMahon, EA Kim Machine Learning: Science and Technology 3 (1), 01LT01, 2021	50	2021
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	49	2023
How to use neural networks to investigate quantum many-body physics J Carrasquilla, G Torlai PRX Quantum 2 (4), 040201, 2021	47*	2021
Expansion of Bose-Hubbard Mott insulators in optical lattices M Jreissaty, J Carrasquilla, FA Wolf, M Rigol Physical Review A 84 (4), 043610, 2011	46	2011
Variational neural annealing M Hibat-Allah, EM Inack, R Wiersema, RG Melko, J Carrasquilla Nature Machine Intelligence 3 (11), 952-961, 2021	45	2021

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