关注
Juan Felipe Carrasquilla Álvarez
Juan Felipe Carrasquilla Álvarez
ETH Zürich
在 ethz.ch 的电子邮件经过验证
标题
引用次数
引用次数
年份
Machine learning phases of matter
J Carrasquilla, RG Melko
Nature Physics 13 (5), 431, 2017
16932017
Neural-network quantum state tomography
G Torlai, G Mazzola, J Carrasquilla, M Troyer, R Melko, G Carleo
Nature physics 14 (5), 447-450, 2018
10002018
Machine learning phases of strongly correlated fermions
K Ch’Ng, J Carrasquilla, RG Melko, E Khatami
Physical Review X 7 (3), 031038, 2017
4342017
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
3872017
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
3702018
Reconstructing quantum states with generative models
J Carrasquilla, G Torlai, RG Melko, L Aolita
Nature Machine Intelligence 1 (3), 155-161, 2019
3652019
Recurrent neural network wave functions
M Hibat-Allah, M Ganahl, LE Hayward, RG Melko, J Carrasquilla
Physical Review Research 2 (2), 023358, 2020
2772020
Machine learning for quantum matter
J Carrasquilla
Advances in Physics: X 5 (1), 1797528, 2020
2772020
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
2352020
Restricted Boltzmann machines in quantum physics
RG Melko, G Carleo, J Carrasquilla, JI Cirac
Nature Physics 15 (9), 887-892, 2019
2332019
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
1092023
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—Atomic, Molecular, and Optical Physics 87 (4), 043606, 2013
1022013
Autoregressive neural network for simulating open quantum systems via a probabilistic formulation
D Luo, Z Chen, J Carrasquilla, BK Clark
Physical review letters 128 (9), 090501, 2022
902022
Neural Gutzwiller-projected variational wave functions
F Ferrari, F Becca, J Carrasquilla
Physical Review B 100 (12), 125131, 2019
902019
Variational neural annealing
M Hibat-Allah, EM Inack, R Wiersema, RG Melko, J Carrasquilla
Nature Machine Intelligence 3 (11), 952-961, 2021
842021
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
832021
Phase diagram of the half-filled one-dimensional -- model
T Mishra, J Carrasquilla, M Rigol
Physical Review B—Condensed Matter and Materials Physics 84 (11), 115135, 2011
832011
How to use neural networks to investigate quantum many-body physics
J Carrasquilla, G Torlai
PRX Quantum 2 (4), 040201, 2021
79*2021
Modern applications of machine learning in quantum sciences
A Dawid, J Arnold, B Requena, A Gresch, M Płodzień, K Donatella, ...
arXiv preprint arXiv:2204.04198, 2022
772022
Spectral tensor networks for many-body localization
A Chandran, J Carrasquilla, IH Kim, DA Abanin, G Vidal
Physical Review B 92 (2), 024201, 2015
692015
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