Di Luo
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Backflow Transformations via Neural Networks for Quantum Many-Body Wave Functions
D Luo, BK Clark
Physical Review Letters 122 (22), 226401, 2019
Deep Learning Enabled Strain Mapping of Single-Atom Defects in Two-Dimensional Transition Metal Dichalcogenides with Sub-Picometer Precision
CH Lee, A Khan, D Luo, TP Santos, C Shi, BE Janicek, S Kang, W Zhu, ...
Nano Letters 20 (5), 3369-3377, 2020
Autoregressive Transformer 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
Probabilistic simulation of quantum circuits with the Transformer
J Carrasquilla, D Luo, F Pérez, A Milsted, BK Clark, M Volkovs, L Aolita
Physical Review A 104 (3), 032610, 2021
Classical shadows for quantum process tomography on near-term quantum computers
R Levy, D Luo, BK Clark
Physical Review Research 6 (1), 013029, 2024
Framework for simulating gauge theories with dipolar spin systems
D Luo, J Shen, M Highman, BK Clark, B DeMarco, AX El-Khadra, ...
Physical Review A 102 (3), 032617, 2020
Gauge equivariant neural networks for quantum lattice gauge theories
D Luo, G Carleo, BK Clark, J Stokes
Physical Review Letters 127 (27), 276402, 2021
Protocol Discovery for the Quantum Control of Majoranas by Differentiable Programming and Natural Evolution Strategies
L Coopmans, D Luo, G Kells, BK Clark, J Carrasquilla
PRX Quantum 2 (2), 020332, 2021
Gauge Invariant and Anyonic Symmetric Transformer and RNN Quantum States for Quantum Lattice Models
D Luo, Z Chen, K Hu, Z Zhao, VM Hur, BK Clark
Physical Review Research 5 (1), 013216, 2023
Beyond many-body localized states in a spin-disordered Hubbard model
X Yu, D Luo, BK Clark
Physical Review B 98 (11), 115106, 2018
Gauge Equivariant Neural Networks for 2+ 1D U (1) Gauge Theory Simulations in Hamiltonian Formulation
D Luo, S Yuan, J Stokes, BK Clark
NeurIPS 2022 AI for Science Workshop, 2022
ANTN: Bridging Autoregressive Neural Networks and Tensor Networks for Quantum Many-Body Simulation
Z Chen, L Newhouse, E Chen, D Luo, M Soljacic
Thirty-seventh Conference on Neural Information Processing Systems, 2023
Finite-volume pionless effective field theory for few-nucleon systems with differentiable programming
X Sun, W Detmold, D Luo, PE Shanahan
Physical Review D 105 (7), 074508, 2022
Spacetime Neural Network for High Dimensional Quantum Dynamics
J Wang, Z Chen, D Luo, Z Zhao, VM Hur, BK Clark
38th International Conference on Machine Learning Workshop on ”Beyond first …, 2021
Variational Neural-Network Ansatz for Continuum Quantum Field Theory
JM Martyn, K Najafi, D Luo
Physical Review Letters 131 (8), 081601, 2023
Simulating 2+ 1D Lattice Quantum Electrodynamics at Finite Density with Neural Flow Wavefunctions
Z Chen, D Luo, K Hu, BK Clark
arXiv preprint arXiv:2212.06835, 2022
QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learning
D Luo, J Shen, R Dangovski, M Soljacic
Thirty-seventh Conference on Neural Information Processing Systems, 2023
GenPhys: From Physical Processes to Generative Models
Z Liu, D Luo, Y Xu, T Jaakkola, M Tegmark
arXiv preprint arXiv:2304.02637, 2023
Simulating quantum mechanics with a -term and an ’t Hooft anomaly on a synthetic dimension
J Shen, D Luo, C Huang, BK Clark, AX El-Khadra, B Gadway, P Draper
Physical Review D 105 (7), 074505, 2022
Infinite Neural Network Quantum States: Entanglement and Training Dynamics
D Luo, J Halverson
Machine Learning: Science and Technology, 2023
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