Related references
Note: Only part of the references are listed.Machine learning in electronic-quantum-matter imaging experiments
Yi Zhang et al.
NATURE (2019)
Identifying quantum phase transitions using artificial neural networks on experimental data
Benno S. Rem et al.
NATURE PHYSICS (2019)
Direct observation of incommensurate magnetism in Hubbard chains
Guillaume Salomon et al.
NATURE (2019)
Spin transport in a Mott insulator of ultracold fermions
Matthew A. Nichols et al.
SCIENCE (2019)
Bad metallic transport in a cold atom Fermi-Hubbard system
Peter T. Brown et al.
SCIENCE (2019)
Probing hidden spin order with interpretable machine learning
Jonas Greitemann et al.
PHYSICAL REVIEW B (2019)
Microscopic spinon-chargon theory of magnetic polarons in the t-J model
Fabian Grusdt et al.
PHYSICAL REVIEW B (2019)
Efficient representation of topologically ordered states with restricted Boltzmann machines
Sirui Lu et al.
PHYSICAL REVIEW B (2019)
Machine learning of quantum phase transitions
Xiao-Yu Dong et al.
PHYSICAL REVIEW B (2019)
Learning multiple order parameters with interpretable machines
Ke Liu et al.
PHYSICAL REVIEW B (2019)
Mutual information, neural networks and the renormalization group
Maciej Koch-Janusz et al.
NATURE PHYSICS (2018)
Neural-network quantum state tomography
Giacomo Torlai et al.
NATURE PHYSICS (2018)
Symmetries and Many-Body Excitations with Neural-Network Quantum States
Kenny Choo et al.
PHYSICAL REVIEW LETTERS (2018)
Meson formation in mixed-dimensional t - J models
Fabian Grusdt et al.
SCIPOST PHYSICS (2018)
Machine learning vortices at the Kosterlitz-Thouless transition
Matthew J. S. Beach et al.
PHYSICAL REVIEW B (2018)
A cold-atom Fermi-Hubbard antiferromagnet
Anton M. Azurenko et al.
NATURE (2017)
Learning phase transitions by confusion
Evert P. L. van Nieuwenburg et al.
NATURE PHYSICS (2017)
Machine learning phases of matter
Juan Carrasquilla et al.
NATURE PHYSICS (2017)
Revealing hidden antiferromagnetic correlations in doped Hubbard chains via string correlators
Timon A. Hilker et al.
SCIENCE (2017)
Solving the quantum many-body problem with artificial neural networks
Giuseppe Carleo et al.
SCIENCE (2017)
Machine learning quantum phases of matter beyond the fermion sign problem
Peter Broecker et al.
SCIENTIFIC REPORTS (2017)
Observation of spatial charge and spin correlations in the 2D Fermi-Hubbard model
Lawrence W. Cheuk et al.
SCIENCE (2016)
Observation of antiferromagnetic correlations in the Hubbard model with ultracold atoms
Russell A. Hart et al.
NATURE (2015)
From quantum matter to high-temperature superconductivity in copper oxides
B. Keimer et al.
NATURE (2015)
Quantum dimer model for the pseudogap metal
Matthias Punk et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2015)
Short-Range Quantum Magnetism of Ultracold Fermions in an Optical Lattice
Daniel Greif et al.
SCIENCE (2013)
String excitations of a hole in a quantum antiferromagnet and photoelectron spectroscopy
Efstratios Manousakis
PHYSICAL REVIEW B (2007)
Doping a Mott insulator: Physics of high-temperature superconductivity
PA Lee et al.
REVIEWS OF MODERN PHYSICS (2006)
Share Paper
