Extrapolating Quantum Observables with Machine Learning: Inferring Multiple Phase Transitions from Properties of a Single Phase

Neural-network quantum state tomography

(2018) Giacomo Torlai et al.   Nature Physics

Discriminative Cooperative Networks for Detecting Phase Transitions

(2018) Ye-Hua Liu et al.   PHYSICAL REVIEW LETTERS

Machine Learning Out-of-Equilibrium Phases of Matter

(2018) Jordan Venderley et al.   PHYSICAL REVIEW LETTERS

Learning phase transitions by confusion

(2017) Evert P. L. van Nieuwenburg et al.   Nature Physics

Machine learning phases of matter

(2017) Juan Carrasquilla et al.   Nature Physics

Solving the quantum many-body problem with artificial neural networks

(2017) Giuseppe Carleo et al.   SCIENCE

Efficient representation of quantum many-body states with deep neural networks

(2017) Xun Gao et al.   Nature Communications

Quantum Entanglement in Neural Network States

(2017) Dong-Ling Deng et al.   Physical Review X

Machine Learning Phases of Strongly Correlated Fermions

(2017) Kelvin Ch’ng et al.   Physical Review X

Phonon-mediated repulsion, sharp transitions and (quasi)self-trapping in the extended Peierls-Hubbard model

(2017) J. Sous et al.   Scientific Reports

Machine learning quantum phases of matter beyond the fermion sign problem

(2017) Peter Broecker et al.   Scientific Reports

Deep Learning the Quantum Phase Transitions in Random Two-Dimensional Electron Systems

(2016) Tomoki Ohtsuki et al.   JOURNAL OF THE PHYSICAL SOCIETY OF JAPAN

Machine Learning Energies of 2 Million Elpasolite(ABC2D6)Crystals

(2016) Felix A. Faber et al.   PHYSICAL REVIEW LETTERS

Crystal structure representations for machine learning models of formation energies

(2015) Felix Faber et al.   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

Big Data of Materials Science: Critical Role of the Descriptor

(2015) Luca M. Ghiringhelli et al.   PHYSICAL REVIEW LETTERS

Strongly bound yet light bipolarons for double-well electron-phonon coupling

(2014) Clemens P. J. Adolphs et al.   PHYSICAL REVIEW B

Machine learning for many-body physics: The case of the Anderson impurity model

(2014) Louis-François Arsenault et al.   PHYSICAL REVIEW B

How to represent crystal structures for machine learning: Towards fast prediction of electronic properties

(2014) K. T. Schütt et al.   PHYSICAL REVIEW B

Investigating Polaron Transitions with Polar Molecules

(2013) Felipe Herrera et al.   PHYSICAL REVIEW LETTERS

Momentum average approximation for models with boson-modulated hopping: Role of closed loops in the dynamical generation of a finite quasiparticle mass

(2010) Mona Berciu et al.   PHYSICAL REVIEW B

Sharp Transition for Single Polarons in the One-Dimensional Su-Schrieffer-Heeger Model

(2010) D. J. J. Marchand et al.   PHYSICAL REVIEW LETTERS

Momentum average approximation for models with electron-phonon coupling dependent on the phonon momentum

(2008) Glen L. Goodvin et al.   PHYSICAL REVIEW B