activity
20192023
most citedDeep learning the Hohenberg-Kohn maps of Density Functional Theory

68 citations · 224 across the 7 of their papers we have counts for

collaborators

7 papers

cond-mat.str-el2023★ 2 cited

Mott Transition and Volume Law Entanglement with Neural Quantum States

Chloé Gauvin-Ndiaye, Joseph Tindall, Javier Robledo Moreno +1

The interplay between delocalisation and repulsive interactions can cause electronic systems to undergo a Mott transition between a metal and an insulator. Here we use neural netwo…

quant-ph2023★ 6 cited

Enhancing the Expressivity of Variational Neural, and Hardware-Efficient Quantum States Through Orbital Rotations

Javier Robledo Moreno, Jeffrey Cohn, Dries Sels +1

Variational approaches, such as variational Monte Carlo (VMC) or the variational quantum eigensolver (VQE), are powerful techniques to tackle the ground-state many-electron problem…

quant-ph2023★ 67 cited

Variational Benchmarks for Quantum Many-Body Problems

Dian Wu, Riccardo Rossi, Filippo Vicentini +30

The continued development of computational approaches to many-body ground-state problems in physics and chemistry calls for a consistent way to assess its overall progress. In this…

cond-mat.str-el2022★ 4 cited

Extracting Off-Diagonal Order from Diagonal Basis Measurements

Bo Xiao, Javier Robledo Moreno, Matthew Fishman +3

Quantum gas microscopy has developed into a powerful tool to explore strongly correlated quantum systems. However, discerning phases with topological or off-diagonal long range ord…

cond-mat.dis-nn2021★ 16 cited

Machine learning band gaps from the electron density

Javier Robledo Moreno, Johannes Flick, Antoine Georges

A remarkable consequence of the Hohenberg-Kohn theorem of density functional theory is the existence of an injective map between the electronic density and any observable of the ma…

cond-mat.str-el2020★ 61 cited

Phases of two-dimensional spinless lattice fermions with first-quantized deep neural-network quantum states

James Stokes, Javier Robledo Moreno, Eftychios A. Pnevmatikakis +1

First-quantized deep neural network techniques are developed for analyzing strongly coupled fermionic systems on the lattice. Using a Slater-Jastrow inspired ansatz which exploits…

cond-mat.dis-nn2019★ 68 cited

Deep learning the Hohenberg-Kohn maps of Density Functional Theory

Javier Robledo Moreno, Giuseppe Carleo, Antoine Georges

A striking consequence of the Hohenberg-Kohn theorem of density functional theory is the existence of a bijection between the local density and the ground-state many-body wave func…