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Quantum Simulators: Architectures and Opportunities
Ehud Altman, Kenneth R. Brown, Giuseppe Carleo +34
Quantum simulators are a promising technology on the spectrum of quantum devices from specialized quantum experiments to universal quantum computers. These quantum devices utilize…
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…
Precise measurement of quantum observables with neural-network estimators
Giacomo Torlai, Guglielmo Mazzola, Giuseppe Carleo +1
The measurement precision of modern quantum simulators is intrinsically constrained by the limited set of measurements that can be efficiently implemented on hardware. This fundame…
Fermionic neural-network states for ab-initio electronic structure
Kenny Choo, Antonio Mezzacapo, Giuseppe Carleo
Neural-network quantum states have been successfully used to study a variety of lattice and continuous-space problems. Despite a great deal of general methodological developments,…
Quantum Natural Gradient
James Stokes, Josh Izaac, Nathan Killoran +1
A quantum generalization of Natural Gradient Descent is presented as part of a general-purpose optimization framework for variational quantum circuits. The optimization dynamics is…
NetKet: A Machine Learning Toolkit for Many-Body Quantum Systems
Giuseppe Carleo, Kenny Choo, Damian Hofmann +15
We introduce NetKet, a comprehensive open source framework for the study of many-body quantum systems using machine learning techniques. The framework is built around a general and…
Study of the Two-Dimensional Frustrated J1-J2 Model with Neural Network Quantum States
Kenny Choo, Titus Neupert, Giuseppe Carleo
The use of artificial neural networks to represent quantum wave-functions has recently attracted interest as a way to solve complex many-body problems. The potential of these varia…
Ground state phase diagram of the one-dimensional Bose-Hubbard model from restricted Boltzmann machines
Kristopher McBrian, Giuseppe Carleo, Ehsan Khatami
Motivated by recent advances in the representation of ground state wavefunctions of quantum many-body systems using restricted Boltzmann machines as variational ansatz, we utilize…
Machine learning and the physical sciences
Giuseppe Carleo, Ignacio Cirac, Kyle Cranmer +5
Machine learning encompasses a broad range of algorithms and modeling tools used for a vast array of data processing tasks, which has entered most scientific disciplines in recent…
Neural-Network Approach to Dissipative Quantum Many-Body Dynamics
Michael J. Hartmann, Giuseppe Carleo
In experimentally realistic situations, quantum systems are never perfectly isolated and the coupling to their environment needs to be taken into account. Often, the effect of the…
Deep autoregressive models for the efficient variational simulation of many-body quantum systems
Or Sharir, Yoav Levine, Noam Wies +2
Artificial Neural Networks were recently shown to be an efficient representation of highly-entangled many-body quantum states. In practical applications, neural-network states inhe…