Work

Recurrent neural network wave functions

Year: 2020

Type: article

Abstract: This paper introduces a new class of computationally tractable wavefunctions, called recurrent neural network wavefunctions, based on recurrent neural network technology. The authors show that these wavefunctions outperform optimization methods for strongly correlated many-body systems with less variational parameters.

Source: Physical Review Research

DOI: 10.1103/physrevresearch.2.023358

Authors: Mohamed Hibat-Allah, Martin Ganahl, Lauren E. Hayward, Roger G. Melko, Juan Carrasquilla

Institutions: University of Waterloo, Perimeter Institute, MaRS, Vector Institute

Language: English

Topic: Quantum many-body systems

Subfield: Atomic and Molecular Physics, and Optics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,625