Neural-network quantum state tomography

• Published in: Nature physics Vol. 14; no. 5; pp. 447 - 450
• Main Authors: Torlai, Giacomo, Mazzola, Guglielmo, Carrasquilla, Juan, Troyer, Matthias, Melko, Roger, Carleo, Giuseppe
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.05.2018; Nature Publishing Group
• Subjects: 119/118; 639/705/1042; 639/766/483/2802; 639/766/483/3924; 639/766/483/481; 639/766/930/12; Artificial intelligence; Atomic; Classical and Continuum Physics; Complex Systems; Computer simulation; Condensed Matter Physics; Entangled states; Letter; Machine learning; Mathematical and Computational Physics; Molecular; Neural networks; Optical and Plasma Physics; Physics; Physics and Astronomy; Quantum computers; Quantum entanglement; Quantum theory; Qubits (quantum computing); Theoretical; Tomography

The experimental realization of increasingly complex synthetic quantum systems calls for the development of general theoretical methods to validate and fully exploit quantum resources. Quantum state tomography (QST) aims to reconstruct the full quantum state from simple measurements, and therefore p...