Quantum autoencoders to denoise quantum data

Entangled states are an important resource for quantum computation, communication, metrology, and the simulation of many-body systems. However, noise limits the experimental preparation of such states. Classical data can be efficiently denoised by autoencoders---neural networks trained in unsupervis...

Celý popis

Podrobná bibliografia

Vydané v:	arXiv.org
Hlavní autori:	Bondarenko, Dmytro, Feldmann, Polina
Médium:	Paper
Jazyk:	English
Vydavateľské údaje:	Ithaca Cornell University Library, arXiv.org 21.10.2019
Predmet:	Computer simulation Entangled states Neural networks Noise reduction Quantum computing
ISSN:	2331-8422
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!