Spiking neuromorphic chip learns entangled quantum states

Volume: 12, Issue: 1
Published: Jan 26, 2022
Abstract
The approximation of quantum states with artificial neural networks has gained a lot of attention during the last years. Meanwhile, analog neuromorphic chips, inspired by structural and dynamical properties of the biological brain, show a high energy efficiency in running artificial neural-network architectures for the profit of generative applications. This encourages employing such hardware systems as platforms for simulations of quantum...
Paper Details
Title
Spiking neuromorphic chip learns entangled quantum states
Published Date
Jan 26, 2022
Volume
12
Issue
1
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.