Computing with Neuromorphic Dissipative Quantum Phase Transitions

Abstract

The objective of this experimental effort is to experimentally realize a computational ncuronnorphic network u sing cold atoms in a high-finesse cavity. This effort will utilize cold atoms trapped in a high-finesse multi-mode cavity as a neural network. The system makes use of light-atom interactions to realize a Hopficld neural network, where pattern learning is encoded using optical fields to perform a computation of a frustrating Ising model.

Document Details

Document Type
DoD Grant Award
Publication Date
Jan 12, 2017
Source ID
W911NF1510597

Entities

People

  • Benjamin Lev

Organizations

  • Army Contracting Command
  • Stanford University
  • United States Army

Tags

Fields of Study

  • Physics

Readers

  • Neural Network Machine Learning.
  • Optical Physics and Photonics.
  • Quantum Dot Semiconductor Device Photonics and Graphene Optoelectronic Materials and THz Physics.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks
  • Quantum Computing