Randomly Disordered-Topological Edge-State of Rydberg Atom Array

Abstract

Rydberg atoms would be essential ingredients in the N-qubit operation. However, we need to control and identify the N-Rydberg system efficiently. For control, we demonstrated a fast-image processing technique applied to atom array. To remove ambiguity, we theoretically demonstrated how to identify the base states of the Rydberg-atoms inversely via machine learning (ML). Due to the UM institutional policy and PIs personal situation, the project could not be completed, and the remaining budget had been returned to AOARD. However, this final report includes an update of the PIs academic activities supported by the grant.

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Document Details

Document Type
Technical Report
Publication Date
May 17, 2023
Accession Number
AD1215677

Entities

People

  • Heejeong Jeong

Organizations

  • Universiti Malaya

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Air Force
  • Air Force Research Laboratories
  • Atoms
  • Computational Science
  • Data Sets
  • Electronic Mail
  • Image Processing
  • Learning
  • Machine Learning
  • Photonics
  • Quantum Computing
  • Quantum Information
  • Rydberg Atoms
  • Schematic Diagrams
  • Three Dimensional
  • Universities

Fields of Study

  • Physics

Readers

  • Quantum Dot Semiconductor Device Photonics and Graphene Optoelectronic Materials and THz Physics.
  • Quantum spin resonance or Electron Paramagnetic Resonance spectroscopy.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms