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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Creating and concentrating quantum resource states in noisy environments using a quantum neural network.

Tanjung Krisnanda1, Sanjib Ghosh1, Tomasz Paterek2

  • 1School of Physical and Mathematical Sciences, Nanyang Technological University, 637371 Singapore, Singapore.

Neural Networks : the Official Journal of the International Neural Network Society
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PubMed
Summary

This study introduces a unified quantum state preparation scheme using a driven quantum network. The method reliably generates various exotic quantum states, even under noisy conditions, by tuning network parameters.

Keywords:
Neural network applicationsOptimizationQuantum entanglementQuantum informationQuantum machine learningQuantum neural networkQuantum state preparation

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Area of Science:

  • Quantum Information Science
  • Quantum Computing
  • Condensed Matter Physics

Background:

  • Quantum information processing relies on preparing specific, often complex, quantum states.
  • Current methods for preparing quantum states are typically specialized and resource-intensive.

Purpose of the Study:

  • To develop a versatile and unified scheme for preparing diverse quantum states.
  • To demonstrate the robustness of the proposed method under realistic noisy conditions.

Main Methods:

  • Utilizing a driven quantum network of randomly-coupled fermionic nodes.
  • Employing linear mixing with trainable weights and phases to superpose network outputs.
  • Investigating the impact of energy decay, dephasing, and depolarization on state preparation.

Main Results:

  • Successfully generated highly accurate maximally entangled, NOON, W, cluster, and discorded states.
  • Achieved high fidelity state preparation even in the presence of significant energy decay, dephasing, and depolarization.
  • Demonstrated entanglement concentration in highly noisy systems by increasing network size.

Conclusions:

  • The proposed driven quantum network scheme offers a robust and unified approach to quantum state preparation.
  • The method's adaptability and resilience to noise make it a promising tool for advancing quantum information processing.
  • Entanglement concentration offers a strategy for overcoming noise limitations in future quantum technologies.