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Machine-Designed Sensor to Make Optimal Use of Entanglement-Generating Dynamics for Quantum Sensing.

Simon A Haine1, Joseph J Hope1

  • 1Department of Quantum Science, Research School of Physics, Australian National University, Canberra, ACT 0200, Australia.

Physical Review Letters
|February 29, 2020
PubMed
Summary
This summary is machine-generated.

Machine optimization enhances quantum sensing sensitivity by using entanglement during parameter interrogation, outperforming traditional methods for atomic clocks and sensors.

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Area of Science:

  • Quantum physics
  • Metrology
  • Machine learning

Background:

  • Traditional quantum sensing schemes often divide time into separate state-preparation and interrogation stages.
  • Achieving higher sensitivity typically requires more quantum resources or longer measurement times.

Purpose of the Study:

  • To develop a quantum sensing scheme using machine optimization for enhanced sensitivity.
  • To investigate the use of one-axis twisting dynamics for generating metrologically useful entanglement.

Main Methods:

  • Employed machine optimization to design a complex sequence of rotations.
  • Utilized one-axis twisting dynamics to generate quantum entanglement.
  • Integrated entanglement generation with parameter interrogation within a single temporal sequence.

Main Results:

  • The machine-optimized scheme achieved significantly better sensitivity than traditional schemes with identical quantum resources.
  • The proposed method generates metrologically useful entanglement during parameter interrogation, improving sensitivity for a given total time.
  • Demonstrated higher sensitivities compared to standard one-axis twisting schemes.

Conclusions:

  • Machine optimization offers a powerful approach to designing quantum sensing protocols.
  • Integrating entanglement generation and parameter interrogation enhances sensing capabilities.
  • This method holds potential for improving atomic clocks, magnetometers, and inertial sensors.