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

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.