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Learning Fermionic Correlations by Evolving with Random Translationally Invariant Hamiltonians.

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This study introduces a new measurement scheme for analog quantum simulators, enabling efficient estimation of correlation functions. The method is practical for current experimental platforms, enhancing quantum device readout capabilities.

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Area of Science:

  • Quantum Information Science
  • Condensed Matter Physics

Background:

  • Classical shadow schemes are vital for digital quantum device readout.
  • Analog quantum simulators lack similar practical measurement tools.

Purpose of the Study:

  • Develop a practical measurement scheme for analog quantum simulators.
  • Estimate second and fourth order correlation functions in fermionic systems.

Main Methods:

  • Utilize free fermionic, translationally invariant evolutions (quenches).
  • Employ measurements in the mode occupation number basis.
  • Characterize recoverable correlation functions and sample complexities.

Main Results:

  • Developed a scheme for estimating correlation functions in fermionic quantum devices.
  • Provided rigorous bounds on sample complexities for the estimation.
  • Demonstrated approximate implementation using nearest-neighbor hopping quenches.

Conclusions:

  • Brings classical shadow concepts to large-scale analog quantum simulators.
  • Offers a practical approach for current experimental requirements.
  • Facilitates enhanced readout and characterization of quantum simulators.