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Optimizing Shot Assignment in Variational Quantum Eigensolver Measurement.

Linghua Zhu1, Senwei Liang2, Chao Yang2

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We introduce Variance-Preserved Shot Reduction (VPSR), a new method for variational quantum eigensolvers (VQE). VPSR significantly reduces measurement shots needed for VQE, lowering costs while maintaining accuracy for quantum chemistry calculations.

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Area of Science:

  • Quantum computing
  • Quantum chemistry
  • Computational physics

Background:

  • Variational quantum eigensolvers (VQE) are promising for quantum chemistry.
  • VQE's measurement step is prone to errors and high costs.
  • Current shot assignment strategies aim to reduce measurement variance.

Purpose of the Study:

  • To introduce a dynamic shot assignment method for VQE.
  • To minimize total measurement shots while preserving measurement variance.
  • To reduce the overall cost of VQE computations.

Main Methods:

  • Developed the Variance-Preserved Shot Reduction (VPSR) method.
  • Implemented a dynamic shot allocation strategy.
  • Tested VPSR on H2 and LiH molecular ground state calculations.

Main Results:

  • VPSR effectively reduces the number of measurement shots required for VQE.
  • The method achieves VQE convergence with significantly fewer shots.
  • Measurement variance is preserved throughout the VQE process using VPSR.

Conclusions:

  • VPSR offers a cost-effective approach to VQE.
  • This method enhances the practicality of VQE for complex quantum chemistry problems.
  • VPSR contributes to realizing quantum advantage in computational chemistry.