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Area of Science:

  • Quantum Computing
  • Quantum Information Science
  • Computational Chemistry

Background:

  • Variational quantum algorithms (VQAs) require efficient estimation of expectation values for many Pauli observables.
  • Randomized measurement strategies are commonly used but can be inefficient in terms of state copies required.
  • Estimating expectation values is crucial for tasks like determining ground-state energies.

Purpose of the Study:

  • To propose an efficient derandomization procedure for estimating expectation values of multiple Pauli observables.
  • To reduce the number of quantum state copies needed for accurate measurements.
  • To demonstrate the advantages of the proposed method over existing randomized techniques.

Main Methods:

  • Developed an iterative derandomization procedure that replaces random single-qubit measurements with fixed Pauli measurements.
  • Analyzed the performance guarantee of the deterministic measurement procedure compared to randomized methods.
  • Investigated the scaling of state copies required, particularly for low-weight Pauli observables (order log L).

Main Results:

  • The proposed deterministic measurement procedure performs at least as well as randomized methods.
  • Estimating L low-weight Pauli observables requires only O(log L) quantum state copies.
  • The derandomized procedure shows substantial improvements, especially for high-weight Pauli observables.
  • Numerical experiments confirm the advantages for estimating ground-state energies of small molecules.

Conclusions:

  • The derandomization technique offers a more efficient and robust approach for expectation value estimation in VQAs.
  • This method significantly reduces the quantum resources (state copies) needed for complex quantum computations.
  • The findings have practical implications for advancing quantum chemistry simulations and other VQA applications.