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Deterministic improvements of quantum measurements with grouping of compatible operators, non-local transformations, and covariance estimates.

Tzu-Ching YenAadithya GaneshramArtur F Izmaylov
Published in: NPJ quantum information (2023)
Obtaining the expectation value of an observable on a quantum computer is a crucial step in the variational quantum algorithms. For complicated observables such as molecular electronic Hamiltonians, one of the strategies is to present the observable as a linear combination of measurable fragments. The main problem of this approach is a large number of measurements required for accurate estimation of the observable's expectation value. We consider three previously studied directions that minimize the number of measurements: (1) grouping commuting operators using the greedy approach, (2) involving non-local unitary transformations for measuring, and (3) taking advantage of compatibility of some Pauli products with several measurable groups. The last direction gives rise to a general framework that not only provides improvements over previous methods but also connects measurement grouping approaches with recent advances in techniques of shadow tomography. Following this direction, we develop two measurement schemes that achieve a severalfold reduction in the number of measurements for a set of model molecules compared to previous state-of-the-art methods.
Keyphrases
  • molecular dynamics
  • deep learning
  • machine learning
  • energy transfer
  • high resolution
  • mass spectrometry
  • quantum dots