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  • 13 - Quantum phase estimation

  • from Part II - Quantum algorithmic primitives
  • Alexander M. Dalzell, AWS Center for Quantum Computing, Sam McArdle, AWS Center for Quantum Computing, Mario Berta, RWTH Aachen University, Przemyslaw Bienias, AWS Center for Quantum Computing, Chi-Fang Chen, University of California, Berkeley, András Gilyén, HUN-REN Alfréd Rényi Institute of Mathematics, Connor T. Hann, AWS Center for Quantum Computing, Michael J. Kastoryano, University of Copenhagen, Emil T. Khabiboulline, National Institute of Standards and Technology, Aleksander Kubica, Yale University, Grant Salton, Amazon Quantum Solutions Lab, Samson Wang, Caltech, Fernando G. S. L. Brandão, AWS Center for Quantum Computing
  • Book:
    Quantum Algorithms
    Published online:
    03 May 2025
    Print publication:
    24 April 2025, pp 228-234
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  • Summary

    This chapter covers the quantum algorithmic primitive called quantum phase estimation. Quantum phase estimation is an essential quantum algorithmic primitive that computes an estimate for the eigenvalue of a unitary operator, given as input an eigenstate of the operator. It features prominently in many end-to-end quantum algorithms, for example, computing ground state energies of physical systems in the areas of condensed matter physics and quantum chemistry. We carefully discuss nuances of quantum phase estimation that appear when it is applied to a superposition of eigenstates with different eigenvalues.