Spectra and phase transition in Grover's algorithm with systematic noise

ORAL

Abstract

In this work, we present a study of Grover's search algorithm in the presence of systematic noise. By modeling the Grover operator within one timestep as a Floquet unitary, we showed that the bulk quasi-energy spectrum is well-captured by the first-order perturbation theory. Using the random matrix theory of an effective Hamiltonian, we obtain the scaling of the critical disorder for the algorithm. In addition, we also derive semi-analytical results for the oscillation frequency of the target state in the presence of noise.

*This work was performed with support from the National Science Foundation (NSF) through award numbers MPS-2228725 and DMR-1945529 and the Welch Foundation through award number AT-2036-20200401. Part of this work was performed at the Aspen Center for Physics, which is supported by NSF grant No. PHY-1607611, and at the Kavli Institute for Theoretical Physics, which is supported by NSF grant No. PHY-1748958. This project was funded by The University of Texas at Dallas Office of Research and Innovation through the SPIRe program.

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Presenters

  • Sasanka Dowarah

    • University of Texas at Dallas

Authors

  • Sasanka Dowarah

    • University of Texas at Dallas

  • Chuanwei Zhang

    • University of Texas at Dallas
    • The University of Texas at Dallas

  • Vedika Khemani

    • Stanford University

  • Michael Kolodrubetz

    • The University of Texas at Dallas