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Filter Functions for Quantum Processes under Correlated Noise.

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This study introduces a new method to accurately model correlated noise in quantum computing, improving the understanding of quantum gate operations and enhancing error correction techniques for more reliable quantum computations.

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Area of Science:

  • Quantum Information Science
  • Quantum Computing
  • Quantum Error Correction

Background:

  • Standard theoretical tools for quantum computing often rely on Markov approximations, which fail to capture correlated noise.
  • Correlated noise, especially on timescales longer than gate durations, complicates the local description of noisy quantum gates.

Purpose of the Study:

  • To develop a method for computing quantum processes in the presence of correlated classical noise.
  • To generalize the filter function formalism for accurate noise modeling in quantum computing.

Main Methods:

  • Utilizing the filter function formalism for perturbative computation of quantum processes.
  • Deriving a composition rule for the filter function of a sequence of gates.

Main Results:

  • Developed a joint filter function for efficient computation of quantum processes in gate sequences.
  • Identified and characterized correlation terms that reveal the impact of noise on gate sequences.
  • Enabled efficient computation of quantum processes for entire gate sequences.

Conclusions:

  • The generalized filter function formalism accurately accounts for correlated noise in quantum gate sequences.
  • This approach provides qualitative and quantitative insights into noise correlations.
  • The method enhances the fidelity verification of quantum algorithms and tools like randomized benchmarking.