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A taxonomy of small Markovian errors

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arxiv 2103.01928 v1 pith:5BZW76P2 submitted 2021-03-02 quant-ph

classification quant-ph
keywords errorerrorselementarygategeneratorgeneratorsprocessmatrices
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abstract

Errors in quantum logic gates are usually modeled by quantum process matrices (CPTP maps). But process matrices can be opaque, and unwieldy. We show how to transform a gate's process matrix into an error generator that represents the same information more usefully. We construct a basis of simple and physically intuitive elementary error generators, classify them, and show how to represent any gate's error generator as a mixture of elementary error generators with various rates. Finally, we show how to build a large variety of reduced models for gate errors by combining elementary error generators and/or entire subsectors of generator space. We conclude with a few examples of reduced models, including one with just $9N^2$ parameters that describes almost all commonly predicted errors on an N-qubit processor.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Tensor-network decoders for process tensor descriptions of non-Markovian noise

    quant-ph 2024-12 conditional novelty 6.0 of 10

    A tensor-network-based maximum likelihood decoder is constructed for quantum error correction under process-tensor noise, with an MPS approximation demonstrated on the five-qubit and Steane codes.

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