% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Rispler:1038537,
      author       = {Rispler, Manuel and Vodola, Davide and Müller, Markus and
                      Kim, Seyong},
      title        = {{T}he random coupled-plaquette gauge model and the surface
                      code under circuit-level noise},
      reportid     = {FZJ-2025-01522, arXiv:2412.14004},
      year         = {2025},
      abstract     = {We map the decoding problem of the surface code under
                      depolarizing and syndrome noise to a disordered spin model,
                      which we call the random coupled-plaquette gauge model
                      (RCPGM). By coupling X- and Z-syndrome volumes, this model
                      allows us to optimally account for genuine Y-errors in the
                      surface code in a setting with noisy measurements. Using
                      Parallel Tempering Monte Carlo simulations, we determine the
                      code's fundamental error threshold. Firstly, for the
                      phenomenological noise setting we determine a threshold of
                      $6\\%$ under uniform depolarizing and syndrome noise. This
                      is a substantial improvement compared to results obtained
                      via the previously known 'uncoupled' random plaquette gauge
                      model (RPGM) in the identical setting, where marginalizing
                      Y-errors leads to a threshold of $4.3\\%$. Secondly, we
                      tackle the circuit-level noise scenario, where we use a
                      reduction technique to find effective asymmetric
                      depolarizing and syndrome noise rates to feed into the RCPGM
                      mapping. Despite this reduction technique breaking up some
                      of the correlations contained in the intricacies of
                      circuit-level noise, we find an improvement exceeding that
                      for the phenomenological case. We report a threshold of up
                      to $1.4\\%$, to be compared to $0.7\\%$ under the identical
                      noise model when marginalizing the Y-errors and mapping to
                      the anisotropic RPGM. These results enlarge the landscape of
                      statistical mechanical mappings for quantum error
                      correction. In particular they provide an underpinning for
                      the broadly held belief that accounting for Y-errors is a
                      major bottleneck in improving surface code decoders. This is
                      highly encouraging for leading efficient practical decoder
                      development, where heuristically accounting for Y-error
                      correlations has seen recent developments such as
                      belief-matching. This suggests that there is further room
                      for improvement of the surface code for fault-tolerant
                      quantum computation.},
      cin          = {PGI-2},
      cid          = {I:(DE-Juel1)PGI-2-20110106},
      pnm          = {5221 - Advanced Solid-State Qubits and Qubit Systems
                      (POF4-522)},
      pid          = {G:(DE-HGF)POF4-5221},
      typ          = {PUB:(DE-HGF)25},
      eprint       = {2412.14004},
      howpublished = {arXiv:2412.14004},
      archivePrefix = {arXiv},
      SLACcitation = {$\%\%CITATION$ = $arXiv:2412.14004;\%\%$},
      url          = {https://juser.fz-juelich.de/record/1038537},
}