Paper

{
  "raw_xml": "<entry>\n    <id>http://arxiv.org/abs/2603.19062v1</id>\n    <title>Fair Decoder Baselines and Rigorous Finite-Size Scaling for Bivariate Bicycle Codes on the Quantum Erasure Channel</title>\n    <updated>2026-03-19T15:53:51Z</updated>\n    <link href='https://arxiv.org/abs/2603.19062v1' rel='alternate' type='text/html'/>\n    <link href='https://arxiv.org/pdf/2603.19062v1' rel='related' title='pdf' type='application/pdf'/>\n    <summary>Fair threshold estimation for bivariate bicycle (BB) codes on the quantum erasure channel runs into two recurring problems: decoder-baseline unfairness and the conflation of finite-size pseudo-thresholds with true asymptotic thresholds. We run both uninformed and \\emph{erasure-aware} minimum-weight perfect matching (MWPM) surface code baselines alongside BP-OSD decoding of BB codes. With standard depolarizing-weight MWPM and no erasure information, performance matches random guessing on the erasure channel in our tested regime -- so prior work that compares against this baseline is really comparing decoders, not codes. Using 200{,}000 shots per point and bootstrap confidence intervals, we sweep five BB code sizes from $N=144$ to $N=1296$. Pseudo-thresholds (WER = 0.10) run from $p^* = 0.370$ to $0.471$; finite-size scaling (FSS) gives an asymptotic threshold $p^*_\\infty \\approx 0.488$, within 2.4\\% of the zero-rate limit and without maximum-likelihood decoding. On the fair baseline, BB at $N=1296$ has a modest edge in threshold over the surface code at twice the qubit count, and a 12$\\times$ lower normalized overhead -- the latter is where the practical advantage sits. All runs are reproducible from recorded seeds and package versions.</summary>\n    <category scheme='http://arxiv.org/schemas/atom' term='quant-ph'/>\n    <published>2026-03-19T15:53:51Z</published>\n    <arxiv:comment>7 figures and 2 tables</arxiv:comment>\n    <arxiv:primary_category term='quant-ph'/>\n    <author>\n      <name>Tushar Pandey</name>\n    </author>\n  </entry>"
}