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Main Authors: Pech, Giulio, Gökduman, Mert, Yao, Hanwen, Pfister, Henry D.
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2601.14236
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author Pech, Giulio
Gökduman, Mert
Yao, Hanwen
Pfister, Henry D.
author_facet Pech, Giulio
Gökduman, Mert
Yao, Hanwen
Pfister, Henry D.
contents In this work, we develop a reduced complexity maximum likelihood (ML) decoder for quantum low-density parity-check (QLDPC) codes over erasures. Our decoder combines classical inactivation decoding, which integrates peeling with symbolic guessing, with a new dual peeling procedure. In the dual peeling stage, we perform row operations on the stabilizer matrix to efficiently reveal stabilizer generators and their linear combinations whose support lies entirely on the erased set. Each such stabilizer identified allows us to freely fix a bit in its support without affecting the logical state of the decoded result. This removes one degree of freedom that would otherwise require a symbolic guess, reducing the number of inactivated variables and decreasing the size of the final linear system that must be solved. We further show that dual peeling combined with standard peeling alone, without inactivation, is sufficient to achieve ML for erasure decoding of surface codes. Simulations across several QLDPC code families confirm that our decoder matches ML logical failure performance while significantly reducing the complexity of inactivation decoding, including more than a 20% reduction in symbolic guesses for the B1 lifted product code at high erasure rates.
format Preprint
id arxiv_https___arxiv_org_abs_2601_14236
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publishDate 2026
record_format arxiv
spellingShingle Stabilizer-Assisted Inactivation Decoding of Quantum Error-Correcting Codes with Erasures
Pech, Giulio
Gökduman, Mert
Yao, Hanwen
Pfister, Henry D.
Information Theory
In this work, we develop a reduced complexity maximum likelihood (ML) decoder for quantum low-density parity-check (QLDPC) codes over erasures. Our decoder combines classical inactivation decoding, which integrates peeling with symbolic guessing, with a new dual peeling procedure. In the dual peeling stage, we perform row operations on the stabilizer matrix to efficiently reveal stabilizer generators and their linear combinations whose support lies entirely on the erased set. Each such stabilizer identified allows us to freely fix a bit in its support without affecting the logical state of the decoded result. This removes one degree of freedom that would otherwise require a symbolic guess, reducing the number of inactivated variables and decreasing the size of the final linear system that must be solved. We further show that dual peeling combined with standard peeling alone, without inactivation, is sufficient to achieve ML for erasure decoding of surface codes. Simulations across several QLDPC code families confirm that our decoder matches ML logical failure performance while significantly reducing the complexity of inactivation decoding, including more than a 20% reduction in symbolic guesses for the B1 lifted product code at high erasure rates.
title Stabilizer-Assisted Inactivation Decoding of Quantum Error-Correcting Codes with Erasures
topic Information Theory
url https://arxiv.org/abs/2601.14236