AlphaSyndrome: Tackling the Syndrome Measurement Circuit Scheduling Problem for QEC Codes

Fuente: arXiv
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Main Authors: Liu, Yuhao, Ping, Shuohao, Zhou, Junyu, Decker, Ethan, Kalloor, Justin, Weiden, Mathias, Chen, Kean, Shi, Yunong, Javadi-Abhari, Ali, Iancu, Costin, Li, Gushu
Format: Preprint
Published: 2026
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_version_ 1866917250469986304
author Liu, Yuhao
Ping, Shuohao
Zhou, Junyu
Decker, Ethan
Kalloor, Justin
Weiden, Mathias
Chen, Kean
Shi, Yunong
Javadi-Abhari, Ali
Iancu, Costin
Li, Gushu
author_facet Liu, Yuhao
Ping, Shuohao
Zhou, Junyu
Decker, Ethan
Kalloor, Justin
Weiden, Mathias
Chen, Kean
Shi, Yunong
Javadi-Abhari, Ali
Iancu, Costin
Li, Gushu
contents Quantum error correction (QEC) is essential for scalable quantum computing, yet repeated syndrome-measurement cycles dominate its spacetime and hardware cost. Although stabilizers commute and admit many valid execution orders, different schedules induce distinct error-propagation paths under realistic noise, leading to large variations in logical error rate. Outside of surface codes, effective syndrome-measurement scheduling remains largely unexplored. We present AlphaSyndrome, an automated synthesis framework for scheduling syndrome-measurement circuits in general commuting-stabilizer codes under minimal assumptions: mutually commuting stabilizers and a heuristic decoder. AlphaSyndrome formulates scheduling as an optimization problem that shapes error propagation to (i) avoid patterns close to logical operators and (ii) remain within the decoder's correctable region. The framework uses Monte Carlo Tree Search (MCTS) to explore ordering and parallelism, guided by code structure and decoder feedback. Across diverse code families, sizes, and decoders, AlphaSyndrome reduces logical error rates by 80.6% on average (up to 96.2%) relative to depth-optimal baselines, matches Google's hand-crafted surface-code schedules, and outperforms IBM's schedule for the Bivariate Bicycle code.
format Preprint
id arxiv_https___arxiv_org_abs_2601_12509
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle AlphaSyndrome: Tackling the Syndrome Measurement Circuit Scheduling Problem for QEC Codes
Liu, Yuhao
Ping, Shuohao
Zhou, Junyu
Decker, Ethan
Kalloor, Justin
Weiden, Mathias
Chen, Kean
Shi, Yunong
Javadi-Abhari, Ali
Iancu, Costin
Li, Gushu
Emerging Technologies
Quantum Physics
Quantum error correction (QEC) is essential for scalable quantum computing, yet repeated syndrome-measurement cycles dominate its spacetime and hardware cost. Although stabilizers commute and admit many valid execution orders, different schedules induce distinct error-propagation paths under realistic noise, leading to large variations in logical error rate. Outside of surface codes, effective syndrome-measurement scheduling remains largely unexplored. We present AlphaSyndrome, an automated synthesis framework for scheduling syndrome-measurement circuits in general commuting-stabilizer codes under minimal assumptions: mutually commuting stabilizers and a heuristic decoder. AlphaSyndrome formulates scheduling as an optimization problem that shapes error propagation to (i) avoid patterns close to logical operators and (ii) remain within the decoder's correctable region. The framework uses Monte Carlo Tree Search (MCTS) to explore ordering and parallelism, guided by code structure and decoder feedback. Across diverse code families, sizes, and decoders, AlphaSyndrome reduces logical error rates by 80.6% on average (up to 96.2%) relative to depth-optimal baselines, matches Google's hand-crafted surface-code schedules, and outperforms IBM's schedule for the Bivariate Bicycle code.
title AlphaSyndrome: Tackling the Syndrome Measurement Circuit Scheduling Problem for QEC Codes
topic Emerging Technologies
Quantum Physics
url https://arxiv.org/abs/2601.12509