AlphaSyndrome: Tackling the Syndrome Measurement Circuit Scheduling Problem for QEC Codes
- URL: http://arxiv.org/abs/2601.12509v1
- Date: Sun, 18 Jan 2026 17:45:58 GMT
- Title: AlphaSyndrome: Tackling the Syndrome Measurement Circuit Scheduling Problem for QEC Codes
- Authors: Yuhao Liu, Shuohao Ping, Junyu Zhou, Ethan Decker, Justin Kalloor, Mathias Weiden, Kean Chen, Yunong Shi, Ali Javadi-Abhari, Costin Iancu, Gushu Li,
- Abstract summary: We present AlphaSyndrome, an automated framework for scheduling syndrome-measurement circuits in general commuting-stabilizer codes.<n>Across diverse code families, sizes, and decoders, AlphaSyndrome reduces logical error rates by 80.6% on average.
- Score: 7.373559718519129
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: 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.
Related papers
- Continual Quantum Architecture Search with Tensor-Train Encoding: Theory and Applications to Signal Processing [68.35481158940401]
CL-QAS is a continual quantum architecture search framework.<n>It mitigates challenges of costly encoding amplitude and forgetting in variational quantum circuits.<n>It achieves controllable robustness expressivity, sample-efficient generalization, and smooth convergence without barren plateaus.
arXiv Detail & Related papers (2026-01-10T02:36:03Z) - Unitary fault-tolerant encoding of Pauli states in surface codes [0.8314040122511801]
We present a unitary, scalable, distance-preserving encoding scheme for preparing Pauli eigenstates in surface codes.<n>Our work bridges the gap between measurement-based and unitary encodings of surface-code states.
arXiv Detail & Related papers (2026-01-08T17:00:25Z) - Constraint-Optimal Driven Allocation for Scalable QEC Decoder Scheduling [3.7768601360100647]
Fault-tolerant quantum computing requires fast and accurate decoding of Quantum Error Correction syndromes.<n>In large-scale systems, the number of available decoders is much smaller than the number of logical qubits, leading to a fundamental resource shortage.<n>To address this limitation, Virtualized Quantum Decoder (VQD) architectures have been proposed to share a limited pool of decoders across multiple qubits.
arXiv Detail & Related papers (2025-12-02T09:07:00Z) - A High-Performance List Decoding Algorithm for Surface Codes with Erroneous Syndrome [9.191400697168389]
We propose a high-performance list decoding algorithm for surface codes with erroneous syndromes.
We first use belief propagation (BP) decoding for pre-processing with syndrome soft information, followed by ordered statistics decoding (OSD) for post-processing to list and recover both qubits and syndromes.
arXiv Detail & Related papers (2024-09-11T03:12:18Z) - Transformer-QEC: Quantum Error Correction Code Decoding with
Transferable Transformers [18.116657629047253]
We introduce a transformer-based Quantum Error Correction (QEC) decoder.
It employs self-attention to achieve a global receptive field across all input syndromes.
It incorporates a mixed loss training approach, combining both local physical error and global parity label losses.
arXiv Detail & Related papers (2023-11-27T18:52:25Z) - Testing the Accuracy of Surface Code Decoders [55.616364225463066]
Large-scale, fault-tolerant quantum computations will be enabled by quantum error-correcting codes (QECC)
This work presents the first systematic technique to test the accuracy and effectiveness of different QECC decoding schemes.
arXiv Detail & Related papers (2023-11-21T10:22:08Z) - The END: An Equivariant Neural Decoder for Quantum Error Correction [73.4384623973809]
We introduce a data efficient neural decoder that exploits the symmetries of the problem.
We propose a novel equivariant architecture that achieves state of the art accuracy compared to previous neural decoders.
arXiv Detail & Related papers (2023-04-14T19:46:39Z) - Modular decoding: parallelizable real-time decoding for quantum
computers [55.41644538483948]
Real-time quantum computation will require decoding algorithms capable of extracting logical outcomes from a stream of data generated by noisy quantum hardware.
We propose modular decoding, an approach capable of addressing this challenge with minimal additional communication and without sacrificing decoding accuracy.
We introduce the edge-vertex decomposition, a concrete instance of modular decoding for lattice-surgery style fault-tolerant blocks.
arXiv Detail & Related papers (2023-03-08T19:26:10Z) - Deep Quantum Error Correction [73.54643419792453]
Quantum error correction codes (QECC) are a key component for realizing the potential of quantum computing.
In this work, we efficiently train novel emphend-to-end deep quantum error decoders.
The proposed method demonstrates the power of neural decoders for QECC by achieving state-of-the-art accuracy.
arXiv Detail & Related papers (2023-01-27T08:16:26Z) - Soft Syndrome Decoding of Quantum LDPC Codes for Joint Correction of
Data and Syndrome Errors [10.200716411599831]
Quantum errors are primarily detected and corrected using the measurement of syndrome information.
In this paper, we use this "soft" or analog information without the conventional discretization step.
We demonstrate the advantages of extracting the soft information from the syndrome in our improved decoders.
arXiv Detail & Related papers (2022-05-04T22:00:32Z) - Performance of teleportation-based error correction circuits for bosonic
codes with noisy measurements [58.720142291102135]
We analyze the error-correction capabilities of rotation-symmetric codes using a teleportation-based error-correction circuit.
We find that with the currently achievable measurement efficiencies in microwave optics, bosonic rotation codes undergo a substantial decrease in their break-even potential.
arXiv Detail & Related papers (2021-08-02T16:12:13Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.