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Dithered Belief Propagation for Real-Time Quantum Memory Decoding

We introduce dithered belief-propagation decoding for circuit-level quantum memory to mitigate the oscillations and trapping behavior that limit standard belief-propagation (BP) decoders for qLDPC codes.

By Cai, Jarkas, Zhao +1

Score████░░░░░░4.3

Key numbers

  • 98% fewer multiplications on average

Caveats

  • Preprint; not yet peer reviewed.

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Abstract

We introduce dithered belief-propagation decoding for circuit-level quantum memory to mitigate the oscillations and trapping behavior that limit standard belief-propagation (BP) decoders for qLDPC codes. Our approach combines a quantum-adapted sign-flip mechanism with chained randomized prior perturbation. Evaluated under circuit-level noise on the distance-11 rotated surface code and the distance-12 bivariate-bicycle code, the proposed dithered decoder significantly outperforms BP and BP+OSD+CS-10. The proposed decoder achieves accuracy comparable to or better than state-of-the-art Relay-BP, especially at higher physical error rates, while trading a moderate increase in additions for about 98% fewer multiplications on average and eliminating node-level RNGs. These results suggest that dithering is a promising approach toward real-time decoding of quantum memories.

Zhengyu Cai, Mohamad Ali Jarkas, Bokun Zhao, Warren J. Gross

The editor's rubric

Heuristic review

Leverage3 / 5
A method or resource many groups across the field will adopt within a year.
18% of this desk’s rubric
Magnitude4 / 5
A qualitative jump: a capability or regime that did not exist before.
20% of this desk’s rubric
Evidence3 / 5
Solid: multiple benchmarks or cohorts, ablations, fair baselines, released code or data.
22% of this desk’s rubric
Novelty2 / 5
A new combination of known ideas.
22% of this desk’s rubric
Trajectory2 / 5
Some room to improve with obvious engineering.
10% of this desk’s rubric
Stakes2 / 5
Benefits a professional community (practitioners, clinicians, engineers).
8% of this desk’s rubric

Editor’s rationale

Heuristic triage from title and abstract text only, not a reading of the paper. Cues found: method (we propose); gains (relative gain, state of the art, outperforms); design (randomized).

How the score was computed

rank-2026-10-18

Score████░░░░░░4.3

Score = 10 × (75% × adjusted merit / 10 + 15% × attention + 10% × freshness)

Desks place stronger verdicts first, then use this score to order work within the same verdict.

Merit
5.6 / 10
Weighted rubric, evidence-gated.
Adjusted merit
4.6 / 10
Shrunk toward the desk prior by editor confidence (40%).
Attention
0%
Citations, upvotes, points, mentions.
Freshness
87%
Half-life decay since publication.

No attention signals recorded yet.

The record

  • Reviewed by heuristic-v10 on Nov 6, 2026, 07:29 UTC. Paper type: method.
  • Categories: quant-ph, cs.IT
  • TOP, No.5 in the Physics edition of November 6, 2026.