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arXiv AI By Anil Bilgin, Wanda Hou, Pranav Srinivas, Yi-Zhuang You

Distilling Knowledge from Search: Decoder Model Factory for Quantum LDPC Codes

Read the original on arXiv AI →

The paper introduces GraphMP, a learning-based message‑passing decoder for quantum low‑density parity‑check codes that can transfer across different code families, sizes, error rates, and noise models without fine‑tuning. GraphMP employs local message passing for scalability and uses beam search guided by its predictions to iteratively refine error patterns, balancing decoding time against logical error rates. The authors propose a decoder model factory that trains successive models on data generated by earlier models during decoding, enabling knowledge distillation and continuous adaptation to changing noise conditions.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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