arXiv Machine Learning By Ran Miao, Rui Luo, Xiaohan Shan, Xiaoming Sun

QAdapt: A Noise-Adaptive Neural Pre-Decoding Framework for Quantum Error Correction

Read the original on arXiv Machine Learning →

arXiv:2607. 28422v1 Announce Type: new Abstract: Fault-tolerant quantum computing (FTQC) relies on quantum error correction to suppress physical errors and preserve logical information at scale.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv AI
Jul 14

MDQEC-QAS: Meta-Decoding for Quantum Error Correction with Hardware-Aware VQC Search and Confidence-Gated Recovery

arXiv:2607. 10707v1 Announce Type: cross Abstract: We propose a unified meta-decoding framework for quantum error correction that learns syndrome-to-recovery mappings across multiple stabilizer codes and noise settings, without requiring separate decoders for each configuration.

By Prashant Kumar Choudhary, Nouhaila Innan, Muhammad Shafique, Rajeev Singh