Mitigating Classical Resource Costs in Quantum Error Correction via Generalized qLDPC Predecoding

Abstract

Large-scale fault-tolerant quantum computing (FTQC) will require quantum-classical interfaces (QCIs) that orchestrate real-time decoding over thousands to millions of logical qubits simultaneously. To scale FTQC systems, complex decoding resources must be shared between logical qubits, creating resource contention bottlenecks in the QCI. Mitigating this contention via optimal resource allocation remains an open problem. Lightweight predecoding techniques can reduce decoder utilization and average latency, both of which ease contention for shared decoding resources. To date, both decoder allocation and predecoding work is limited to the surface code. As focus shifts towards general qLDPC codes, slower decoding exacerbates resource contention, while code complexity precludes manual predecoder design. To address this gap, we introduce an automated framework designed to generate predecoders for arbitrary qLDPC codes. By independently handling up to 99.98% of the decoding workload, these predecoders reduce decoder utilization up to 4,090$\times$, including up to 81.19% decrease in expensive OSD post-processing and 59.96% decrease in extra RelayBP legs. An efficient, pipelined hardware architecture enables simultaneous decoding of ~1,800 BB code logical qubits on a single FPGA, while cryogenic ASIC implementation supports ~50,000-500,000 BB code logical qubits within a 1.5 W power budget at 4 K.