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Hierarchical decoding to reduce hardware requirements for quantum computing
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abstract
Extensive quantum error correction is necessary in order to scale quantum hardware to the regime of practical applications. As a result, a significant amount of decoding hardware is necessary to process the colossal amount of data required to constantly detect and correct errors occurring over the millions of physical qubits driving the computation. The implementation of a recent highly optimized version of Shor's algorithm to factor a 2,048-bits integer would require more 7 TBit/s of bandwidth for the sole purpose of quantum error correction and up to 20,000 decoding units. To reduce the decoding hardware requirements, we propose a fault-tolerant quantum computing architecture based on surface codes with a cheap hard-decision decoder, the lazy decoder, combined with a sophisticated decoding unit that takes care of complex error configurations. Our design drops the decoding hardware requirements by several orders of magnitude assuming that good enough qubits are provided. Given qubits and quantum gates with a physical error rate $p=10^{-4}$, the lazy decoder drops both the bandwidth requirements and the number of decoding units by a factor 50x. Provided very good qubits with error rate $p=10^{-5}$, we obtain a 1,500x reduction in bandwidth and decoding hardware thanks to the lazy decoder. Finally, the lazy decoder can be used as a decoder accelerator. Our simulations show a 10x speed-up of the Union-Find decoder and a 50x speed-up of the Minimum Weight Perfect Matching decoder.
Forward citations
Cited by 6 Pith papers
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Confidence-gated neural decoding escalates only ~3–6% of rotated-surface-code syndromes to MWPM and raises end-to-end accuracy from 99.21% to 99.81% at d=7 under circuit-level depolarising noise.
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LATTE: A Decoding Architecture for Quantum Computing with Temporal and Spatial Scalability
A hybrid FPGA-CPU streaming decoder cuts syndrome transmission by over 90% and keeps feedback latency roughly constant in long surface-code memory runs.
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Enhancing the Clique Local Decoder to Correct Length-2 Space Errors in the Surface Code
A modest extension of the Clique decoder, Clique_L2, corrects length-2 space error chains locally and cuts out-of-fridge decoding bandwidth by up to 18.38x under clustered noise models.
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Synchronization for Fault-Tolerant Quantum Computers
Active and Hybrid synchronization policies cut logical error rates by up to 2.4x and 3.4x compared to passive waiting, by distributing idle time across syndrome generation rounds.
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