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Belief propagation as a partial decoder
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abstract
One of the fundamental challenges in enabling fault-tolerant quantum computation is realising fast enough quantum decoders. We present a new two-stage decoder that accelerates the decoding cycle and boosts accuracy. In the first stage, a partial decoder based on belief propagation is used to correct errors that occurred with high probability. In the second stage, a conventional decoder corrects any remaining errors. We study the performance of our two-stage decoder with simulations using the surface code under circuit-level noise. When the conventional decoder is minimum-weight perfect matching, adding the partial decoder decreases bandwidth requirements, increases speed and improves logical accuracy. Specifically, we observe partial decoding consistently speeds up the minimum-weight perfect matching stage by between $2$x-$4$x on average depending on the parameter regime, and raises the threshold from $0.94\%$ to $1.02\%$.
Forward citations
Cited by 2 Pith papers
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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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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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