An FPGA-based neural-network decoder achieves 550 ns deterministic closed-loop latency for real-time distance-3 surface code error correction on a superconducting processor, matching offline decoding performance.
M., Serra-Peralta, M., Byfield, D
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PAEMS is a new adaptive qubit error model that reduces timelike, spacelike, and spacetime error correlations by 19.5×, 9.3×, and 5.2× on IBM QPUs while outperforming Google's SI1000 model by 58-73% across multiple platforms.
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Real-time Surface-Code Error Correction Using an FPGA-based Neural-Network Decoder
An FPGA-based neural-network decoder achieves 550 ns deterministic closed-loop latency for real-time distance-3 surface code error correction on a superconducting processor, matching offline decoding performance.
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PAEMS: Precise and Adaptive Error Model for Superconducting Quantum Processors
PAEMS is a new adaptive qubit error model that reduces timelike, spacelike, and spacetime error correlations by 19.5×, 9.3×, and 5.2× on IBM QPUs while outperforming Google's SI1000 model by 58-73% across multiple platforms.