Resource estimation for magic-state distillation on silicon spin qubits finds 42% overhead reduction via optimized pulses and ~3x physical footprint reduction with biased codes versus surface code.
Surface-Code Thresholds and Qubit Footprints in Shuttling-Based Spin-Qubit Railways
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abstract
We present a fault-tolerant mapping of rotated surface codes onto a $2\times N$ silicon spin-qubit railway architecture, utilizing electron shuttling to resolve the wiring fan-out bottleneck. Employing circuit-level noise modeling, we evaluate threshold performances across various noise biases. We demonstrate that shuttling check qubits instead of data qubits fundamentally improves system thresholds. Crucially, under a noise model biased towards dephasing for spin-qubit shuttling, the non-CSS XZZX surface code outperforms standard CSS variants. By tailoring the topological code to this specific inherent bias, we show that the Megaquop footprint is achievable with a distance 7 code requiring a $p = 10^{-3}$ physical error rate, highlighting a pathway for substantial hardware reductions in early fault-tolerant quantum processors.
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2026 1verdicts
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Hardware-Tailored Resource Estimation for Magic-State Distillation on Silicon Spin Qubits
Resource estimation for magic-state distillation on silicon spin qubits finds 42% overhead reduction via optimized pulses and ~3x physical footprint reduction with biased codes versus surface code.