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AI Architecture › Quantum for Fusion
Quantum for Fusion

Surface-Code Error Correction

Fault tolerance is the gate to real fusion-materials simulation; the surface code shows how many physical qubits one logical qubit costs.

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From physical to logical qubits

Every credible fusion-materials advantage, phase estimation, qubitization, requires deep circuits that noise would destroy. Quantum error correction (QEC) encodes one reliable logical qubit into many noisy physical qubits, detecting and correcting errors faster than they accumulate. The surface code is the leading candidate because it tolerates relatively high physical error and needs only nearest-neighbor connectivity.

text
# Surface code, distance d:
physical qubits per logical qubit  ~  2 d^2
corrects any error pattern of weight < d/2
logical error rate  ~  A * ( p / p_th )^{ (d+1)/2 }
#   p    = physical gate error,  p_th ~ 1e-2 threshold
#   need p < p_th, then increase d to drive logical error down

The threshold condition

QEC only helps if the physical error rate p is below the code threshold p_th (about 1% for the surface code). Below threshold, increasing the code distance d suppresses logical errors exponentially; above it, adding qubits makes things worse. Today's best hardware sits near this threshold, which is why fault tolerance is emerging but not yet at scale.

The cost that shapes the timeline

text
# to reach logical error ~1e-10 with p/p_th ~ 0.1 -> d ~ 15-20
# => ~500-800 physical qubits per logical qubit, plus distillation
# a first-wall QPE run needs ~10^2-10^3 logical qubits (see estimates)

This is the hard boundary between what quantum can do now and what it could eventually do for Kronos. It is the reason our materials use cases are framed as long-term. The concrete counts for a first-wall problem are on the resource-estimation page; the bridge from noisy runs today is error mitigation.

Content reviewed August 2026 · design-and-simulation stage