Covariant quantum error correction in a three-layer quantum brain model: computational analysis of layer-specific coherence dynamics
Hikaru Wakaura

TL;DR
This study evaluates covariant quantum error correction in a three-layer quantum brain model, demonstrating its potential to preserve coherence in certain proteins over behaviorally relevant timescales.
Contribution
It provides a quantitative analysis of CQEC's effectiveness in maintaining quantum coherence in protein-based quantum brain models, highlighting layer-specific tradeoffs.
Findings
CQEC maintains high coherence in CRY protein at realistic veto rates.
Coherence collapses in MAO-A protein under higher decoherence rates.
Layer-protein tradeoffs influence the effectiveness of quantum error correction.
Abstract
Quantum brain proposals require coherence on behaviorally relevant timescales, yet the gap between spin coherence times and neural decision windows has remained a quantitative obstacle. We evaluate approximate covariant quantum error correction (CQEC) -- a purification protocol constrained by the Eastin-Knill theorem -- across two radical-pair proteins parameterized by \textit{ab initio} spin Hamiltonians: monoamine oxidase~A (MAO-A) and cryptochrome (CRY, PDB~4I6G). Both share a three-layer architecture (P nuclear spin memory, electron spin interface, classical electrochemistry) and identical hyperfine coupling (~MHz), but differ 16-fold in nuclear : 3.2~ms (MAO-A) versus 52~ms (CRY). We test whether CQEC preserves coherence over the 200~ms Schultze-Kraft veto window by mapping each protein's gap onto a simulation decoherence rate ($\gamma_\mathrm{veto} =…
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