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Papers
Two preprints on Zenodo. The DOI opens the full text.
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Preprint · Zenodo · 16 June 2026
Circuit-level equivariance is code-dependent: obstruction in the surface code, exactness in the honeycomb Floquet code, and consequences for neural decoders
Whether exact (twisted) equivariance survives at circuit level depends on the code. It is obstructed for surface-code extraction circuits and exact for the honeycomb Floquet code, whose C3 rotation mixes the logical qubits. Tying that symmetry into the decoder flips the honeycomb task from unlearnable to learned.
DOI10.5281/zenodo.20715320Read the preprint -
Preprint · Zenodo · 27 July 2026
The lattice's teeth: primitive reciprocal axes govern which Fourier components neural cellular automata can grow
Neural cellular automata are trained on square grids by default; this paper treats the lattice as an experimental variable. An apparent advantage of hexagonal over square grids turned out to be a normalisation artefact in cross-lattice comparisons, and the paper documents and retracts it. The second result is a primitive-axis rule: a trained NCA grows only the Fourier components whose wavevectors lie on a primitive reciprocal-lattice axis of its grid. A pre-registered out-of-sample test partially refuted that rule as stated. What survives is the gate itself: growth stays direction-selective and no geometry-forbidden component grows, so the constraint is real and soft, not sharp.
DOI10.5281/zenodo.21614035Read the preprint