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Show HN: ZUSE – 69x causal compression of a period-15 CA oscillator

ZUSE Automat Agent v1.11 achieves 69.1x causal compression of a period-15 cellular automaton oscillator, reducing 25 cells over 12 steps to recover defect_state0 in 20/20 trials. The deterministic system discovers empirical laws for elementary cellular automata without language models, using policy-driven world selection and law evaluation.

read2 min views1 publishedJun 29, 2026
Show HN: ZUSE – 69x causal compression of a period-15 CA oscillator
Image: source

Deterministic empirical law discovery for elementary cellular automata (ECA).

ZUSE Automat Agent runs cellular-automata worlds, applies a fixed observer stack, evaluates seven binary cycle laws, and stores multi-seed evidence in reproducible journals. The discovery loop is policy-driven and deterministic: no language model participates in world selection, law evaluation, scoring, or acceptance.

Latest: v1.11 - Early causal-cone compression of the T=15 mechanism: 25 cells for 12 steps recover defect_state0

in 20/20, a 69.1x reduction.

World taxonomy and law coverage matrix: formal classification of 20 worlds, seven-law coverage, and measured fragility where available.Scientific synthesis: consolidated findings across world families, law coverage, fragility mechanisms, and open questions.Physical-tree findings: meta-analysis of physical metrics that predict law richness.Fragility report: basin fragility spectrum and observed mechanisms.Rule 54 noise-gate anatomy: diagnosis of the dedup noise-boundary mechanism.Local oscillator family sweep: exhaustive quiescent ECA sweep;rule_108

is unique under the current local oscillator protocol.Periodicity sweep: designed periodic ICs validateperiodicidad

across ECA.

python -m venv .venv
.\.venv\Scripts\Activate.ps1
pip install -r requirements.txt

Run a simulation:

python -m zaa simulate --rule 110 --steps 200 --width 256 --out outputs\rule110

Run a short deterministic discovery loop:

python -m zaa discover --world rule_110 --cycles 5 --journal journal.jsonl

Run the test suite:

python -m unittest discover -s tests

See REPRODUCIBILITY.md for the commands used to regenerate the atlas, fragility reports, oscillator sweeps, and periodicity results.

Large raw JSONL outputs are not tracked in git when they exceed 1 MB. The corresponding scripts and summary reports are tracked, and the raw files can be regenerated from the commands in the reproducibility guide.

Concha Estrada, M. A. (2026). ZUSE Automat Agent: Empirical Law Discovery in
Elementary Cellular Automata (v1.11). Zenodo.
https://doi.org/10.5281/zenodo.21034813

Code is released under the MIT License. The preprint is distributed under Creative Commons Attribution 4.0 International via Zenodo.

source & further reading
github.com — original article
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