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Field notes / Experiment guide

A field guide to the shapes ants leave behind

How different can the visited territories look when the only instruction is a repeating string of left and right turns?

New to these ants? Start here.

An ant moves on a grid of coloured squares. Each colour tells it to turn left (L) or right (R). It advances that square to the next colour, then steps forward. A rule such as RLR is the list of turns, starting at colour zero. On a blank grid the same rule always makes the same trajectory.

Territory means every cell visited so far. Its boundary consists of visited cells with an unvisited neighbour. A highway is a repeating pattern of motion that carries the ant away. A tether means repeated returns to a small home region.

Growing like the cube root of time means taking eight times as many steps to double a linear size. The rotor walker is a comparison model that follows and rotates arrows stored on cells. A seed makes a random starting pattern reproducible; the ant itself can still move deterministically.

We distinguish c, the chance of discovering a cell per boundary step, from kappa (κ), time at the boundary normalized by perimeter divided by area. Explaining their values is harder than using them to account for growth.

A closer look

A gallery comparing the colour patterns and territory shapes produced by different ant rules.
A few instructions can produce very different worlds. This is a selected gallery, not a measure of how often each kind of behaviour occurs; rule labels identify the examples. Figure source and recipe ↗
Saved colour-field snapshot of the symmetric builder LLRR.
LLRR is a reminder that an ant need not build an irregular blob. This selected saved snapshot is visual context; use the generating record for its run parameters rather than inferring a growth exponent from the shape. Figure source and recipe ↗

The idea under test

This is a visual reference collection rather than a separate hypothesis test: selected snapshots let readers connect rule strings with spatial outcomes.

What we learned

The archive preserves examples ranging from compact territories to structured builders, used as context for quantitative studies.

What this leaves open

The examples are selected, not representative frequencies. Shape in a still image cannot certify an eventual growth regime.

Read the evidence and reproduction recipe ↗

Inside the experiment

Methods, registered predictions, exact commands and saved analysis. These are the working research documents; expand them for the detail behind the introduction.

Methods and original experiment record

snapshots

Migrated legacy investigation (2026-10-14). Its files used to sit in the flat data/ directory (and calib/, occ/, snaps/, dumps*, knock* where listed) with the label prefix below; experiments/_migration/map.tsv gives the exact old -> new path of every file. This stub was generated from file names and script docstrings. It is not the original write-up: the question, timestamped hypotheses, commands and results are in notes/ (mainly notes/frontier-results.md, notes/frontier-status.md, notes/research-frontier*.md; search for the label), and the producing command is usually in the script docstring or a run_*.sh here.

Old labels / prefixes: LLRR, RL, RLR, RRLRLLRLRRLR, RRLRLLRRR, RRLRRRRRRLRL, RRRLRLLRRRLR, RRRRLL, RRRRRRRRRRLL, portrait, render

Scripts

  • scripts/portrait.py: portrait.py GRID.bin N OUT.png [MAXPX]: RGBA portrait, colour 0 transparent.
  • scripts/render.py

Results

9 entries in results/ (0 are .log/.done markers); csv/json/txt outputs, *_stats.txt hold the summaries quoted in the notes.

Notebook

No committed Jupyter notebook is available for this experiment yet.

2026-10-13-snapshots · Source revision ba38590b33e3

Original source ↗ · Input hashes

Introductions summarize the evidence; the expandable record preserves the original predictions, methods and caveats. Figures and notebooks are published as saved. Publication runs no simulations or notebook cells.