Field notes / Experiment guide
Do other tethered ants have the same weak spots?
The first sensitive-patch maps concern only two rules. Do similar small hot regions appear in other tethered ants?
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.
The idea under test
A small fraction of territory should carry disproportionate sensitivity in additional rules.
What we learned
Several additional maps show small hot regions, but two tight-tether rules have no meaningful hot spots under this test.
What this leaves open
The exceptions matter: localized fragility is not a necessary feature of every tether.
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
e5-more-knockout-maps
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: dumps, e5, knock, run
Scripts
scripts/e5_map.py: E5: knockout coarse map (E1 script plus a tile-origin offset env OFFX/OFFY) (same protocol as knockout.py coarse: every 5x5 tile with >= 5 visited cells,scripts/e5_select.py: E5 rule selection: tethered rules (all rules of experiments/2026-10-13-tether-rules/results/tether_screen.csv) from spread clusters (2% gap, as spread_clusters.scripts/e5_stats.py: E5: knockout maps on more tethered rules and a shifted tile origin. Inputs experiments/2026-10-13-e5-more-knockout-maps/knock_e5/*/{base.csv,coarse.csv} (+ thescripts/run_e5.sh: E5: knockout maps on 6 more tethered rules (experiments/2026-10-13-e5-more-knockout-maps/results/e5_rules.txt, 2^24 dumps) + RRRRRLLLLLL with the tile origin sh
Results
4 entries in results/ (2 are .log/.done markers); csv/json/txt outputs, *_stats.txt hold the summaries quoted in the notes.
Bulk output (gitignored)
dumps_e5/knock_e5/
Notebook
No committed Jupyter notebook is available for this experiment yet.