# Level Resolution Experiments Computational investigation of a structural proof strategy for the four color theorem via *level resolutions* of maximal planar graphs. See `paper.tex` for full definitions, conjectures, and findings. ## Files ### Core library - `level_cycles.py` — levels, level subgraphs, level cycles, resolution enumeration (used by old-definition coverage). - `triangulation_gen.py` — vertex-insertion + flip closure (good to n=10). - `triangulation_gen_fast.py` — WL-hash pre-filter for n ≥ 11. - `balanced_layout.py` — Tutte-init random-search planar layout. - `four_color.py` — level 4-coloring via parity 2-coloring of L_k. ### Experiments - `coverage_new_def.py` — **coverage under the cleaner definition**: G' is a level resolution of G via S iff its parity subgraphs are bipartite. Reachability reduces to "G' admits a bipartite 2-partition with cardinality matching some BFS-realizable parity split." - `coverage.py`, `coverage_fast.py`, `coverage_chunked.py` — coverage under the OLD (stricter) definition involving specific edge flips on level cycles. - `face_counting.py` — per-target preimage counts (N_iso, N_paths) under the old definition. - `orbit_check.py` — orbit-counting with k-flip reverse-preimages (used for old-definition icosahedron analysis). ### Visualizations - `plot_oct.py`, `n7_examples.py`, `four_color_viz.py`. ## Summary under the new definition | n | iso-classes | reachable | md4 reachable | |----|-------------|-----------|---------------| | 6 | 2 | 2 | 1/1 | | 7 | 5 | 5 | 1/1 | | 8 | 14 | 14 | 2/2 | | 9 | 50 | 50 | 5/5 | | 10 | 233 | 233 | 12/12 | | 11 | 1249 | 1249 | 34/34 | | 12 | icosahedron | reachable | yes | **Every iso-class is reachable** at every tested size. The previously "uncovered" classes T1 (n=7) and T6 (n=8) under the old definition are both reachable under the cleaner definition. The new definition makes coverage equivalent to 4CT plus a BFS-realizable partition cardinality constraint, raising the question of what additional structure on the preimage G would make the framework non-circular. ## Dependencies ``` pip install networkx matplotlib numpy scipy ```