Maintains an exact min-cut over the live mesh coupling graph — nodes are
sensing nodes, coupling is the product of fusion attention weights — and
surfaces per cycle, as TrustedOutput::mesh:
- cut value: the global "how close is the array to partitioning" number,
a structural measure per-node heuristics miss;
- weak side: which specific nodes would split off (failure/jamming triage,
feeds ADR-032 posture);
- at-risk flag: counts as a structural event for the drift->recalibration
advisor (alongside ADR-142 change-points).
Degenerate cases fail toward risk: a node with zero coupling is reported as
already partitioned (cut 0, that node as the weak side).
Measured cost policy (criterion, 12-node mesh — the honest part):
- weights quantized (1/64) + change-gated: steady-state cycles do ZERO graph
work and reuse the cached cut (~7.3 us, ~23x cheaper than building);
- on any real change a full exact rebuild (~171 us) is used, because ONE
DynamicMinCut delete+insert measured ~240 us — the subpolynomial machinery
amortizes on much larger graphs, so rebuild-on-change is the measured
optimum at mesh scale (one-edge case -28% after switching policy);
- full process_cycle with the guard: ~33 us for 4 nodes vs the 50 ms budget.
9 mesh_guard tests (weak-node detection, steady-state zero updates,
sub-quantum gating, join/drop rebuild, determinism, disconnection) + an
engine-level wiring test (down-weighted node -> weak side -> recalibration).
Engine 24 tests; workspace gate 2,946 passed / 0 failed.
https://claude.ai/code/session_01MjBucx95K4BuUxZi8NWwRH
Claude