Causal Forge

One event. Its value is how much of the diffusing quantity starts there — think of it as how much dye you pour in at that point before the simulation runs.

Try — Drag a node far away from its neighbours and re-run. Nothing moves on the panel — distance on screen is not distance in the model.

A one-way link: this event can influence that one, and not the other way round. The arrow is the causal direction.

Try — Reverse one edge and re-run. Only causal consistency can react — that tells you exactly which part of the score is about causality and which part is about shape.

How strongly two events are coupled. A heavier edge lets the quantity flow faster between its endpoints.

Try — Raise one weight sharply with Auto α off, then re-run. Stability falls without you touching α — the safe step size depends on the weights, not just the wiring.

Turns one event into two that share its value and its connections. A way to make the structure finer without changing what it is connected to.

Try — Split a hub node and watch locality move. Refinement changes the triangle count, so a structure that was "the same idea" scores differently — worth knowing before you trust a locality reading.

Collapses two events into one, adding their values and joining their connections. Useful for asking whether the big picture survives when you stop resolving fine detail.

Try — Merge two nodes and compare the metrics before and after. A reading that survives coarse-graining is a much stronger result than one that does not — that comparison is the closest thing this module has to a physics argument.

You are allowed to connect an event back to one of its own causes. The simulation will still run — and causal consistency will fall, because an event has become its own ancestor.

Try — Close a loop on purpose and watch causal consistency drop. It is the only metric you can drive to zero deliberately, and doing it once is the fastest way to see what the score is actually measuring.