WARP Graphs: Computational Holography & Provenance Payloads

We formalise computational holography: for a deterministic computation, the full interior derivation volume is recoverable from a compact boundary representation.

For deterministic WARP worldlines, we take the boundary to be an initial state together with a provenance payload, an ordered sequence of tick patches that deterministically advance the state tick by tick.

We define the induced provenance graph, prove backward provenance completeness, and show that the boundary encoding consisting of an initial state and its payload uniquely reconstructs the interior computation (up to isomorphism).

We introduce the Boundary Transition Record (BTR) as a concrete, tamper-evident packaging format for boundary data.

We then develop slicing, which materialises only the causal cone required for a target value, and prefix forks, which support Git-style branching of worldlines under content-addressed storage.

Finally, we introduce wormholes: single edges that compress multi-tick segments while preserving full provenance.