Alphabeta Math
LemmaStatement: Literature-sourcedProof: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-09-12
How statement and proof provenance work

The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.

  • Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
  • AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
  • AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.

These labels describe origin, not correctness: citations and verification chips remain separate evidence.

The bounded reachability recursion uses logarithmic recursion depth

Statement

Let G be a finite digraph with N1 vertices, numbered by {0,,N1}. To decide whether a directed path exists from u to v, it is enough to evaluate ReachiG(u,v) with i=0 when N=1 and i=log2(N1) when N2. This recursion has depth at most i+1=O(logN), each stack frame stores O(logN) bits, and the whole deterministic search therefore uses O(log2N) space. In particular, if N2cs(n) for some constant c, then the search uses O(s(n)2) space.

Facts & Assumptions

Given: a finite digraph G with N1 numbered vertices.

[L1]

ReachiG(u,v) is intended to decide existence of a path of length at most 2i, and its recursive definition decreases i by one at each call (The bounded reachability recursion for directed paths of length at most 2^i).

[L2]

A space-s(n) machine has at most 2O(s(n)) configurations (A machine using space s(n) has at most exponentially many configurations).

Proof

technique · direct
1.1

If N=1, the only possible path question is settled by Reach0G. Suppose now that N2. Any directed path with repeated vertices can be shortened by deleting a directed cycle, so if u reaches v at all then u reaches v by a simple directed path. A simple directed path in an N-vertex digraph has length at most N1, and 2log2(N1)N1.

L1givenalgebra
2.1

By [L1], every recursive call decreases the index i by one, so starting from that initial i yields recursion depth at most i+1=O(logN).

L1step 1.1
3.1

One stack frame stores the current vertices u, v, a midpoint candidate z, and the current index i. Each of these numbers is below max(N,i+1), so one frame uses O(logN) bits. Multiplying by the depth from step 2.1 gives total space O(log2N).

step 2.1algebra
4.1

If N2cs(n), then logNcs(n), and step 3.1 becomes O(s(n)2). The last sentence follows; [L2] records exactly the configuration bound that supplies such an N in Savitch's theorem.

L2step 3.1algebra

Depends on

Used by

Dependency tree · two levels

5 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.

Sources