Alphabeta Math
AlgorithmAlgorithm: Literature-sourcedProof: Not applicablePipeline-generated
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.

Population PC causal-discovery algorithm

Definition

Input: A finite vertex set V, a perfect conditional-independence oracle for a law in the causally sufficient discovery regime, and a fixed total order of V. For every adjacent pair and conditioning set S tested below, the oracle returns whether Xi and Xj are conditionally independent given XS.

Output: An undirected skeleton C, a separator record Sep⁡(i,j) for each deleted edge, and a partially directed graph P.

  1. Initialize C to the complete undirected graph on V and set the level ℓ=0.

  2. In the fixed lexicographic order of unordered vertex pairs, process each pair i−j that is still an edge of C. First test every ℓ-element subset of Adj⁡C(i)∖{j} in lexicographic order; then test every ℓ-element subset of Adj⁡C(j)∖{i} in lexicographic order. On the first oracle result of conditional independence given a tested set S, delete i−j, record Sep⁡(i,j)=Sep⁡(j,i)=S, and do not test that pair again. If no set separates the pair, leave it adjacent. Adjacency sets are read from the current graph, including deletions already made at level ℓ.

  3. If at least one remaining edge has an endpoint with at least ℓ+1 neighbors other than the other endpoint, increment ℓ and repeat step 2. Otherwise stop the skeleton search.

  4. Copy the completed skeleton C to a separate graph P. For each unshielded triple i−k−j in C, orient its incident edges in P as i→k←j exactly when k∉Sep⁡(i,j), retaining any orientations already made. Keep C unchanged.

  5. Repeatedly orient edges of P to closure under the following background-free rules, using fixed lexicographic order on rule instances:

    • R1: If i→j−k and i,k are nonadjacent, orient j−k as j→k.
    • R2: If i−j is undirected and i→k→j, orient i−j as i→j.
    • R3: If i−j, i−k, and i−ℓ are undirected, k→j, ℓ→j, and k,ℓ are nonadjacent, orient i−j as i→j.

Do not apply a background-knowledge rule. Return C, the separator record, and P.

Depends on

Used by

Dependency tree · two levels

11 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