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.
Exact Gaussian randomized range finder
Definition
Input a fixed matrix , a positive integer sketch width , and a Gaussian draw primitive as in Standard real and normalized complex Gaussian matrix laws. Draw with iid entries in the chosen field and form . Select deterministically by scanning columns of in order, subtracting projections onto already retained columns, skipping zero residuals, and normalizing each nonzero residual. In the complex case fix each phase by making its first nonzero coordinate positive real. Return this orthonormal basis and the approximation .
Empty ranges return the empty basis. All operations use exact arithmetic. No truncated rank- factorization, finite-precision stability result, or deterministic error certificate is part of the procedure.
Depends on
Used by
- Reorthogonalized randomized power subspace iteration Algorithm
- Exact range recovery on a rank-k matrix Example
- Borel measurability and range correctness of the finite scan Lemma
- Deterministic SVD-partition error bound for the range finder Lemma
- Direct expected spectral bound for the normalized complex range finder Lemma
- Expected spectral error for real and normalized complex Gaussian range finders Theorem
- Expected spectral error of the real Gaussian range finder Theorem
Dependency tree · two levels
7 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
- Halko, Martinsson, and Tropp, Finding Structure with Randomness, Algorithm 4.1 (standard reference, not scraped)
- Martinsson and Tropp, Randomized Numerical Linear Algebra: Foundations & Algorithms, §11.1.1 (standard reference, not scraped)