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.
A vanishing eigengap allows a fixed eigenvector rotation
Statement refuted
The following uniform claim is false: among all real symmetric matrices with a simple leading eigenvalue, an operator-norm perturbation tending to zero forces the leading eigenvector line to rotate by an angle tending uniformly to zero, without any lower bound on the eigengap.
Witness construction
For every , take The unperturbed leading line is and the gap is . The perturbation norm is , but the perturbed leading line makes the fixed positive angle with , independent of . Thus an absolute perturbation bound alone cannot give uniform eigenspace stability as the gap vanishes.
Facts & Assumptions
Given: A real parameter , the matrices
above, and the false uniform claim stated in ## Statement refuted.
The operator norm is zero on the zero domain and otherwise is max_{||v||=1} ||Tv||: the operator norm is the maximum of over unit vectors.
Local leading-eigenvector stability under a spectral gap: when , the sign-free sine-angle is bounded by .
Refutation
The eigenvalues of are and , so its leading line is and its gap is . Also , whence [F1] gives .
The characteristic polynomial of has roots , so the larger root is the leading eigenvalue. If is its leading eigenvector, the first row of the eigenvalue equation gives . Thus its line makes angle with , independently of .
Letting makes by step 1.1 while the angle in step 1.2 stays fixed and positive, contradicting the proposed uniform claim. Here , so [F2] still applies; its gap-dependent bound is consistent with the example.
Depends on
Used by
Nothing in the library uses this result yet.
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
- Online Bayesian Data Analysis, Lecture Notes 8: Learning Signal Representations (11 April 2016) (standard reference, not scraped)
- Soumendu Sundar Mukherjee, Multivariate Analysis, Lecture 8: Principal Component Analysis (standard reference, not scraped)