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.
An explicit rational envelope for the scaled Householder QR error
Statement
Let , , and let be the local scaled-Householder coefficient of The scaled computed Householder step satisfies the local backward error premise at active row dimension . Set If , then Thus the QR backward-error factor can be bounded by the stated rational dimension-dependent expression in this precision range.
Facts & Assumptions
Given: Integers , , and .
For active row dimension , the local constants are The scaled computed Householder step satisfies the local backward error premise
Proof
Given: The hypotheses in the Statement.
Put . The precision hypothesis gives and . Since , set . The power series gives and, for , . Therefore Also , so Hence the first branch in [F1] satisfies .
Bernoulli's inequality gives ; for integer , this follows by induction from . Since and , by expansion, and because . Thus As and , the last expression minus is at most . Consequently and . Both branches in [F1] are therefore bounded by , so .
Put and . Step 1.2 gives . Since and by the same power-series estimate as in step 1.1, This proves the stated rational envelope.
Depends on
Used by
Dependency tree · two levels
8 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
- Kevin S. Tracy, A Square-Root Kalman Filter Using Only QR Decompositions (standard reference, not scraped)
- M. A. Salzmann, Some Aspects of Kalman Filtering, Technical Report 140 (standard reference, not scraped)