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Record W1966533816 · doi:10.1137/110843137

A Structure-Preserving Curve for Symplectic Pairs and Its Applications

2012· article· en· W1966533816 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSIAM Journal on Matrix Analysis and Applications · 2012
Typearticle
Languageen
FieldComputer Science
TopicMatrix Theory and Algorithms
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMathematicsSymplectic geometryParameterized complexityMonotonic functionNumerical analysisFixed-point iterationConvergence (economics)Newton's methodHermitian matrixPositive-definite matrixMatrix (chemical analysis)Mathematical analysisFixed pointApplied mathematicsEigenvalues and eigenvectorsPure mathematicsCombinatoricsNonlinear system

Abstract

fetched live from OpenAlex

The main purpose of this paper is the study of numerical methods for the maximal solution of the matrix equation $X+A^*X^{-1}A = Q$, where $Q$ is Hermitian positive definite. We construct a smooth curve parameterized by $t\ge 1$ of symplectic pairs with a special structure, in which the curve passes through all iteration points generated by the known numerical methods, including the fixed-point iteration, the structure-preserving doubling algorithm (SDA), and Newton's method provided that $A^*Q^{-1}A=AQ^{-1}A^*$. In the theoretical section, we give a necessary and sufficient condition for the existence of this structure-preserving curve for each parameter $t\ge1$. We also study the monotonicity and boundedness properties of this curve. In the application section, we use this curve to measure the convergence rates of those numerical methods. Numerical results illustrating these solutions are also presented.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.969
Threshold uncertainty score0.609

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.292
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it