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Boundary control for inverse Cauchy problems of the Laplace equations

2008· article· en· W3463815 on OpenAlex

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

Bibliographic record

VenueComputer Modeling in Engineering & Sciences · 2008
Typearticle
Languageen
FieldMathematics
TopicNumerical methods in inverse problems
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsTikhonov regularizationCauchy problemCauchy distributionCauchy boundary conditionBoundary value problemBoundary (topology)MathematicsInverse problemInitial value problemApplied mathematicsRegularization (linguistics)Elliptic partial differential equationMathematical analysisComputer sciencePartial differential equationMixed boundary condition

Abstract

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Abstract: The method of fundamental solu-tions is coupled with the boundary control tech-nique to solve the Cauchy problems of theLaplaceEquations. Themainideaoftheproposedmethod is to solve a sequence of direct problemsinsteadofsolvingtheinverse problemdirectly. Inparticular,weusea boundarycontroltechniquetoobtain an approximation of the missing Dirichletboundary data; the Tikhonov regularization tech-nique and the L-curve method are employed toachieve such goal stably. Once the boundarydataon the whole boundary are known, the numericalsolution to the Cauchy problem can be obtainedby solving a direct problem. Numerical exam-plesare providedfor verificationsoftheproposedmethod on the steady-state heat conductionprob-lems. Keyword: Method of fundamental solution,methodofparticularsolution,collocationmethod,Tikhonovregularization,L-curve. 1 Introduction The Cauchy problem for an elliptic equation isa typical ill-posed problem whose solution doesnot depend continuously on the boundary data.That is, a small error in the specified data mayresult in an enormous error in the numerical so-lution. This problem appears in many applica-tions for example in the cardiography, the non-destructive testing, and etc. Stable and efficientnumerical methods are of highimportance. How-ever, it is well-known that the Cauchy problemfor an elliptic equation is ill-posed without any

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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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.421
Threshold uncertainty score0.385

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.140
GPT teacher head0.312
Teacher spread0.172 · 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