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On use of inhomogeneous media for elimination of inverse problem ill-posedness

2013· article· en· W2063437631 on OpenAlex

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

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMathematics
TopicNumerical methods in inverse problems
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsInverse problemWell-posed problemInverseComputer scienceApplied mathematicsMathematical optimizationMathematicsMathematical analysisGeometry

Abstract

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Summary form only given. In our previous work (Okhmatovski, et al., IEEE TAP vol. 60, no. 5, 2012) we demonstrated that the ill-posedness of the inverse problem can be eliminated, if the problem of object reconstruction is staged in the medium exhibiting focusing properties and the scattered field is collected in properly defined locations. The desired focusing properties of the media can be realized using either conventional lenses, mirrors, and antenna arrays or novel materials supporting propagation of the evanescent waves. In this work we utilize Luneburg lens (Henry Jasik, “The Electromagnetic Theory of the Luneburg Lens”, 1954) as an example in which focusing properties required for making inverse problem well-posed are realized through inhomogeneity of the media. The lens is responsible in converting the spherically emitted waves of the contrast sources into plane waves. As a result, the waves emitted by different regions of the contrast source are concentrated at different regions of observation. Observing the scattered field at these regions casts the inverse problem into a well-posed form. We prove the concept numerically by reconstructing material properties of a thin layer conformal to the surface of the Luneburg lens. In the experiment we immersed the object of interest in a background dielectric of relative permittivity of 24. We then take inhomogeneous permittivity of the Luneburg lens appropriately increasing to the value of 48 at its center. In the inverse problem formulation the inhomogeneity of the Luneburg lens and the homogeneous medium of permittivity 24 are treated as the background medium described by Green's function. The latter is easily computable with use of a direct solver (e.g. Richmond, IEEE TAP vol. 13, no. 3, 1965). The focusing properties of the background medium Green's function cast the inverse source problem into a well-posed form allowing for its direct inversion with respect to the unknown distribution of the contrast sources in the thin object conformal to the lens. The permittivity contrast of the object is subsequently obtained from the found contrast source using volumetric equivalence principle.

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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)0.000
metaresearch head score (Gemma)0.005
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 score0.474
Threshold uncertainty score0.578

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
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 science0.0000.000
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 head0.141
GPT teacher head0.342
Teacher spread0.201 · 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

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Citations0
Published2013
Admission routes1
Has abstractyes

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