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Record W4388302368 · doi:10.1002/mana.202300185

On singular limits of finite Hilbert transform operators on multi‐intervals

2023· article· en· W4388302368 on OpenAlexafffund
M. Bertola, Elliot Blackstone, Andrei Katsevich, A. Tovbis

Bibliographic record

VenueMathematische Nachrichten · 2023
Typearticle
Languageen
FieldMathematics
TopicMathematical functions and polynomials
Canadian institutionsConcordia University
FundersEuropean Research CouncilNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsMathematicsMathematical analysisEigenfunctionOperator (biology)Method of steepest descentPure mathematicsEigenvalues and eigenvectors

Abstract

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Abstract In this paper, we study the small‐ spectral asymptotics of an integral operator defined on two multi‐intervals and , when the multi‐intervals touch each other (but their interiors are disjoint). The operator is closely related to the multi‐interval finite Hilbert transform (FHT). This case can be viewed as a singular limit of self‐adjoint Hilbert–Schmidt integral operators with so‐called integrable kernels, where the limiting operator is still bounded, but has a continuous spectral component. The regular case when , and is of the Hilbert–Schmidt class, was studied in an earlier paper by the authors. The main assumption in this paper is that is a single interval (although part of our analysis is valid in a more general situation). We show that the eigenvalues of , if they exist, do not accumulate at . Combined with the results in an earlier paper by the authors, this implies that , the subspace of discontinuity (the span of all eigenfunctions) of , is finite dimensional and consists of functions that are smooth in the interiors of and . We also obtain an approximation to the kernel of the unitary transformation that diagonalizes , and obtain a precise estimate of the exponential instability of inverting . Our work is based on the method of Riemann–Hilbert problem and the nonlinear steepest descent method of Deift and Zhou.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.004
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.079
GPT teacher head0.333
Teacher spread0.254 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2023
Admission routes2
Has abstractyes

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