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Record W2048246865 · doi:10.1103/physrevb.87.165136

Variational approach for calculating Auger electron spectra: Going beyond the impurity approximation

2013· article· en· W2048246865 on OpenAlexafffund
Anamitra Mukherjee, G. A. Sawatzky, Mona Berciu

Bibliographic record

VenuePhysical Review B · 2013
Typearticle
Languageen
FieldMaterials Science
TopicCopper-based nanomaterials and applications
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEigenvalues and eigenvectorsImpurityPropagatorVariational methodSpectral lineIonElectronAuger electron spectroscopyPhysicsAugerQuantum mechanicsAtomic physics

Abstract

fetched live from OpenAlex

We propose a variational method to calculate the two-hole propagators relevant for Auger spectroscopy in transition-metal oxides. This method can be thought of as an intermediary step between the full solution (which is difficult to generalize to systems with partially filled bands) and the impurity approximation. Like the former, our solution has full translational invariance, and like the latter, it can be generalized to certain types of systems with partially filled bands. Here we compare both our variational approximation and the impurity approximation against the exact solution for a simple one-dimensional model with filled bands. We show that when the energies of the eigenstates residing primarily on the transition-metal ions do not overlap with those of the eigenstates residing primarily on oxygen ions, both approximations are valid but the variational approach is superior.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
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 head0.015
GPT teacher head0.291
Teacher spread0.276 · 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 designSimulation or modeling
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".

Quick stats

Citations3
Published2013
Admission routes2
Has abstractyes

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