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An efficient mapped pseudospectral method for weakly bound states: vibrational states of He<sub>2</sub>, Ne<sub>2</sub>, Ar<sub>2</sub>and Cs<sub>2</sub>

2008· article· en· W2088175309 on OpenAlexafffund
Joseph Lo, Bernie D. Shizgal

Bibliographic record

VenueJournal of Physics B Atomic Molecular and Optical Physics · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEigenfunctionQuadrature (astronomy)DiscretizationBound stateConvergence (economics)Upper and lower boundsMathematicsPseudo-spectral methodMathematical analysisPhysicsQuantum mechanicsOpticsEigenvalues and eigenvectorsFourier transform

Abstract

fetched live from OpenAlex

This paper reports the application of pseudospectral methods to the calculation of the bound states of He2, Ne2, Ar2 and Cs2. The calculation of the uppermost loosely bound states, only one for He2, presents a challenge for most numerical methods. We employ the quadrature discretization method which is a collocation based on quadrature points defined with weight functions that approximate the ground states. A mapping procedure is proposed that greatly improves the convergence of the uppermost states that are very loosely bound and characterized by very diffuse eigenfunctions. Comparisons with the results with other methods and experiment are also carried out wherever possible.

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)0.000
metaresearch head score (Gemma)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.008
GPT teacher head0.246
Teacher spread0.238 · 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

Citations17
Published2008
Admission routes2
Has abstractyes

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