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Record W2342257878 · doi:10.1103/physrevc.94.034317

Electric dipole polarizability from first principles calculations

2016· article· en· W2342257878 on OpenAlexafffund
Mirko Miorelli, Sonia Bacca, Nir Barnea, G. Hagen, G. R. Jansen, Giuseppina Orlandini, T. Papenbrock

Bibliographic record

VenuePhysical review. C · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear physics research studies
Canadian institutionsUniversity of ManitobaUniversity of British ColumbiaTRIUMF
FundersNuclear PhysicsNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaOffice of ScienceTRIUMFMinistero dell’Istruzione, dell’Università e della RicercaUniversity of TennesseeOak Ridge National LaboratoryPAZY FoundationUnited States - Israel Binational Science FoundationU.S. Department of Energy
KeywordsPolarizabilityDipolePhysicsBond dipole momentElectric fieldAtomic physicsRADIUSElectric dipole momentCharge radiusScatteringElectric dipole transitionObservableProtonQuantum electrodynamicsMagnetic dipoleQuantum mechanics

Abstract

fetched live from OpenAlex

The electric dipole polarizability quantifies the low-energy behavior of the dipole strength and is related to critical observables such as the radii of the proton and neutron distributions. Its computation is challenging because most of the dipole strength lies in the scattering continuum. In this paper we combine integral transforms with the coupled-cluster method and compute the dipole polarizability using bound-state techniques. Employing different interactions from chiral effective field theory, we confirm the strong correlation between the dipole polarizability and the charge radius, and study its dependence on three-nucleon forces. We find good agreement with data for the $^{4}\mathrm{He},\phantom{\rule{0.16em}{0ex}}^{40}\mathrm{Ca}$, and $^{16}\mathrm{O}$ nuclei, and predict the dipole polarizability for the rare nucleus $^{22}\mathrm{O}$.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0040.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0130.003

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 head0.028
GPT teacher head0.340
Teacher spread0.312 · 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

Citations65
Published2016
Admission routes2
Has abstractyes

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