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Record W1900062776 · doi:10.1103/physrevc.93.044002

Few-nucleon systems with state-of-the-art chiral nucleon-nucleon forces

2016· article· en· W1900062776 on OpenAlexaff
Sven Binder, Angelo Calci, E. Epelbaum, R. J. Furnstahl, J. Golak, K. Hebeler, H. Kamada, H. Krebs, Joachim Langhammer, S. Liebig, Pieter Maris, Ulf-G. Meißner, D. Minossi, A. Nogga, Hugh Potter, Robert Roth, R. Skibiński, K. W. Topolnicki, James P. Vary, H. Witała

Bibliographic record

VenuePhysical review. C · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear physics research studies
Canadian institutionsTRIUMF
FundersNarodowe Centrum NaukiChinese Academy of SciencesBundesministerium für Bildung und ForschungNational Natural Science Foundation of ChinaDeutsche ForschungsgemeinschaftU.S. Department of EnergyEuropean Research CouncilNational Science Foundation
KeywordsNucleonPhysicsObservableScatteringEffective field theoryOrder (exchange)Particle physicsRange (aeronautics)Truncation (statistics)State (computer science)Nuclear physicsQuantum mechanicsMathematicsStatistics

Abstract

fetched live from OpenAlex

We apply improved nucleon-nucleon potentials up to fifth order in chiral effective field theory, along with a new analysis of the theoretical truncation errors to study nucleon-deuteron $(\mathrm{N}d)$ scattering and selected low-energy observables in $^{3}\mathrm{H},^{4}\mathrm{He}$, and $^{6}\mathrm{Li}$. Calculations beyond second order differ from experiment well outside the range of quantified uncertainties, providing truly unambiguous evidence for missing three-nucleon forces within the employed framework. The sizes of the required three-nucleon-force contributions agree well with expectations based on Weinberg's power counting. We identify the energy range in elastic $\mathrm{N}d$ scattering best suited to study three-nucleon-force effects and estimate the achievable accuracy of theoretical predictions for various observables.

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)0.003
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.300
Teacher spread0.288 · 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

Citations145
Published2016
Admission routes1
Has abstractyes

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