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Record W2906266373 · doi:10.1088/1361-6455/aafa4a

Resonant transmission of weakly bound multi-atomic molecules

2018· article· en· W2906266373 on OpenAlexafffund
Mark R. A. Shegelski, George A. Jones, Caleb Sample, Mitchell Hawse, M. Reid

Bibliographic record

VenueJournal of Physics B Atomic Molecular and Optical Physics · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum optics and atomic interactions
Canadian institutionsUniversity of Northern British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsTransmission (telecommunications)MoleculeAtomic physicsMolecular physicsQuantum mechanicsTelecommunications

Abstract

fetched live from OpenAlex

Abstract This article examines resonant tunnelling of multi-atomic systems, extending the body of work on resonant tunnelling in this area beyond diatomic homo-nuclear systems. We consider diatomic molecules with distinct atoms having different masses, and linear triatomic molecules with indistinguishable atoms. The molecule is incident in the bound state upon a step potential with an energy increase of V 0 for each atom. We calculate the probabilities of reflection p R and transmission p T in the bound state and the dependence on the energy of the molecule. We find that, as was the case for the homo-nuclear molecule, resonant transmission for diatomic molecules with distinguishable atoms occurs for arbitrarily weak binding, and p T is close to one for finite binding energy. We also find resonant transmission for linear triatomic molecules. We show results for the time-dependent Schrödinger equation which agree with resonant transmission. We also consider the transmission of an N -atom one-dimensional molecule.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score0.954

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.270
Teacher spread0.260 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations2
Published2018
Admission routes2
Has abstractyes

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