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Record W1970066640 · doi:10.1103/physreva.77.032702

Tunneling of a diatomic molecule with unbound states in one dimension

2008· article· en· W1970066640 on OpenAlexafffund
Mark R. A. Shegelski, Jeff Hnybida, H. Friesen, Crystal Lind, Jeremy J. Kavka

Bibliographic record

VenuePhysical Review A · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsUniversity of Northern British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDiatomic moleculePhysicsHomonuclear moleculeBound stateQuantum tunnellingReflection (computer programming)Rectangular potential barrierAtomic physicsMoleculeAmplitudeTransmission (telecommunications)Quantum mechanicsMolecular physics

Abstract

fetched live from OpenAlex

We study the reflection and transmission of a homonuclear diatomic molecule incident upon a potential barrier in one dimension. The effect of discrete and continuous unbound molecular states is investigated. We use the method of variable reflection and transmission amplitudes for discrete unbound states and we extend the method to include continuous unbound states. We take into account transitions between the bound and unbound states in the process of tunneling. For the molecule incident in a bound state, we calculate the probabilities of reflection and transmission in bound states as well as in unbound states. We focus on the molecule incident upon a $\ensuremath{\delta}$ barrier but we also investigate rectangular and Gaussian barriers. We show that transmission resonances are appreciably reduced by the inclusion of unbound states due to the lack of resonant structure in the probabilities of reflection and transmission in unbound states. We also find that much of the behavior of the molecule in the process of tunneling is primarily due to the bound states.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0020.000

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 head0.018
GPT teacher head0.288
Teacher spread0.270 · 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 designTheoretical or conceptual
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

Citations14
Published2008
Admission routes2
Has abstractyes

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