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On the evolution of the phase-space distributions of a non-spherical molecular ultracold plasma in a supersonic beam

2016· article· en· W2522852976 on OpenAlexafffund
Markus Schulz-Weiling, H. Sadeghi, Jachin Hung, Edward R. Grant

Bibliographic record

VenueJournal of Physics B Atomic Molecular and Optical Physics · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsUniversity of British Columbia
FundersAir Force Office of Scientific ResearchNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsPhysicsAtomic physicsSupersonic speedPlasmaRydberg formulaPhase spaceExcited stateJet (fluid)Beam (structure)Ambipolar diffusionExcitationMolecular beamVolume (thermodynamics)LaserOpticsMechanicsIonizationQuantum mechanicsIonMolecule

Abstract

fetched live from OpenAlex

This paper offers a toolbox for characterizing the initial conditions and predicting the evolution of the ultracold plasma that forms after resonant laser preparation of a Rydberg gas entrained in a differentially pumped supersonic molecular beam. The conditions afforded by a skimmed free-jet expansion combined with the geometry of laser excitation, determines the phase-space volume of the excited gas. A hydrodynamic shell model, that accounts for the ellipsoidal spatial distribution of this excitation volume in concert with the deforming effects of dissociative recombination, serves to simulate the ambipolar expansion of this molecular ultracold plasma.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
Threshold uncertainty score0.613

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.005
GPT teacher head0.228
Teacher spread0.223 · 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

Citations16
Published2016
Admission routes2
Has abstractyes

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