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Electron Plasmas Cooled by Cyclotron-Cavity Resonance

2016· article· en· W2510813735 on OpenAlexafffund
A. Povilus, N. D. DeTal, L. T. Evans, N. Evetts, J. Fajans, W. N. Hardy, E. D. Hunter, Isaac Martens, F. Robicheaux, Sabrina Shanman, C. So, Xiao Wang, J. S. Wurtele

Bibliographic record

VenuePhysical Review Letters · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaLawrence Livermore National LaboratoryU.S. Department of EnergyNational Science Foundation
KeywordsAtomic physicsCyclotronPlasmaElectron cyclotron resonanceElectronCyclotron resonancePhysicsElectromagnetic electron waveTrappingIon cyclotron resonanceMagnetic fieldElectron coolingElectron temperaturePenning trapResonance (particle physics)Waves in plasmasNuclear physics

Abstract

fetched live from OpenAlex

We observe that high-Q electromagnetic cavity resonances increase the cyclotron cooling rate of pure electron plasmas held in a Penning-Malmberg trap when the electron cyclotron frequency, controlled by tuning the magnetic field, matches the frequency of standing wave modes in the cavity. For certain modes and trapping configurations, this can increase the cooling rate by factors of 10 or more. In this Letter, we investigate the variation of the cooling rate and equilibrium plasma temperatures over a wide range of parameters, including the plasma density, plasma position, electron number, and magnetic field.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.603
Threshold uncertainty score0.692

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.005
GPT teacher head0.253
Teacher spread0.248 · 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 designNot applicable
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

Citations8
Published2016
Admission routes2
Has abstractyes

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