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Record W3214931871 · doi:10.1063/5.0063755

Adiabatic invariant of a charged particle moving in a magnetic field with a constant gradient

2021· article· en· W3214931871 on OpenAlexafffund
К. Кабин

Bibliographic record

VenuePhysics of Plasmas · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsRoyal Military College of Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAdiabatic invariantPhysicsAdiabatic processMagnetic fieldInvariant (physics)Classical mechanicsCharged particleMagnetosphere particle motionQuantum electrodynamicsQuantum mechanicsIon

Abstract

fetched live from OpenAlex

This paper presents the calculation of the adiabatic invariant for the motion of a charged particle in a two-dimensional magnetic field with a constant gradient. Magnetic field intensity is equal to zero along the neutral line for this field model. The mathematical expression for the invariant depends upon whether the particle crosses the neutral line. For trajectories that do not cross the neutral line, the adiabatic invariant reduces to the familiar expression for the magnetic moment, μ0=v2/B, for small values of the magnetic field gradient. The two expressions for the adiabatic invariant can be matched continuously across the change in the type of trajectory. When the magnetic field parameters smoothly change in time, the adiabatic invariant is conserved exponentially well as long as the type of the particle trajectory remains the same. If, however, the trajectory of a particle initially crosses the neutral line but after the magnetic field evolution stops crossing it (or vice versa), the adiabatic invariant is not conserved.

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 categoriesInsufficient payload (model declined to judge)
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 score0.615
Threshold uncertainty score0.990

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)0.0110.000

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 head0.013
GPT teacher head0.230
Teacher spread0.217 · 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.

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

Citations6
Published2021
Admission routes2
Has abstractyes

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