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Record W1668590717 · doi:10.1109/plasma.2002.1030609

Fermi accelerated particles: orbit analysis for the chaotic behavior of the magnetic field lines

2003· article· en· W1668590717 on OpenAlexaff
C. Ciubotariu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum chaos and dynamical systems
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPhysicsMagnetic fieldElectron cyclotron resonanceCyclotron resonanceMagnetosphere particle motionField lineComputational physicsFermi accelerationClassical mechanicsCyclotronCondensed matter physicsQuantum mechanicsParticle acceleration

Abstract

fetched live from OpenAlex

Summary form only given, as follows. The "magnetic null points" of a symmetric array of permanent magnets yield a strong nonlinearity for chaotic particle motion in microwave generated plasmas (at electron cyclotron resonance). It has been shown that particles can be heated in a "shaking billiard table" configuration of the multi-cusp: low-energy particles are heated by cyclotron resonance with the wave field, while high energy particles are heated through a nonresonant transit-time mechanism. We apply a recent theory which proves that magnetic field lines are trajectories of Hamiltonian systems and develop a quasilinear theory for the dynamics of particles in presence of the chaotic behavior of the magnetic field lines. The aim of the present study is the development of a numerical technique for handling local trajectories of particles and generate symplectic maps for nontwist systems. Periodic orbits and their characteristics are found by searching symmetry lines. Hence, including the tracking of particles and of magnetic field lines, we demonstrate that the chaotic acceleration of particles and thus the anomalous resistivity found in ultrafine plasma etching experiments, is likely to occur not only in the neighborhood of magnetic field line reconnection points but also at magnetic symmetry break-up points.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.437
Threshold uncertainty score1.000

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)0.0010.000

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 head0.028
GPT teacher head0.270
Teacher spread0.242 · 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 designObservational
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

Citations0
Published2003
Admission routes1
Has abstractyes

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