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Nonlinear Wave Growth Analysis of Chorus Emissions modulated by field line resonance and mirror-mode ULF waves

2023· article· en· W4387314766 on OpenAlexaff
Li Li, Yoshiharu Omura, Xuzhi Zhou, Qiugang Zong, R. Rankin, Chao Yue, S. Y. Fu, Jie Ren

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Alberta
FundersChina Postdoctoral Science FoundationChinese Academy of SciencesChina National Space Administration
KeywordsPhysicsChorusField lineVan Allen ProbesExcitationStanding waveGeophysicsComputational physicsMagnetosphereMagnetic fieldAcousticsVan Allen radiation belt

Abstract

fetched live from OpenAlex

Previous studies have found that chorus waves can be generated in the troughs of the compressional ULF waves. Here, we report for the first time the periodic excitation of chorus waves near ULF wave crests, which is attributed to different modes of the observed ULF waves. We demonstrate that latitudinal profile of the ULF waves can play important roles in excitation of chorus waves on the basis of nonlinear generation theory of chorus emissions. Field line resonance (FLR) mode results in chorus wave excitation near ULF wave troughs, while the mirror mode causes chorus near the wave crest. Chorus wave occurrence near the ULF wave crests is attributed to the antisymmetric field profiles of mirror-mode ULF waves, which periodically modulate the threshold amplitude by modifying the second-order derivative of the background dipole field. FLR ULF wave with the symmetric profile of magnetic field with respect to the equator fosters chorus wave excitation near ULF wave trough. The good agreement between the theory and the observations highlights the effects of ULF wave field configuration in modulating chorus waves.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.249
Teacher spread0.241 · 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 designSimulation or modeling
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
Published2023
Admission routes1
Has abstractyes

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