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Record W119155464

Shock Drift Acceleration in presence of turbulence: A simple model

2010· article· en· W119155464 on OpenAlexaff
K. Meziane, A. M. Hamza, M. Wilber, C. Mazelle

Bibliographic record

VenueEGU General Assembly Conference Abstracts · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSolar and Space Plasma Dynamics
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsPhysicsShock (circulatory)TurbulenceMach numberAccelerationBow shock (aerodynamics)Fermi accelerationMechanicsParticle accelerationComputational physicsRange (aeronautics)Particle (ecology)Moving shockOblique shockClassical mechanicsShock waveMaterials science
DOInot available

Abstract

fetched live from OpenAlex

Analytic treatments of particle acceleration by collisionless shocks have commonly been based on the assumption that the shock surface is quasi-planar with length scales larger than the particle gyroradius. Within this framework, the derived particle distributions are not in full agreement with the observations. Recent theoretical studies as well as numerical simulations indicate that ion scales shock fluctuations could account for several features observed in shock-associated energetic particle velocity distributions. We have developed a simple model based on the shock drift acceleration mechanism in which both the shock normal direction and the shock mirror ratio N = B2=B1 are subject to random fluctuations. While, the maximum particle energy gain is dependent upon N, the pitch angle distribution is dependent to both N and shock geometry. The fluctuations could be induced by shock turbulence inherent to the shock nonstationarity occuring for high Mach number and for a wide range of shock geometries. For low energy particles, we derive the probability distributions functions f(vjj) and f(v?) of ions escaping upstream; we show that the distributions significantly deviate from the conventional Maxwellian signature. At higher energy, the derived energy spectrum extends to higher energy in comparison to the one obtained when the fluctuations are suppressed. The derived results are compared to ion distributions and spectra observed upstream of the Earth bow shock. They also in turn allow us to draw possible analogy with neutral fluid turbulence involving higher moments of the particle distribution.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.588
Threshold uncertainty score0.777

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 head0.016
GPT teacher head0.267
Teacher spread0.251 · 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 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
Published2010
Admission routes1
Has abstractyes

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