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Record W4411166439 · doi:10.1088/1402-4896/ade373

Analytical solution of the space-dependent cosmic ray Fokker-Planck equation using Airy functions

2025· article· en· W4411166439 on OpenAlexafffund
B Klippenstein, A. Shalchi

Bibliographic record

VenuePhysica Scripta · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsUniversity of Manitoba
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsFokker–Planck equationPhysicsAiry functionSpace (punctuation)PlanckCOSMIC cancer databaseAstrophysicsCosmic rayClassical mechanicsStatistical physicsQuantum mechanicsDifferential equationComputer science

Abstract

fetched live from OpenAlex

Abstract The motion of energetic particles such as cosmic rays is complicated due to their interaction with turbulent magnetic fields. In particular, an analytical description of such interactions is difficult to achieve due to their stochastic and nonlinear nature. Therefore, transport equations are used to describe the motion of energetic particles. In phase-space, where the particle distribution function depends on position, time, and velocity, one uses a Fokker-Planck partial differential equation. While the general case of such a transport equation is too complicated to solve analytically, we consider the special case of a constant pitch-angle scattering coefficient. For this special case we explore analytical solutions of the Fokker-Planck equation by using Airy functions. We also develop an N-dimensional subspace method for this case corresponding to a semi-analytical approach. We compare the different methods, obtained results, and computational times needed with each other. We also determine different expectation values which are relevant for applications in particle transport theory.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.024
GPT teacher head0.277
Teacher spread0.253 · 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 designTheoretical or conceptual
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
Published2025
Admission routes2
Has abstractyes

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