Bayesian Inference of Quasi‐Linear Radial Diffusion Parameters using Van Allen Probes Article Swipe
Rakesh Sarma
,
Mandar Chandorkar
,
Irina Zhelavskaya
,
Yuri Shprits
,
Alexander Drozdov
,
Enrico Camporeale
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1029/2019ja027618
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1029/2019ja027618
The Van Allen radiation belts in the magnetosphere have been extensively studied using models based on radial diffusion theory, which is derived from a quasi‐linear approach with prescribed inner and outer boundary conditions. The 1D diffusion model requires the knowledge of a diffusion coefficient and an electron loss timescale, which is typically parameterized in terms of various quantities such as the spatial ( L ) coordinate or a geomagnetic index (e.g., K p ). These terms are typically empirically derived, not directly measurable, and hence are not known precisely, due to the inherent nonlinearity of the process and the variable boundary conditions. In this work, we demonstrate a probabilistic approach by inferring the values of the diffusion and loss term parameters, along with their uncertainty, in a Bayesian framework, where identification is obtained using the Van Allen Probe measurements. Our results show that the probabilistic approach statistically improves the performance of the model, compared to the empirical parameterization employed in the literature.
Related Topics
Concepts
Diffusion
Probabilistic logic
Van Allen radiation belt
Bayesian inference
Nonlinear system
Statistical physics
Applied mathematics
Inference
Bayesian probability
Boundary (topology)
Diffusion process
Mathematics
Magnetosphere
Physics
Algorithm
Computer science
Statistics
Mathematical analysis
Artificial intelligence
Thermodynamics
Plasma
Quantum mechanics
Innovation diffusion
Knowledge management
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1029/2019ja027618
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1029/2019JA027618
- OA Status
- bronze
- Cited By
- 13
- References
- 54
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3005318080
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3005318080Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1029/2019ja027618Digital Object Identifier
- Title
-
Bayesian Inference of Quasi‐Linear Radial Diffusion Parameters using Van Allen ProbesWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-04-07Full publication date if available
- Authors
-
Rakesh Sarma, Mandar Chandorkar, Irina Zhelavskaya, Yuri Shprits, Alexander Drozdov, Enrico CamporealeList of authors in order
- Landing page
-
https://doi.org/10.1029/2019ja027618Publisher landing page
- PDF URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1029/2019JA027618Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1029/2019JA027618Direct OA link when available
- Concepts
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Diffusion, Probabilistic logic, Van Allen radiation belt, Bayesian inference, Nonlinear system, Statistical physics, Applied mathematics, Inference, Bayesian probability, Boundary (topology), Diffusion process, Mathematics, Magnetosphere, Physics, Algorithm, Computer science, Statistics, Mathematical analysis, Artificial intelligence, Thermodynamics, Plasma, Quantum mechanics, Innovation diffusion, Knowledge managementTop concepts (fields/topics) attached by OpenAlex
- Cited by
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13Total citation count in OpenAlex
- Citations by year (recent)
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2024: 2, 2023: 3, 2022: 5, 2021: 3Per-year citation counts (last 5 years)
- References (count)
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54Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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