{
  "abstract": "We develop a projection-based reduced-order model for the high-field Vlasov-Poisson-Fokker-Planck system. Based on a micro-macro decomposition, the proposed Micro-ROM applies proper orthogonal decomposition (POD)-Galerkin reduction only to the microscopic fluctuation while retaining the macroscopic density on the full spatial grid. The field-dependent Maxwellian and collision operator introduce additional computational costs that cannot be eliminated by Galerkin projection alone. To remove the dependence on the velocity-grid resolution during online simulations, we approximate the projected Maxwellian terms using precomputed Chebyshev expansions of functions of the local electric field and exploit a separable discretization of the collision operator to assemble the reduced collision matrix exactly from precomputed blocks. A first-order implicit-explicit scheme is employed to evolve the reduced coefficients and the density. The resulting method conserves discrete mass and formally recovers a discretization of the limiting high-field model as $\\varepsilon\\rightarrow 0$. Its online computational cost per time step is independent of the velocity-grid resolution. Numerical experiments demonstrate the accuracy and efficiency of the proposed method across a range of parameters, including the high-field regime.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.25569",
  "author_total": 2,
  "authors": [
    {
      "name": "Shiheng Zhang"
    },
    {
      "name": "Jingwei Hu"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/2tc8aj27gc644.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.25569",
  "fulltext_url": null,
  "id": "2tc8aj27gc644",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.25569",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.NA"
    ],
    [
      "arxiv",
      "math.NA"
    ],
    [
      "openalex",
      "3109|Model Reduction and Neural Networks"
    ]
  ],
  "openalex": "W7222995759",
  "pdf_url": "https://arxiv.org/pdf/2610.25569",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-18",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/2tc8aj27gc644.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:30:57Z",
      "native_id": "2610.25569",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.25569"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:math.NA",
      "subfield": "numerical-analysis"
    }
  ],
  "title": "A Reduced-Order Model for the High-Field Vlasov-Poisson-Fokker-Planck System Based on a Micro-Macro Decomposition",
  "title_text": "A Reduced-Order Model for the High-Field Vlasov-Poisson-Fokker-Planck System Based on a Micro-Macro Decomposition",
  "type": "preprint",
  "updated_at": "2026-10-30T12:33:44Z",
  "url": "https://research.draconitic.com/paper/2tc8aj27gc644",
  "venue": "arXiv",
  "versions": []
}