{
  "abstract": "We present a data-driven investigation of Galactic diffuse emission. Using multi-frequency Planck maps (30–857 GHz), we construct a non-linear mapping between microwave-to-far-infrared and gamma-ray intensity through supervised machine learning. Our models achieve high predictive accuracy ( $$R^2>$$ R 2 > 0.90 in the 0.1–10 GeV range), demonstrating that multi-band Planck emission encodes sufficient information to reconstruct both spatial morphology and spectral properties of diffuse gamma-ray emission. By analyzing model performance across different frequency bands and spatial regions, we find that the high-frequency Planck bands are the dominant predictors, indicating that the learned mapping is primarily driven by gas- and dust-correlated structures encoded in the adopted interstellar emission model. Above 10 GeV, the increasing relevance of the low-frequency bands is consistent with synchrotron-traced cosmic-ray electron structures that may be associated with leptonic inverse Compton emission. Residual maps reveal coherent large-scale structures, including Loop I and III, highlighting regions where standard interstellar emission models are incomplete or biased. Compared with the GALPROP model, our machine learning approach yields a higher $$R^2=0.95$$ R 2 = 0.95 and lower mean absolute relative error (14.7%) in the inner Galactic disk and the Galactic Center (GC) region at $$\\sim $$ ∼ 4.3 GeV. Our results illustrate that machine learning serves as a physically interpretable tool for multi-messenger astrophysics, providing a data-driven baseline for separating non-standard emission components and deriving new constraints on cosmic-ray propagation and interstellar medium structure.",
  "abstract_shown": true,
  "affiliations": [
    "Sun Yat-sen University",
    "Ocean University of China",
    "Mathematics and Physics, Ocean University of China",
    "University of Johannesburg"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 7,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Xi Liu"
    },
    {
      "affs": [
        0
      ],
      "name": "Xiao-Dong Li"
    },
    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "Sujie Lin"
    },
    {
      "affs": [
        0
      ],
      "name": "Yihan Liu"
    },
    {
      "affs": [
        0
      ],
      "name": "Chengyu Shao"
    },
    {
      "affs": [
        0,
        3
      ],
      "name": "Lili Yang",
      "orcid": "0000-0001-7416-7434"
    },
    {
      "affs": [
        0
      ],
      "name": "Le Zhang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/8n6x43zqdyt6v.bib",
  "cited_by": 0,
  "doi": "10.1140/epjc/s10052-026-16408-2",
  "fulltext_url": null,
  "id": "8n6x43zqdyt6v",
  "issns": [
    "1434-6052"
  ],
  "landing_url": "https://link.springer.com/10.1140/epjc/s10052-026-16408-2",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "3106|Astrophysics and Cosmic Phenomena"
    ]
  ],
  "openalex": "W7164573899",
  "pdf_url": "https://link.springer.com/content/pdf/10.1140/epjc/s10052-026-16408-2.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-30",
  "publisher": "Springer Science and Business Media LLC",
  "ris": "https://research.draconitic.com/paper/8n6x43zqdyt6v.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:04Z",
      "native_id": "10.1140/epjc/s10052-026-16408-2",
      "source": "crossref",
      "url": "https://link.springer.com/10.1140/epjc/s10052-026-16408-2"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "openalex:3106|Astrophysics and Cosmic Phenomena",
      "subfield": "high-energy"
    }
  ],
  "title": "Data-driven modeling of Galactic diffuse emission with multi-wavelength observations",
  "title_text": "Data-driven modeling of Galactic diffuse emission with multi-wavelength observations",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:18:04Z",
  "url": "https://research.draconitic.com/paper/8n6x43zqdyt6v",
  "venue": "The European Physical Journal C",
  "versions": []
}