{
  "abstract": "Mapping the three-dimensional distribution of dark matter is key to tracing the growth of cosmic structure. Two-dimensional weak lensing mass maps recover its projected distribution, but they blend structures at different distances along the line of sight. We reconstruct the three-dimensional matter distribution in the 0.54 deg$^2$ COSMOS-Web field using deep James Webb Space Telescope imaging, with an effective source density of 121 galaxies arcmin$^{-2}$ We combine a physical weak lensing forward model with a diffusion-based Bayesian generative prior learned from cosmological simulations, yielding a posterior distribution of the matter field across 20 lens planes to $z \\simeq 2$, doubling the redshift reach of previous Hubble Space Telescope-based 3D reconstructions and approaching cosmic noon, an epoch of rapid galaxy growth. The reconstruction separates structures that overlap in projection and recovers non-Gaussian matter structure across a range of spatial scales, including over-densities associated with independently identified galaxy clusters that were not detected in earlier weak lensing maps. Posterior sampling quantifies the range of three-dimensional matter distributions allowed by the data, enabling a probabilistic visualization of the cosmic web while propagating uncertainties in its inferred structure. Null and simulation-based tests show that the recovered structures are supported by the lensing signal and are consistent with expectations from the fiducial $Λ$CDM cosmology. These results extend three-dimensional weak lensing mapping into the high-redshift, non-Gaussian regime and establish a route towards probabilistic mapping of the evolving cosmic web with current wide-field lensing surveys.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2611.03786",
  "author_total": 20,
  "authors": [
    {
      "name": "Diana Scognamiglio"
    },
    {
      "name": "Brandon Zhao"
    },
    {
      "name": "Katherine L. Bouman"
    },
    {
      "name": "Olivier Doré"
    },
    {
      "name": "Caitlin M. Casey"
    },
    {
      "name": "Maximilien Franco"
    },
    {
      "name": "Ghassem Gozaliasl"
    },
    {
      "name": "David Harvey"
    },
    {
      "name": "Olivier Ilbert"
    },
    {
      "name": "Jeffrey B. Jewell"
    },
    {
      "name": "Jeyhan S. Kartaltepe"
    },
    {
      "name": "Anton M. Koekemoer"
    },
    {
      "name": "Gavin Leroy"
    },
    {
      "name": "Richard Massey"
    },
    {
      "name": "Jason Rhodes"
    },
    {
      "name": "Brant E. Robertson"
    },
    {
      "name": "Marko Shuntov"
    },
    {
      "name": "Sune Toft"
    },
    {
      "name": "Greta Toni"
    },
    {
      "name": "Michael A. Troxel"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/4tmf97jw8bbsd.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2611.03786",
  "fulltext_url": null,
  "id": "4tmf97jw8bbsd",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2611.03786",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "astro-ph.CO"
    ],
    [
      "arxiv",
      "cs.LG"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://arxiv.org/pdf/2611.03786",
  "pmcid": null,
  "pmid": null,
  "published": "2026-11-02",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/4tmf97jw8bbsd.ris",
  "sources": [
    {
      "first_seen": "2026-11-04T15:21:25Z",
      "native_id": "2611.03786",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2611.03786"
    }
  ],
  "subjects": [
    {
      "field": "astronomy",
      "origin": "arxiv:astro-ph.CO",
      "subfield": "cosmology"
    }
  ],
  "title": "3D dark matter map of the JWST COSMOS-Web field using diffusion-based generative priors",
  "title_text": "3D dark matter map of the JWST COSMOS-Web field using diffusion-based generative priors",
  "type": "preprint",
  "updated_at": "2026-11-05T15:20:35Z",
  "url": "https://research.draconitic.com/paper/4tmf97jw8bbsd",
  "venue": "arXiv",
  "versions": []
}