Pith Number

pith:KVYG6DU5

pith:2025:KVYG6DU5LTIBIOVCCOUQFJIOXN

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SE3D: Building a radiative transfer emulator to fit panchromatic resolved galaxy observations with 3D models of dust and stars

Cheng Li, Junkai Zhang, Steven Ramnichal, Stijn Wuyts

A Bayesian neural network emulator reproduces 3D radiative transfer outputs for galaxies to 0.05 dex accuracy.

arxiv:2511.19623 v2 · 2025-11-24 · astro-ph.GA · astro-ph.IM

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\usepackage{pith}
\pithnumber{KVYG6DU5LTIBIOVCCOUQFJIOXN}

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Record completeness

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3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

The computationally efficient machine learning emulator uses a Bayesian neural network architecture, and reproduces the spectral distributions at an accuracy of ~ 0.05 dex or less across the dynamic range of input parameters, and across the rest-frame UVJ colour space spanned by observed galaxies.

C2weakest assumption

The library of toy models with chosen stellar and dust geometries plus radial population gradients is representative enough of real galaxies that the emulator can be used to fit actual panchromatic resolved observations.

C3one line summary

SE3D builds a Bayesian neural network emulator that reproduces galaxy spectral distributions and structural parameters from 3D dust radiative transfer models at ~0.05 dex accuracy across UVJ colors and input ranges.

Receipt and verification

First computed	2026-05-20T00:05:37.942776Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

55706f0e9d5cd0143aa213a902a50ebb6247df97aa7ac71db29537b1ad565b6f

Aliases

arxiv: 2511.19623 · arxiv_version: 2511.19623v2 · doi: 10.48550/arxiv.2511.19623 · pith_short_12: KVYG6DU5LTIB · pith_short_16: KVYG6DU5LTIBIOVC · pith_short_8: KVYG6DU5

Agent API

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/KVYG6DU5LTIBIOVCCOUQFJIOXN \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 55706f0e9d5cd0143aa213a902a50ebb6247df97aa7ac71db29537b1ad565b6f

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "6527b882badcb4470c10f68b45af406c9b862f4a6595fd82497b83ec1ae5e908",
    "cross_cats_sorted": [
      "astro-ph.IM"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "astro-ph.GA",
    "submitted_at": "2025-11-24T19:00:34Z",
    "title_canon_sha256": "fd4e44678a8df40eafb4216ecbdaea2899a07936a30ae7a2616a54fd5799bb9d"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2511.19623",
    "kind": "arxiv",
    "version": 2
  }
}