Optical Colors as Compressed Spectral Information for Trans-Neptunian Objects

Abstract

Broadband optical colors have long been recognized as tracers of the surface spectral properties of trans-Neptunian objects (TNOs), yet their relationship to near-infrared (NIR) spectra has not been quantitatively characterized. We construct an empirical optical-NIR spectral manifold from JWST spectroscopy of 40 TNOs and 8 Neptune Trojans and interpret broadband photometry as compressed representations of this manifold. Using the spectral manifold as a prior, the model conditions on observed broadband optical colors to infer a posterior distribution in the spectral latent space. We then evaluate filter combinations through posterior entropy and Kullback-Leibler information gain and found that the gr colors provide broad localization on the manifold, while additional filters substantially reduce posterior uncertainty. Independently defined optical color populations map coherently onto the major compositional classes of the spectral manifold, providing a physical interpretation of previously identified color groups. The learned manifold also enables the inverse mapping back to optical color space. Sampling and decoding the manifold reproduces the observed topology of optical color space, indicating that these color populations arise naturally as low-dimensional projections of a continuous optical-NIR compositional manifold rather than isolated empirical clusters. The forward and inverse mappings provide a unified interpretation of optical colors as compressed representations of an optical-NIR spectral manifold. As JWST expands the manifold and Rubin maps millions of objects onto it, this framework provides an innovated approach to population-scale compositional studies and the discovery of rare surface types.

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BibTeX RIS

BibTeX

@misc{lin2026optical,
  title = {{Optical Colors as Compressed Spectral Information for Trans-Neptunian Objects}},
  author = {Hsing-Wen Lin and Larissa Markwardt and Kevin Napier and Fred Adams and Renu Malhotra and David Gerdes},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.01169},
  eprint = {2609.01169},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.01169},
  note = {CC BY 4.0},
}

RIS

TY  - UNPB
TI  - Optical Colors as Compressed Spectral Information for Trans-Neptunian Objects
AU  - Hsing-Wen Lin
AU  - Larissa Markwardt
AU  - Kevin Napier
AU  - Fred Adams
AU  - Renu Malhotra
AU  - David Gerdes
PY  - 2026
DA  - 2026/09/06
PB  - arXiv
DO  - 10.48550/arxiv.2609.01169
UR  - https://arxiv.org/abs/2609.01169
AB  - Broadband optical colors have long been recognized as tracers of the surface spectral properties of trans-Neptunian objects (TNOs), yet their relationship to near-infrared (NIR) spectra has not been quantitatively characterized. We construct an empirical optical-NIR spectral manifold from JWST spectroscopy of 40 TNOs and 8 Neptune Trojans and interpret broadband photometry as compressed representations of this manifold. Using the spectral manifold as a prior, the model conditions on observed broadband optical colors to infer a posterior distribution in the spectral latent space. We then evaluate filter combinations through posterior entropy and Kullback-Leibler information gain and found that the gr colors provide broad localization on the manifold, while additional filters substantially reduce posterior uncertainty. Independently defined optical color populations map coherently onto the major compositional classes of the spectral manifold, providing a physical interpretation of previously identified color groups. The learned manifold also enables the inverse mapping back to optical color space. Sampling and decoding the manifold reproduces the observed topology of optical color space, indicating that these color populations arise naturally as low-dimensional projections of a continuous optical-NIR compositional manifold rather than isolated empirical clusters. The forward and inverse mappings provide a unified interpretation of optical colors as compressed representations of an optical-NIR spectral manifold. As JWST expands the manifold and Rubin maps millions of objects onto it, this framework provides an innovated approach to population-scale compositional studies and the discovery of rare surface types.
ER  -

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