{"ID":2867323,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.19453","arxiv_id":"2509.19453","title":"The Platonic Universe: Do Foundation Models See the Same Sky?","abstract":"We test the Platonic Representation Hypothesis (PRH) in astronomy by measuring representational convergence across a range of foundation models trained on different data types. Using spectroscopic and imaging observations from JWST, HSC, Legacy Survey, and DESI, we compare representations from vision transformers, self-supervised models, and astronomy-specific architectures via mutual $k$-nearest neighbour analysis. We observe consistent scaling: representational alignment generally increases with model capacity across our tested architectures, supporting convergence toward a shared representation of galaxy astrophysics. Our results suggest that astronomical foundation models can use pre-trained general-purpose architectures, allowing us to capitalise on the broader machine learning community's already-spent computational investment.","short_abstract":"We test the Platonic Representation Hypothesis (PRH) in astronomy by measuring representational convergence across a range of foundation models trained on different data types. Using spectroscopic and imaging observations from JWST, HSC, Legacy Survey, and DESI, we compare representations from vision transformers, self...","url_abs":"https://arxiv.org/abs/2509.19453","url_pdf":"https://arxiv.org/pdf/2509.19453v1","authors":"[\"UniverseTBD\",\":\",\"Kshitij Duraphe\",\"Michael J. Smith\",\"Shashwat Sourav\",\"John F. Wu\"]","published":"2025-09-23T18:10:05Z","proceeding":"astro-ph.IM","tasks":"[\"astro-ph.IM\",\"cs.LG\"]","methods":"[\"Vision Transformer\",\"Transformer\"]","has_code":false}