{"ID":2875137,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.03623","arxiv_id":"2509.03623","title":"Revealing Fine Structure in Protoplanetary Disks with Physics Constrained Neural Fields","abstract":"Protoplanetary disks are the birthplaces of planets, and resolving their three-dimensional structure is key to understanding disk evolution. The unprecedented resolution of ALMA demands modeling approaches that capture features beyond the reach of traditional methods. We introduce a computational framework that integrates physics-constrained neural fields with differentiable rendering and present RadJAX, a GPU-accelerated, fully differentiable line radiative transfer solver achieving up to 10,000x speedups over conventional ray tracers, enabling previously intractable, high-dimensional neural reconstructions. Applied to ALMA CO observations of HD 163296, this framework recovers the vertical morphology of the CO-rich layer, revealing a pronounced narrowing and flattening of the emission surface beyond 400 au - a feature missed by existing approaches. Our work establish a new paradigm for extracting complex disk structure and advancing our understanding of protoplanetary evolution.","short_abstract":"Protoplanetary disks are the birthplaces of planets, and resolving their three-dimensional structure is key to understanding disk evolution. The unprecedented resolution of ALMA demands modeling approaches that capture features beyond the reach of traditional methods. We introduce a computational framework that integra...","url_abs":"https://arxiv.org/abs/2509.03623","url_pdf":"https://arxiv.org/pdf/2509.03623v1","authors":"[\"Aviad Levis\",\"Nhan Luong\",\"Richard Teague\",\"Katherine. L. Bouman\",\"Marcelo Barraza-Alfaro\",\"Kevin Flaherty\"]","published":"2025-09-03T18:18:16Z","proceeding":"astro-ph.EP","tasks":"[\"astro-ph.EP\",\"cs.CV\"]","methods":"[]","has_code":false}