arxiv
PublishedOctober 27, 2026 at 4:00 AM
An actively trained neural operator for near-explicit atmospheric chemistry
Publisher summary· verbatim
arXiv:2610.33771v1 Announce Type: new Abstract: Earth-system models simplify atmospheric chemistry into condensed mechanisms, because near-explicit mechanisms such as the Master Chemical Mechanism (MCM) are too costly to solve in every grid cell. Neural emulators could lift this limit, but most adva
Stay posted· Newsletter
Three short emails a week: Monday, Wednesday and Friday. Top movers, new models and the most-referenced story.
Your email is used only to send The Bubble Brief. Privacy policy
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivWhen Generated Information Returns: Error Persistence in LLM-Mediated Information Ecosystems13harxivQuery-Driven Learning for Lifted Reasoning13harxivThe Social World Model Evaluation Gap13harxivConviction Without Evidence: Verdict Stability Is Independent of Visual Grounding in Medical Vision--Language Models13hThe Bubble Brief
MON · WED · FRIRead AI insights every Monday, Wednesday and Friday — top movers, new models, story of the week.
Your email is used only to send The Bubble Brief. Privacy policy
Originally published on arxiv ↗