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Generative AI for Hypothetical Exoplanet Ecosystems: A Physics-Informed Generative Framework for Space Discovery

Year: 2025

Type: article

Abstract: We propose a physics-informed generative framework to simulate plausible exoplanet biospheres conditioned on stellar type, orbital/planetary parameters, and atmospheric chemistry. The model synthesizes ecosystem state variables (energy flow, trophic structure, metabolism classes) under thermodynamic and radiative-transfer constraints. Results suggest that generative AI can act as a hypothesis engine to guide biosignature searches.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.16997647

Author: Kochetti, Naga sri ram

Language: English

Topic: Space Science and Extraterrestrial Life

Subfield: Astronomy and Astrophysics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7078688173

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