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Mohammed Abdel Razek
· 1 min read
ResearcharXiv cs.LG
Universal Observatory Graphs for Distributed Sky Coverage and Artificial Intelligence Based Interplanetary Routing
arXiv:2609.22244v1 Announce Type: new
Abstract: This research proposes the Universal Observatory Graph (UOG), an AI-driven framework for distributed astronomical observation across the Solar System. The proposed architecture models autonomous observatories located at the Sun planet L2 Lagrange points as nodes in a weighted graph, while communication links are represented as graph edges characterized by multi-objective physical and operational metrics, including interplanetary distance, communication latency, transmission power, and link reliability. The resulting graph provides a unified mathematical representation of a cooperative interplanetary observatory network. This proposal examines a six-observatory Solar System configuration comprising Earth, Mars, Jupiter, Saturn, Uranus and Neptune. Instantaneous sky coverage is evaluated independently using a 200,000 direction Fibonacci sphere, a 2,000,000 direction fixed seed Monte Carlo calculation and deterministic spherical integration. All three methods yield complete network union coverage, approximately 0.43% complete six observatory intersection and approximately 24.96% mean pairwise Jaccard similarity under the adopted pointing model. Communication routing is subsequently formulated as a finite horizon Markov decision process and solved using tabular Q-learning. The reward balances node participation and a distance dependent reliability proxy against distance, light time latency and a distance squared transmission power proxy. The learned Earth-Saturn-Uranus-Neptune route is also the highest discounted return route among all 41 feasible simple paths under the four hop constraint. The framework provides a reproducible baseline for sequential coverage assessment and multi objective routing; time dependent ephemerides, mission specific visibility, calibrated link budgets and scalable graph policies remain future work.
Original source
This story was published by arXiv cs.LG and written by Mohammed Abdel Razek. SyncAI.news shows a preview; the complete article is on the publisher's site.
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