3 papers
astro-ph.EP2025
Analyzing Data Quality and Decay in Mega-Constellations: A Physics-Informed Machine Learning Approach
Katarina Dyreby, Francisco Caldas, Cláudia Soares
In the era of mega-constellations, the need for accurate and publicly available information has become fundamental for satellite operators to guarantee the safety of spacecrafts an…
cs.LG2025
OrbitZoo: Real Orbital Systems Challenges for Reinforcement Learning
Alexandre Oliveira, Katarina Dyreby, Francisco Caldas +1
The increasing number of satellites and orbital debris has made space congestion a critical issue, threatening satellite safety and sustainability. Challenges such as collision avo…
cs.LG2025
Advancing Solutions for the Three-Body Problem Through Physics-Informed Neural Networks
Manuel Santos Pereira, Luís Tripa, Nélson Lima +2
First formulated by Sir Isaac Newton in his work "Philosophiae Naturalis Principia Mathematica", the concept of the Three-Body Problem was put forth as a study of the motion of the…