Astronomical Transient

Astronomical transients are fleeting celestial events, such as supernovae and other stellar explosions, whose detection and classification are crucial for advancing our understanding of the universe. Current research focuses on developing automated, real-time anomaly detection systems using machine learning techniques, including neural networks (like convolutional and recurrent networks) and ensemble methods (such as isolation forests and gradient boosting), to sift through the massive datasets generated by modern and upcoming surveys. These efforts aim to improve the efficiency and accuracy of transient identification, enabling faster follow-up observations and ultimately leading to a more comprehensive understanding of stellar evolution and high-energy astrophysical phenomena.