Microlensing Survey

Microlensing surveys analyze the brightening of distant stars caused by intervening objects, primarily to detect exoplanets and other faint celestial bodies. Current research focuses on improving the accuracy and efficiency of analyzing the complex light curves produced by these events, employing machine learning techniques like neural networks and convolutional neural networks to overcome computational challenges and resolve inherent ambiguities in interpreting the data. These advancements are leading to a better understanding of exoplanetary systems and the detection of asteroids, enhancing our knowledge of planetary formation and the distribution of objects within our galaxy.