Speaker
Description
Gravitational microlensing is a powerful astrophysical method for detecting celestial objects that are not directly observable. This phenomenon, predicted by Einstein's general theory of relativity, occurs when a massive object (lens) bends the light from a more distant object (source), resulting in a magnified image.
Microlensing is particularly effective for studying distant stars and detecting exoplanets, including low-mass, cold planets. It allows us to observe events where the light from a distant star is temporarily amplified by a massive intervening object.
In this project, we investigate how the temporal density of observational data impacts the probability of detecting nearby planets during microlensing events. Using data simulations, we analyze how reducing telescope exposure times affects the likelihood of planet detection. Optimizing these exposure times is crucial for improving the efficiency of detecting microlensing events and studying faint, distant objects like exoplanets.
