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RTModel: a platform for real-time modeling and massive analysis of microlensing events
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RTModel: a platform for real-time modeling and massive analysis of microlensing events
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Microlensing of stars in our Galaxy has long been used to detect and characterize stellar populations, exoplanets, brown dwarfs, stellar remnants and whatever objects may magnify the source stars with their gravitational fields. The interpretation of microlensing light curves is relatively simple for single lenses and single sources but becomes more and more complicated if we add more objects and take their relative motion into account. RTModel is a modeling platform that has been very active in the real-time investigation of microlensing events, providing preliminary models that have proven very useful for driving follow-up resources towards the most interesting events. The success of RTModel is due to the ability to make a thorough and aimed exploration of the parameter space in a relatively short time. This is obtained by three key ideas: the initial conditions are chosen from a template library including all possible caustic crossing and approaches; the fits are performed by the Levenberg-Marquardt algorithm using a bumper mechanism to explore multiple minima; the basic computations of microlensing magnification are performed by the fast and robust VBBinaryLensing package. In this paper we will illustrate all algorithms in RTModel in detail, with the purpose of fostering new ideas in view of future microlensing pipelines aimed at massive microlensing analysis.
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Cited by 1 Pith paper
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Microlensing Detection and Inference via Learned Bayes Factors
A unified transformer-based pipeline detects 99.9% of recoverable simulated microlensing events and outperforms literature hard cuts in the short-duration finite-source regime with amortized neural posterior inference.
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