Cosmological information and bias from lensing of point sources
My seminar will be about cosmological gravitational lensing of point sources by matter structures along the line of sight. I will first introduce the sGL method, an approach to quickly compute the lensing PDF for point sources. I will then show various applications. When analyzing supernova datasets lensing is usually treated as a noise which changes the error budget and can bias the results (if selection effects are present). This is an important topic for accurate cosmology and I will show how sGL can contribute to it. On the other hand, if a good modeling of SN lensing is available, one can invert the problem and transform noise into signal and I will show which cosmological information can be extracted from future SN surveys. Finally, I will discuss ongoing work on constraining the inner halo profile with strong lensing.