Tuesday

I will discuss the application of Bayesian inference methods to allow the determination of mass profile parameters using galaxy sizes and fluxes as the main observable. I will discuss the main limitations and strengths of such an approach, and details ways in which systematic uncertainty in the observables may be mitigated. I will discuss the application of the method in the reconstruction of the large clusters of the STAGES HST field, and compare the statistical power and accuracy of the method in comparison to shear observations on the same field, and will show that magnification can reconstruct cluster masses to comparable signal-to-noise, but with evidence of low bias.

I will detail an extension to this method which combines shear observables to allow the simultaneous inference of the intrinsic (un-lensed) distributions of lensing observables, as well as a natural framework for the computationally efficient inclusion of measurement uncertainty and calibration in observables. I will discuss how size and flux magnification may be combined for mass reconstruction for future large surveys.