Particle-Based Lensing is a new technique for gravitaional lensing mass reconstruction. Traditionally, most methods have employed either a finite inversion or gridding to turn observational lensed galaxies ellipticities into an estimate of the surface mass density of a galaxy cluster. We approach the problem from a different perspective, motivated by the success of multi-scale analysis in smoothed particle hydrodynamics. In PBL, we treat each of the lensed galaxies as a particle and then reconstruct the potential by smoothing over a local kernel with variable smoothing scale. In this way, we can tune a reconstruction to produce constant signal-noise throughout, and maximally exploit regions of high information density.
PBL is designed to include all lensing observables, including
multiple image positions and fluxes from strong lensing, as well as weak lensing
signals including shear and flexion. In this paper, however, we describe a
shear-only reconstruction, and apply the method toseveral test cases, including
simulated lensing clusters, as well as the well-studied ``Bullet Cluster''
(1E0657-56). In the former cases, we show that PBL is better able to identify
cusps and substructures than are grid-based reconstructions, and in the latter
case, we show that PBL is able to at identify substructure in the Bullet Cluster
without even exploiting strong lensing measurements.
Here is the POSTERon the subject.
Some interesting results.