Presentation #139.17 in the session Galaxy Clusters/Large Scale Structure, Cosmic Distance — iPoster Session.
Merging clusters have been used as powerful tools to understand cosmic ray acceleration and dark matter. However, the ambiguity in their merging scenarios severely weakens the constraining powers. We present a robust merging scenario reconstruction method based on a library of hydro merger simulations. The method takes inputs from multi-wavelength data such as substructure masses, halo positions, radio relic properties, etc., and produces full posteriors for key merger parameters. Since we sample chains from numerical simulations, the algorithm can properly take into account dynamical friction, asymmetric acceleration, and shock propagation, which leads to considerable differences in merging scenario reconstruction when compared to purely analytic approaches. We apply the method to the massive merger case ACT-CL J0102-4915 nicknamed “El Gordo” and obtain a merger scenario, which, although discrepant from previous studies, is remarkably consistent with the existing multi-wavelength data. Finally, we demonstrate that the method can easily be extended and accommodate merger cases with different dark matter properties.