MeSsI (Merging Systems Identification)
de los rios+16 2016MNRAS.458..226D
Merging galaxy systems provides observational evidence of the existence of dark matter and constraints on its properties. Therefore, statistical uniform samples of merging systems would be a powerful tool for several studies. In this work, we present MeSsI (Merging Systems Identification algorithm) a new machine learning method for merging systems identification.
We use as a starting point a mock catalog of galaxy systems, identified using traditional FoF algorithms, which experienced a major merger as indicated by its merger tree. This code is completely free and public and can be downloaded and used as an R package (https://github.com/Martindelosrios/MeSsI).
This project was developed by Martín de los Rios, Mariano Domínguez, Dante Paz and Manuel Merchán.
A versatile multifluid HD/MHD code that runs on clusters of CPUs or GPUs, with special emphasis on protoplanetary disks. FARGO3D is the successor of the FARGO code, that you can still find in the legacy part of this site. FARGO3D. The main features of FARGO3D are: FARGO3D son:
Cartesian, cylindrical or spherical geometry. As in FARGO, a simple Runge-Kutta N-body solver may be used to describe the orbital evolution of embedded point-like objects. Multifluid capability. 1, 2 or 3 dimensional calculations. Orbital advection (aka FARGO) for HD and MHD calculations. No need to know CUDA: you can develop new functions in C and have them translated to CUDA automatically to run on GPUs. FARGO3D was written by Pablo Benítez Llambay (main developper) and by Frédéric Masset. The multifluid version was developed by Pablo Benítez Llambay and Leonardo Krapp.