DEAVI incorporates several algorithms. The main ones are:
INDICATE (INdex to Define Inherent Clustering And TEndencies ) is a novel statistical clustering tool to assess and quantify the degree of spatial association of an object in a dataset. Highly versatile, INDICATE has many applications, including characterising morphological stellar features and tracing spatial evolution in star forming regions.
Papers:
S2D2 is an algorithm that uses the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) to detect the smallest significant structure in a spatial/spatial-kinematic space. The procedure proposes, in structured regions, the calculation of the epsilon scale and Nmin parameters for DBSCAN to retrieve the smallest structures in the region with a 3-sigma level significance. If the region is not structured, or the user wants it, epsilon scale and Nmin can be supplied, and DBSCAN will be run with the user defined parameters, however, without guaranteeing any level of significance.
Papers:
One of the goals of the SFM project is to develop new tools which can be used to look at Gaia and Herschel data. One such tools is a code to Make Your Own Synthetic ObservaTIonS (MYOSOTIS). The code is designed to take the output from Nbody (or any other) simulations and show how the cluster would look when observed with various different platforms. The code can do both imaging, and spectroscopy, making it ideally suited for exploring observational constraints on mass segregation, binary fractions, etc. A set of this simulations performed by Cardiff University for the SFM project is included in DEAVI.
Papers:
The StarFormMapper project, or SFM project, should be acknowledged using the following quote:
DEAVI should be acknowledged using the following quote (or similar):
DEAVI is hosted at: https://sfmdeavi.quasarsr.com/