Mining galaxy morphology

It is not trivial to find the intrinsic properties of galaxy morphology from the ensemble posterior of entire galaxy sample that one studies. We always see a marginalized information; even 3D structure is hard to visualize. Often we lose useful information by looking at simple 2D distribution of galaxy morphology parameters; some of apparently contradictory correlations might be unified as a coherent structure in higher dimensional parameter space. This higher order inference is possible only if we have a better way of characterizing the data.

As we have large volume of data from forthcoming survey like LSST, this data mining will become more essential ingredient for a successful research career of graduate student.


~ by ilsangyoon on December 10, 2010.

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