Conveners
Galaxy Finding and Sorting in the Vera Rubin Observatory’s LSST and Beyond
- Ian Dell'Antonio (Brown University)
Description
In this module we will use the multi-band imaging information and a multi-layer neural network trained on a subset of galaxies with five-band images (u,g,r,i,z, representing images spanning the wavelength to solve a slightly simpler version of the galaxy redshift determination problem. Often, it’s more important to know which galaxies to include or exclude in an analysis as a first step rather than extracting the precise redshift. In this module, you’ll be using a network trained via stochastic gradient descent to separate galaxies into background (galaxies that are gravitationally lensed by the mass) and potential galaxy cluster members.
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