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FOMO-Z. Optimal galaxy classification, photometric redshifts, and reconstruction of population distributions
We present FOMO-Z (Flexible Optimizer of Multi-dimensional Operators and photo-$z$s), a set of statistical methods implemented in Python for galaxy classification and probabilistic inference from photometry. The methods use a reference sample with known galaxy properties. They rely on explicit, ph
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