The current version of the Zurich Extragalactic Bayesian Redshift Analyzer (ZEBRA) combines and extends several of the classical approaches to produce accurate photometric redshifts down to faint magnitudes. In particular, ZEBRA uses the template-fitting approach to produce Maximum Likelihood and Bayesian redshift estimates based on: (1.) An automatic iterative technique to correct the original set of galaxy templates to best represent the SEDs of real galaxies at different redshifts; (2.) A training set of spectroscopic redshifts for a small fraction of the photometric sample; and (3.) An iterative technique for Bayesian redshift estimates, which extracts the full two-dimensional redshift and template probability function for each galaxy.

GLACiAR (GaLAxy survey Completeness AlgoRithm) estimates the completeness and selection functions in galaxy surveys. Tailored for multiband imaging surveys aimed at searching for high-redshift galaxies through the Lyman Break technique, the code can nevertheless be applied broadly. GLACiAR generates artificial galaxies that follow Sérsic profiles with different indexes and with customizable size, redshift and spectral energy distribution properties, adds them to input images, and measures the recovery rate.

Forcepho infers the fluxes and shapes of galaxies from astronomical images. It models the appearance of multiple sources in multiple bands simultaneously and compares to observed data via a likelihood function. Gradients of this likelihood allow for efficient maximization of the posterior probability or sampling of the posterior probability distribution via Hamiltonian Monte Carlo. The model intrinsic galaxy shapes and positions are shared across the different bands, but the fluxes are fit separately for each band. Forcepho does not perform detection; initial locations and (very rough) parameter estimates must be supplied by the user.