LIGHT implements a Bayesian framework for reconstructing the three-dimensional galaxy and underlying dark matter fields informed by large-scale structure. The software uses Hamiltonian Monte Carlo (HMC) sampling via NumPyro (ascl:2505.005) to infer the true galaxy density distribution and its magnitude distribution given incomplete galaxy catalog data, addressing biases in statistical analyses that combine galaxy catalogs with other observations. LIGHT’s models incorporate spatial correlations of galaxies on cosmological scales and enable construction of improved three-dimensional priors in redshift and sky position for host galaxies of gravitational-wave events. LIGHT supports dark siren cosmology, where gravitational-wave distances are combined with reconstructed galaxy fields to improve inference of cosmological parameters, and includes example configurations and scripts.

Hi-COLA runs fast approximate N-body simulations of non-linear structure formation in reduced Horndeski gravity (Horndeski theories with luminal gravitational waves). It is generic with respect to the reduced Horndeski class. Given an input Lagrangian, Hi-COLA's front-end dynamically constructs the appropriate field equations and consistently solves for the cosmological background, linear growth, and screened fifth force of that theory. This is passed to the back-end, which runs a hybrid N-body simulation at significantly reduced computational and temporal cost compared to traditional N-body codes. By analyzing the particle snapshots, one can study the formation of structure through statistics such as the matter power spectrum.