PIAO is an efficient memory-controlled Python code that uses the standard spherical overdensity (SO) algorithm to identify halos. PIAO employs two additional parameters besides the overdensity Δc. The first is the mesh-box size, which splits the whole simulation box into smaller ones then analyzes them one-by-one, thereby overcoming a possible memory limitation problem that can occur when dealing with high-resolution, large-volume simulations. The second is the smoothed particle hydrodynamics (SPH) neighbors number, which is used for the SPH density calculation.

PyMGal generates optical mock observations from cosmological simulations. Incorporating methods from EzGal (ascl:1208.021), the program infers the spectral energy distributions (SEDs) of stellar particles within a simulation snapshot using customizable simple stellar population (SSP) models. These SEDs are used to calculate particle brightness through selected telescope filters. The results can be projected into realistic 2D images. The software is compatible with different simulation formats, including GADGET, GIZMO, and AREPO. Tested on IllustrisTNG, SIMBA, EAGLE, and The Three Hundred hydrodynamical simulations, PyMGal should work on other cosmological simulations as well.