xmm_simulator generates mock XMM-Newton images and spectra from 3D galaxy cluster simulations from hydrodynamical simulations. It generates particle background spectra from filter-wheel-closed data, a realistic sky background model, energy-dependent vignetting, energy redistribution, and PSF convolution. Users can extract lists of simulated events, corresponding photon images, exposure maps, non-X-ray background maps, and spectra with redistribution matrices and weighted ancillary responses. xmm_simulator also includes tools to sum maps from multiple instruments and to organize simulation outputs into FITS files suitable for further analysis.

Hydromass analyzes galaxy cluster mass profiles from X-ray and/or Sunyaev-Zel’dovich observations. It provides a global Bayesian framework for deprojection and mass profile reconstruction, including mass model fitting, forward fitting with parametric and polytropic models, and non-parametric log-normal mixture reconstruction. Hydromass easily loads public X-COP data products and applies reconstruction tools directly within a Jupyter notebook.

pred_loggs models the entire PGF probability density field, enabling iterative statistical modeling of upper limits and prediction of full G/S probability distributions for individual galaxies.

DPMhalo (Descriptive Parametric Model) generates profiles of gaseous halos (pressure, electron density, and metallicity) as functions of radius, halo mass, and redshift. The code assumes spherically symmetric, volume-filling warm/hot gas, and enables mock observations of the circumgalactic medium (CGM), group halos, and clusters across a number of wavebands including X-ray, sub-millimeter/millimeter, radio, and ultraviolet (UV).