Category archives: DIPC Astrophysics

DSPS: a python package for stellar population synthesis

DSPS: a python package for stellar population synthesis

DIPC AstrophysicsDIPC Computational Cosmology

By DIPC

Stellar population synthesis (SPS) is the prevailing framework for predicting the spectral energy distribution of a galaxy (SED) from its fundamental physical properties. SPS is a mature subfield with a long history dating back to the seventies of the last century. Applications of SPS range from inferring the physical properties of individual galaxies, to forward […]

Robust clustering predictions using hydrodynamics for different samples of galaxies

Robust clustering predictions using hydrodynamics for different samples of galaxies

DIPC Astrophysics

By DIPC

Not all matter in the universe is visible. The mass of matter that cannot be “seen” by direct observatops of its emitted or absorbed electromagnetic radiation is called dark matter. In the current lambda-Cold Dark Matter (ΛCDM) paradigm, the most accepted “theory to model the Universe in large scales”, so-called baryonic (visible) matter assembles where […]