Related papers: pop-cosmos: Scaleable inference of galaxy properti…
We present an extension of the pop-cosmos model for the evolving galaxy population up to redshift $z\sim6$. The model is trained on distributions of observed colors and magnitudes, from 26-band photometry of $\sim420,000$ galaxies in the…
Principled Bayesian inference of galaxy properties has not previously been performed for wide-area weak lensing surveys with millions of sources. We address this gap by applying the pop-cosmos generative model to perform spectral energy…
We present pop-cosmos: a comprehensive model characterizing the galaxy population, calibrated to $140,938$ ($r<25$ selected) galaxies from the Cosmic Evolution Survey (COSMOS) with photometry in $26$ bands from the ultra-violet to the…
The accuracy of the cosmological constraints from Stage~IV galaxy surveys will be limited by how well the galaxy redshift distributions can be inferred. We have addressed this challenging problem for the Kilo-Degree Survey (KiDS) cosmic…
Next generation photometric and spectroscopic surveys will enable unprecedented tests of the concordance cosmological model and of galaxy formation and evolution. Fully exploiting their potential requires a precise understanding of the…
We present PopSED, a framework for the population-level inference of galaxy properties from photometric data. Unlike the traditional approach of first analyzing individual galaxies and then combining the results to determine the physical…
Models of Stellar Population Synthesis (SPS) provide a predictive framework for the spectral energy distribution (SED) of a galaxy. SPS predictions can be computationally intensive, creating a bottleneck for attempts to infer the physical…
We present a Bayesian hierarchical framework to analyze photometric galaxy survey data with stellar population synthesis (SPS) models. Our method couples robust modeling of spectral energy distributions with a population model and a noise…
We present GalSBI, a phenomenological model of the galaxy population for cosmological applications using simulation-based inference. The model is based on analytical parametrizations of galaxy luminosity functions, morphologies and spectral…
Accurate redshift calibration is required to obtain unbiased cosmological information from large-scale galaxy surveys. In a forward modelling approach, the redshift distribution n(z) of a galaxy sample is measured using a parametric galaxy…
Models of stellar population synthesis (SPS) are the fundamental tool that relates the physical properties of a galaxy to its spectral energy distribution (SED). In this paper, we present DSPS: a python package for stellar population…
We present a forward modeling framework for estimating galaxy redshift distributions from photometric surveys. Our forward model is composed of: a detailed population model describing the intrinsic distribution of physical characteristics…
We study star formation over 12 Gyr using pop-cosmos, a generative model trained on 26-band photometry of 420,000 COSMOS2020 galaxies (IRAC Ch.1 $<26$). The model learns distributions over 16 SPS parameters via score-based diffusion,…
For the next generation of spectroscopic galaxy surveys, it is important to forecast their performances and to accurately interpret their large data sets. For this purpose, it is necessary to consistently simulate different populations of…
Using the photometric population prediction method {\bf Red Dragon}, we characterize the Red Sequence (RS) and Blue Cloud (BC) of DES galaxies in the COSMOS field. Red Dragon (RD) uses a redshift-evolving, error-corrected Gaussian mixture…
The Probabilistic Value-Added Bright Galaxy Survey (PROVABGS) catalog will provide the posterior distributions of physical properties of $>10$ million DESI Bright Galaxy Survey (BGS) galaxies. Each posterior distribution will be inferred…
We present SPECULATOR - a fast, accurate, and flexible framework for emulating stellar population synthesis (SPS) models for predicting galaxy spectra and photometry. For emulating spectra, we use principal component analysis to construct a…
We measure photometric redshifts and spectral types for galaxies in the COSMOS survey. We use template fitting technique combined with luminosity function priors and with the option to simultaneously estimate dust extinction (i.e. E(B-V))…
Determining the redshift distribution $n(z)$ of galaxy samples is essential for several cosmological probes including weak lensing. For imaging surveys, this is usually done using photometric redshifts estimated on an object-by-object…
Highly accurate models of the galaxy population over cosmological volumes are necessary in order to predict the performance of upcoming cosmological missions. We present a data-driven model of the galaxy population constrained by deep 0.1-8…