Dark from light (DfL): Inferring halo properties from luminous tracers with machine learning trained on cosmological simulations Article

Bluck, Asa FL, Piotrowska, Joanna M, Goubert, Paul et al. (2025). Dark from light (DfL): Inferring halo properties from luminous tracers with machine learning trained on cosmological simulations . ASTRONOMY & ASTROPHYSICS, 700 10.1051/0004-6361/202554702

Open Access International Collaboration

cited authors

  • Bluck, Asa FL; Piotrowska, Joanna M; Goubert, Paul; Maiolino, Roberto; Casimiro, Camilo; Franco, Thomas Pinto; Cea, Nicolas

authors

publication date

  • August 28, 2025

published in

keywords

  • ASSEMBLY BIAS
  • Astronomy & Astrophysics
  • ILLUSTRISTNG SIMULATIONS
  • MILLENNIUMTNG PROJECT
  • OCCUPATION DISTRIBUTION
  • PROBE WMAP OBSERVATIONS
  • Physical Sciences
  • ROTATION CURVES
  • SATELLITE GALAXIES
  • SPIRAL GALAXIES
  • STAR-FORMING GALAXIES
  • STELLAR MASS
  • Science & Technology
  • dark matter
  • galaxies: abundances
  • galaxies: evolution
  • galaxies: formation
  • galaxies: statistics

Digital Object Identifier (DOI)

publisher

  • EDP SCIENCES S A

volume

  • 700