Neural physical engines for inferring the halo mass distribution function

@article{Charnock2019NeuralPE,
  title={Neural physical engines for inferring the halo mass distribution function},
  author={Tom Charnock and Guilhem Lavaux and Benjamin D. Wandelt and Supranta S. Boruah and Jens Jasche and Michael James Hudson},
  journal={arXiv: Cosmology and Nongalactic Astrophysics},
  year={2019}
}
  • Tom Charnock, Guilhem Lavaux, +3 authors Michael James Hudson
  • Published 2019
  • Physics
  • arXiv: Cosmology and Nongalactic Astrophysics
  • An ambitious goal in cosmology is to forward-model the observed distribution of galaxies in the nearby Universe today from the initial conditions of large-scale structures. For practical reasons, the spatial resolution at which this can be done is necessarily limited. Consequently, one needs a mapping between the density of dark matter averaged over ~Mpc scales, and the distribution of dark matter halos (used as a proxy for galaxies) in the same region. Here we demonstrate a method for… CONTINUE READING

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