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Cosmological constraints from non-Gaussian and nonlinear galaxy clustering using the SimBIG inference framework

  • ChangHoon Hahn,
  • Pablo Lemos,
  • Liam Parker,
  • Bruno Régaldo-Saint Blancard,
  • Michael Eickenberg,
  • Shirley Ho,
  • Jiamin Hou,
  • Elena Massara,
  • Chirag Modi,
  • Azadeh Moradinezhad Dizgah,
  • David Spergel

摘要

The standard ΛCDM cosmological model predicts the presence of cold dark matter, with the current accelerated expansion of the Universe driven by dark energy. This model has recently come under scrutiny because of tensions in measurements of the expansion and growth histories of the Universe, parameterized using H0 and S8. The three-dimensional clustering of galaxies encodes key cosmological information that addresses these tensions. Here we present a set of cosmological constraints using simulation-based inference that exploits additional non-Gaussian information on nonlinear scales from galaxy clustering, inaccessible with current analyses. We analyse a subset of the Baryon Oscillation Spectroscopic Survey (BOSS) galaxy survey using SimBIG, a new framework for cosmological inference that leverages high-fidelity simulations and deep generative models. We use two clustering statistics beyond the standard power spectrum: the bispectrum and a summary of the galaxy field based on a convolutional neural network. We constrain H0 and S8 1.5 and 1.9 times more tightly than power spectrum analyses. With this increased precision, our constraints are competitive with those of other cosmological probes, even with only 10% of the full BOSS volume. Future work extending SimBIG to upcoming spectroscopic galaxy surveys (DESI, PFS, Euclid) will produce improved cosmological constraints that will develop understanding of cosmic tensions.