• DOI:10.1051/0004-6361/202038308
• Corpus ID: 218470095

A hydrodynamical halo model for weak-lensing cross correlations

@article{Mead2020AHH,
  title={A hydrodynamical halo model for weak-lensing cross correlations},
  author={Alexander Mead and Tilman Tr{\"o}ster and Catherine Heymans and Ludovic Van Waerbeke and Ian G. McCarthy},
  journal={arXiv: Cosmology and Nongalactic Astrophysics},
  year={2020}
}

• A. Mead, T. Tröster, +2 authors I. McCarthy
• Published 1 April 2020
• Physics
• arXiv: Cosmology and Nongalactic Astrophysics

On the scale of galactic haloes, the distribution of matter in the cosmos is affected by energetic, non-gravitational processes; so-called baryonic feedback. A lack of knowledge about the details of how feedback processes redistribute matter is a source of uncertainty for weak-lensing surveys, which accurately probe the clustering of matter in the Universe over a wide range of scales. We develop a cosmology-dependent model for the matter distribution that simultaneously accounts for the clustering of dark matter, gas and stars. We inform our model by comparing it to power spectra measured from the BAHAMAS suite of hydrodynamical simulations. As well as considering matter power spectra, we also consider spectra involving the electron-pressure field, which directly relates to the thermal Sunyaev-Zel'dovich (tSZ) effect. We fit parameters in our model so that it can simultaneously model both matter and pressure data and such that the distribution of gas as inferred from tSZ has influence on the matter spectrum predicted by our model. We present two variants; one that matches the feedback-induced suppression seen in the matter-matter power spectrum at the per-cent level and a second that matches the matter-matter data slightly less well (~2 per cent), but that is able to simultaneously model the matter-electron pressure spectrum at the ~15 per-cent level. We envisage our models being used to simultaneously learn about cosmological parameters and the strength of baryonic feedback using a combination of tSZ and lensing auto- and cross-correlation data.