It's not $σ_8$ : constraining the non-linear matter power spectrum with the Dark Energy Survey Year-5 supernova sample
Authors: Paul Shah, T. M. Davis, M. Vincenzi, P. Armstrong, D. Brout, R. Camilleri, L. Galbany, M. S. S. Gill, D. Huterer, N. Jeffrey, O. Lahav, J. Lee, C. Lidman, A. Möller, M. Sullivan, L. Whiteway, P. Wiseman, S. Allam, M. Aguena, J. Annis, J. Blazek, D. Brooks, A. Carnero Rosell, J. Carretero, C. Conselice, L. N. da Costa, M. E. S. Pereira, S. Desai, H. T. Diehl, P. Doel, S. Everett, I. Ferrero, B. Flaugher, J. Frieman, J. García-Bellido, E. Gaztanaga, G. Giannini, D. Gruen, R. A. Gruendl, G. Gutierrez, S. R. Hinton, D. L. Hollowood, K. Honscheid, D. J. James, S. Lee, J. L. Marshall, J. Mena-Fernández, R. Miquel, A. Palmese, A. Pieres, A. A. Plazas Malagón, A. Porredon, S. Samuroff, E. Sanchez, I. Sevilla-Noarbe, M. Smith, E. Suchyta, M. E. C. Swanson, G. Tarle, D. L. Tucker, N. Weaverdyck
Abstract: The weak gravitational lensing magnification of Type Ia supernovae (SNe Ia) is sensitive to the matter power spectrum on scales $k>1 h$ Mpc$^{-1}$, making it unwise to interpret SNe Ia lensing in terms of power on linear scales. We compute the probability density function of SNe Ia magnification as a function of standard cosmological parameters, plus an empirical parameter $A_{\rm mod}$ which describes the suppression or enhancement of matter power on non-linear scales compared to a cold dark matter only model. While baryons are expected to enhance power on the scales relevant to SN Ia lensing, other physics such as neutrino masses or non-standard dark matter may suppress power. Using the Dark Energy Survey Year-5 sample, we find $A_{\rm mod} = 0.77^{+0.69}_{-0.40}$ (68\% credible interval around the median). Although the median is consistent with unity there are hints of power suppression, with $A_{\rm mod} < 1.09$ at 68\% credibility.
Explore the paper tree
Click on the tree nodes to be redirected to a given paper and access their summaries and virtual assistant
Look for similar papers (in beta version)
By clicking on the button above, our algorithm compares the title and abstract of this paper with all the papers of the same arXiv category that we have summarized, and finds the closest ones. You can rerun it from time to time: the results improve as our database grows.