Fuzzy dark matter and the Dark Energy Survey Year 1 data

Gravitational weak lensing by dark matter haloes leads to a measurable imprint in the shear correlation function of galaxies. Fuzzy dark matter (FDM), composed of ultralight axion-like particles of mass m similar to 10(-22) eV, suppresses the matter power spectrum and shear correlation with respect to standard cold dark matter. We model the effect of FDM on cosmic shear using the optimized halo model HMCode, accounting for additional suppression of the mass function and halo concentration in FDM as observed in N-body simulations. We combine Dark Energy Survey Year 1 (DES-Y1) data with the Planck cosmic microwave background anisotropies to search for shear correlation suppression caused by FDM. We find no evidence of suppression compared to the preferred cold dark matter model, and thus set a new lower limit to the FDM particle mass. Using a log-flat prior and marginalizing over uncertainties related to the non-linear model of FDM, we find a new, independent 95 per cent C.L. lower limit log(10)m > -23 combining Planck and DES-Y1 shear, an improvement of almost two orders of magnitude on the mass bound relative to CMB-only constraints. Our analysis is largely independent of baryonic modelling, and of previous limits to FDM covering this mass range. Our analysis highlights the most important aspects of the FDM non-linear model for future investigation. The limit to FDM from weak lensing could be improved by up to three orders of magnitude with O(0.1) arcmin cosmic shear angular resolution, if FDM and baryonic feedback can be simultaneously modelled to high precision in the halo model.

Automated summary

Gravitational weak lensing by dark matter haloes leaves a measurable imprint in galaxy shear correlation function. Fuzzy dark matter (FDM), composed of ultralight axion-like particles, suppresses matter power spectrum and shear correlation. Our analysis sets a new lower limit to FDM particle mass, improving the mass bound by almost two orders of magnitude compared to previous constraints.