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Feedback from active galactic nuclei and stellar processes changes the matter distribution on small scales, leading to significant systematic uncertainty in weak lensing constraints on cosmology. We investigate how the observable properties of group-scale haloes can constrain feedback’s impact on the matter distribution using Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS). Extending the results of previous work to smaller halo masses and higher wavenumber, k, we find that the baryon fraction in haloes contains significant information about the impact of feedback on the matter power spectrum. We explore how the thermal Sunyaev Zel’dovich (tSZ) signal from group-scale haloes contains similar information. Using recent Dark Energy Survey weak lensing and Atacama Cosmology Telescope tSZ cross-correlation measurements and models trained on CAMELS, we obtain 10 per cent constraints on feedback effects on the power spectrum at $k \sim 5\, h\, {\rm Mpc}^{-1}$. We show that with future surveys, it will be possible to constrain baryonic effects on the power spectrum to $\mathcal {O}(\lt 1~{{\ \rm per\ cent}})$ at $k = 1\, h\, {\rm Mpc}^{-1}$ and $\mathcal {O}(3~{{\ \rm per\ cent}})$ at $k = 5\, h\, {\rm Mpc}^{-1}$ using the methods that we introduce here. Finally, we investigate the impact of feedback on the matter bispectrum, finding that tSZ observables are highly informative in this case.

 

Many sources contribute to the diffuse gamma-ray background (DGRB), including star forming galaxies, active galactic nuclei, and cosmic ray interactions in the Milky Way. Exotic sources, such as dark matter annihilation, may also make some contribution. The photon counts-in-pixels distribution is a powerful tool for analysing the DGRB and determining the relative contributions of different sources. However, including photon energy information in a likelihood analysis of the counts-in-pixels distribution quickly becomes computationally intractable as the number of source types and energy bins increase. Here, we apply the likelihood-free method of approximate Bayesian computation (ABC) to the problem. We consider a mock analysis that includes contributions from dark matter annihilation in Galactic subhaloes as well as astrophysical backgrounds. We show that our results using ABC are consistent with the exact likelihood when energy information is discarded, and that significantly tighter parameter constraints can be obtained with ABC when energy information is included. ABC presents a powerful tool for analysing the DGRB and understanding its varied origins.

 

Abstract Dark matter annihilation in dwarf spheroidal (dSph) galaxies near the Milky Way has the potential to produce a detectable signature in gamma-rays. The amplitude of this signal depends on the dark matter density in a dSph, the dark matter particle mass, the number of photons produced in an annihilation, and the possibly velocity-dependent dark matter annihilation cross section. We argue that if the amplitude of the annihilation signal from multiple dSphs can be measured, it is possible to determine the velocity-dependence of the annihilation cross section. However, we show that doing so will require improved constraints on the dSph density profiles, including control of possible sources of systematic uncertainty. Making reasonable assumptions about future improvements, we make forecasts for the ability of current and future experiments — including Fermi, CTA and AMEGO — to constrain the dark matter annihilation velocity dependence.