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Measuring the total neutrino mass is one of the most exciting opportunities available with next-generation cosmological data sets. We study the possibility of detecting the total neutrino mass using large-scale clustering in 21cm intensity mapping and photometric galaxy surveys, together with CMB information. We include the scale-dependent halo bias contribution due to the presence of massive neutrinos, and use a multi-tracer analysis in order to reduce cosmic variance. The multi-tracer combination of an SKAO-MID 21cm intensity map with Stage~4 CMB lensing dramatically shrinks the uncertainty on total neutrino mass to $sigma(M_ u) simeq 45,$meV, using only linear clustering information ($k_{rm max} = 0.1, h/$Mpc) and without a prior on optical depth. When we add to the multi-tracer the clustering information expected from LSST, the forecast is $sigma(M_ u) simeq 12,$meV.
We perform a thorough examination of the neutrino mass ($M_ u$) constraints achievable by combining future spectroscopic galaxy surveys with cosmic microwave background (CMB) experiments, focusing on the contribution of CMB lensing and galaxy-CMB len
Cosmic Microwave Background (CMB) is a powerful probe to study the early universe and various cosmological models. Weak gravitational lensing affects the CMB by changing its power spectrum, but meanwhile, it also carries information about the distrib
We explore the effect of massive neutrinos on the weak lensing shear bispectrum using the Cosmological Massive Neutrino Simulations. We find that the primary effect of massive neutrinos is to suppress the amplitude of the bispectrum with limited effe
We analyze the ability of galaxy and CMB lensing surveys to constrain massive neutrinos and new models of dark radiation. We present a Fisher forecast analysis for neutrino mass constraints with the LSST galaxy survey and the CMB S4 survey. A joint a
We explore the effects of incorporating redshift uncertainty into measurements of galaxy clustering and cross-correlations of galaxy positions and cosmic microwave background (CMB) lensing maps. We use a simple Gaussian model for a redshift distribut