Tests of Neutrino and Dark Radiation Models from Galaxy and CMB surveys

TL;DR

This work evaluates how LSST galaxy weak lensing and clustering, together with CMB Stage-4 lensing, can constrain the sum of neutrino masses $\sum m_\nu$ and nonstandard light relics that affect $N_{\rm eff}$ and late-time power. Using a Fisher forecast with tomographic LSST data, Planck priors, and cross-survey information, the authors find $\sigma(\sum m_\nu)\approx0.041$ eV (LSST alone) dropping to $\approx0.032$ eV with DESI priors, and about $0.031$ eV in LSST+S4, further improving to $\sim0.020$ eV with DESI. For dark radiation with $\Delta N_{\rm eff}=0.15$, they forecast $\sigma(m_{\rm DR})\approx0.137$–$0.162$ eV depending on fermionic vs bosonic statistics, illustrating combined constraints on $N_{\rm eff}$ and mass. They also show that the NNaturalness scenario yields sub-percent signatures on linear scales, requiring more ambitious surveys or new observables to be detectable. Overall, the results highlight strong complementarity between optical surveys, CMB lensing, and spectroscopic priors, while emphasizing the need for nonlinear modeling and robust systematics control to achieve robust detections.

Abstract

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 analysis of the three galaxy and shear 2-point functions, along with key systematics parameters and Planck priors, constrains the neutrino masses to $\sum m_ν= 0.041\,$eV at 1-$σ$ level, comparable to constraints expected from Stage 4 CMB lensing. If low redshift information from upcoming spectroscopic surveys like DESI is included, the constraint becomes $\sum m_ν= 0.032\,$eV. These constraints are derived having marginalized over the number of relativistic species ($N_{\rm eff}$), which is somewhat degenerate with the neutrino mass. We also explore the gain by combining LSST and CMB S4, that is, using the five relevant auto- and cross-correlations of the two datasets. We conclude that advances in modeling the nonlinear regime and the measurements of other parameters are required to ensure a neutrino mass detection. Using the same datasets, we explore the ability of LSST-era surveys to test "nonstandard" models with dark radiation. We find that if evidence for dark radiation is found from $N_{\rm eff}$ measurements, the mass of the dark radiation candidate can be measured at a 1-$σ$ level of $0.162\,$eV for fermionic dark radiation, and $0.137\,$eV for bosonic dark radiation, for $ΔN_{\rm eff} = 0.15$. We also find that the NNaturalness model of Arkani-Hamed et al 2016, with extra light degrees of freedom, has a sub-percent effect on the power spectrum: even more ambitious surveys than the ones considered here will be needed to test such models.

Figures (10)

• Figure 1: Expected source galaxy counts (per square arcmin) as a function of redshift in the LSST survey is plotted with the black curve. The solid red lines indicate the photometric redshifts $z_{\rm min}$ and $z_{\rm max}$ of the 6 lens bins used in our analysis. The dashed blue lines represent the $z_{\rm min}$ and $z_{\rm max}$ for the 6 source bins. The blue lines have been slightly displaced for clarity.
• Figure 2: Comparison of the $C_l^{gg}$ and $C_l^{\kappa\kappa}$ power spectra at different redshifts to the shot noise and shape noise levels at those redshifts. The solid lines plot the power spectrum, while the dashed line of the same color plots the shot noise or shape noise for that power spectrum at that redshift expected at LSST. The dot-dashed lines represent the value of $l_{\rm max}$ for each redshift bin. The spectra are sample variance dominated out to $l\sim 400$.
• Figure 3: Noise level $N_l^{dd}$ in the deflection power spectrum $C_l^{dd}$ from CMB Stage 4 lensing for the assumed survey parameters. The lensing signal is sample variance dominated out to $l\sim 1000$.
• Figure 4: Marginalized probability distributions for the sum of neutrino masses (left), and dark energy equation of state $w$ (right), from LSST. The blue, red and black curves correspond to $N_L = N_S = 1,4,6$ respectively. Increasing the number of redshift helps extract more tomographic information, but this gain saturates as the individual bins become too thin.
• Figure 5: 1-$\sigma$ (solid lines) and 2-$\sigma$ (dashed lines) confidence intervals on 2-d subspace of the parameters $\sum m_\nu$ and $w$ from LSST. The red curves are the results from 4 source bin and 4 lens bin analysis. The black curves represent the results when 6 source bins and 6 lens bins are used.