Hints of Isocurvature Perturbations in the Cosmic Microwave Background?

TL;DR

This paper investigates whether primordial perturbations include a subdominant, positively correlated CDM isocurvature component. Using a two-scale, power-law parametrization and Bayesian MCMC analysis of CMB (WMAP3, Boomerang, ACBAR) plus LSS data, it finds hints that a correlated isocurvature mode improves the fit (Δχ^2 = 9.7) and yields a nonzero isocurvature fraction ($\alpha \approx 0.08$) with a positive correlation ($\gamma > 0$), corresponding to a ~4% nonadiabatic contribution to the CMB temperature variance ($\alpha_T \approx 0.043$). However, the significance depends on priors and breaks when including small-scale data like Lyman-$\alpha$, suggesting the result is intriguing but not definitive; confirming isocurvature would have major implications for inflationary theory and early-Universe physics. The study highlights the sensitivity of isocurvature inferences to priors and external data, and points to the need for higher-precision CMB measurements to resolve the issue.

Abstract

The improved data on the cosmic microwave background (CMB) anisotropy allow a better determination of the adiabaticity of the primordial perturbation. Interestingly, we find that recent CMB data seem to favor a contribution of a primordial isocurvature mode where the entropy perturbation is positively correlated with the primordial curvature perturbation and has a large spectral index (niso ~ 3). With 4 additional parameters we obtain a better fit to the CMB data by Delta chi^2 = 9.7 compared to an adiabatic model. For this best-fit model the nonadiabatic contribution to the CMB temperature variance is 4%. According to a Markov Chain Monte Carlo analysis the nonadiabatic contribution is positive at more than 95% C.L. The exact C.L. depends somewhat on the choice of priors, and we discuss the effect of different priors as well as additional cosmological data.

Figures (7)

• Figure 1: Marginalized likelihood functions for selected primary and derived parameters. The solid black curves are our new results using WMAP 3-year data and Boomerang data from the 2003 flight (+ ACBAR & SDSS). The dotted black curves show the effect of assigning flat priors in the index parametrization instead of the amplitude parametrization. The red/gray curves are for an adiabatic model using the same data. The dashed blue curves are from our previous study Kurki-Suonio:2004mn using data available in 2004. Note that also in the adiabatic model WMAP3 data favors a larger $H_0$ than WMAP1 (not shown)---allowing isocurvature modes favors larger $H_0$ regardless of which WMAP data set is used, although the effect is much stronger with WMAP3.
• Figure 2: The CMB temperature angular power spectrum for our best-fit model (black) compared to the best-fit adiabatic model (red/gray). The dashed blue curve shows the nonadiabatic contribution. The inset shows the 2nd and 3rd peaks.
• Figure 3: Marginalized likelihood functions for selected primary and derived parameters after including additional priors coming from other cosmological data. The solid black curves are the same as in Fig.\ref{['fig:1dlikelihoods']}. The solid blue curves show the effect of adding the HST $H_0$ prior. The solid red curves show the effect of the stronger $\Omega_m = 0.29^{+0.05}_{-0.03}$ prior and the dashed red curves are for the weaker $\Omega_m = 0.263\pm0.074$ prior. The central values and 1-$\sigma$ ranges of these Gaussian priors are indicated by vertical lines and gray areas in the $\Omega_\Lambda$ and $H_0$ panels.
• Figure 4: The red curves show the priors for the parameters of the index parametrization, when flat priors are assumed for the parameters of the amplitude parametrization. The black curves are the posterior likelihoods we have obtained (the same as the solid black curves in Fig. \ref{['fig:1dlikelihoods']}).
• Figure 5: The priors for the parameters of the amplitude parametrization, when flat priors are assumed for the parameters of the index parametrization.