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Register a new userSecondary CMB temperature anisotropies from magnetic reheating
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Spatially fluctuating primordial magnetic fields (PMFs) inhomogeneously reheat the Universe when they dissipate deep inside the horizon before recombination. Such an energy injection turns into an additional photon temperature perturbation. We investigate secondary cosmic microwave background (CMB) temperature anisotropies originated from this mechanism, which we call {it inhomogeneous magnetic reheating}. We find that it can bring us information about non-linear coupling between PMFs and primordial curvature perturbations parametrized by $b_{rm NL}$, which should be important for probing the generation mechanism of PMFs. In fact, by using current CMB observations, we obtain an upper bound on the non-linear parameter as $log (b_{rm NL} (B_{lambda}/{rm nG})^2) lesssim {-36.5n_{B} - 94.0}$ with $B_{lambda}$ and $n_{rm B}$ being a magnetic field amplitude smoothed over $lambda=1; {rm Mpc}$ scale and a spectral index of the PMF power spectrum, respectively. Our constraints are far stronger than a previous forecast based on the future CMB spectral distortion anisotropy measurements because inhomogeneous magnetic reheating covers a much wider range of scales, i.e., $1; {rm Mpc}^{-1} lesssim klesssim 10^{15}; {rm Mpc}^{-1}$.
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As well as primary fluctuations, CMB temperature maps contain a wealth of additional information in the form of secondary anisotropies. Secondary effects that can be identified with individual objects, such as the thermal and kinetic Sunyaev-Zeldovich (SZ) effects due to galaxy clusters, are difficult to unambiguously disentangle from foreground contamination and the primary CMB however. We develop a Bayesian formalism for rigorously characterising anisotropies that are localised on the sky, taking the TSZ and KSZ effects as an example. Using a Gibbs sampling scheme, we are able to efficiently sample from the joint posterior distribution for a multi-component model of the sky with many thousands of correlated physical parameters. The posterior can then be exactly marginalised to estimate properties of the secondary anisotropies, fully taking into account degeneracies with the other signals in the CMB map. We show that this method is computationally tractable using a simple implementation based on the existing Commander component separation code, and also discuss how other types of secondary anisotropy can be accommodated within our framework.
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