Constraining inﬂationary scalar ﬁeld models with CMB spectral distortions
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The Cosmic Microwave Background (CMB) demonstrates extreme uniformity, with only small temperature anisotropies of the order of 10^(-5). These anisotropies are believed to originate from primordial density perturbations, caused by quantum fluctuations of scalar fields during the cosmic inflation. In the canonical scenario, the single-field slow-roll inflation, these perturbations are assumed to be sourced by one field, the inflaton. However, it is possible that there are multiple fields present during inflation, that give contribution to the perturbations. In addition to the temperature anisotropies, the CMB spectrum encodes a wealth of information on the thermal history of the early universe. The measured frequency spectrum of the CMB is remarkably close to a black-body spectrum, meaning that the photons and electrons in the early universe plasma were extremely close to a thermal equilibrium. However, in the concordance model of cosmology, Lambda-CDM, there are mechanisms present that lead to unavoidable deviations from the black-body, dubbed as spectral distortions. The diffusion of the acoustic oscillations, that are created due to the initial perturbations, leads to mixing of photons of different temperatures, creating of spectral distortions, which are expected to be below the current observational sensitivity. In the literature, this mechanism is dubbed as the Silk damping. In this thesis we study the formation of mu-type spectral distortions due to the Silk damping in models, where the primordial perturbations are sourced by multiple scalar fields. Our main task is to investigate the spectral distortion signal of inflationary two-field models. We find that generally, the mu-signal can be greatly enhanced compared to the single-field model value. We further show that in a specific two-field model, the mixed inflaton-curvaton model, the mu-distortion testable by future CMB surveys in conjunction with bounds on the tensor-to-scalar ratio r, can efficiently constrain the curvaton model parameter space. ...
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