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Register a new userThe Persistence of Large Scale Structures I: Primordial non-Gaussianity
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We develop an analysis pipeline for characterizing the topology of large scale structure and extracting cosmological constraints based on persistent homology. Persistent homology is a technique from topological data analysis that quantifies the multiscale topology of a data set, in our context unifying the contributions of clusters, filament loops, and cosmic voids to cosmological constraints. We describe how this method captures the imprint of primordial local non-Gaussianity on the late-time distribution of dark matter halos, using a set of N-body simulations as a proxy for real data analysis. For our best single statistic, running the pipeline on several cubic volumes of size $40~(rm{Gpc/h})^{3}$, we detect $f_{rm NL}^{rm loc}=10$ at $97.5%$ confidence on $sim 85%$ of the volumes. Additionally we test our ability to resolve degeneracies between the topological signature of $f_{rm NL}^{rm loc}$ and variation of $sigma_8$ and argue that correctly identifying nonzero $f_{rm NL}^{rm loc}$ in this case is possible via an optimal template method. Our method relies on information living at $mathcal{O}(10)$ Mpc/h, a complementary scale with respect to commonly used methods such as the scale-dependent bias in the halo/galaxy power spectrum. Therefore, while still requiring a large volume, our method does not require sampling long-wavelength modes to constrain primordial non-Gaussianity. Moreover, our statistics are interpretable: we are able to reproduce previous results in certain limits and we make new predictions for unexplored observables, such as filament loops formed by dark matter halos in a simulation box.
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Our current understanding of the Universe is established through the pristine measurements of structure in the cosmic microwave background (CMB) and the distribution and shapes of galaxies tracing the large scale structure (LSS) of the Universe. One key ingredient that underlies cosmological observables is that the field that sources the observed structure is assumed to be initially Gaussian with high precision. Nevertheless, a minimal deviation from Gaussianityis perhaps the most robust theoretical prediction of models that explain the observed Universe; itis necessarily present even in the simplest scenarios. In addition, most inflationary models produce far higher levels of non-Gaussianity. Since non-Gaussianity directly probes the dynamics in the early Universe, a detection would present a monumental discovery in cosmology, providing clues about physics at energy scales as high as the GUT scale.
We study primordial non-gaussianity in supersolid inflation. The dynamics of supersolid is formulated in terms of an effective field theory based on four scalar fields with a shift symmetric action minimally coupled with gravity. In the scalar sector, there are two phonon-like excitations with a kinetic mixing stemming from the completely spontaneous breaking of diffeomorphism. In a squeezed configuration, $f_{text{NL}}$ of scalar perturbations is angle dependent and not proportional to slow-roll parameters showing a blunt violation of the Maldacena consistency relation. Contrary to solid inflation, the violation persists even after an angular average and generically the amount of non-gaussianity is significant. During inflation, non-gaussianity in the TSS and TTS sector is enhanced in the same region of the parameters space where the secondary production of gravitational waves is sizeable enough to enter in the sensitivity region of LISA, while the scalar $f_{text{NL}}$ is still within the current experimental limits.
(ABRIDGED)The rise of cosmic structure depends upon the statistical distribution of initial density fluctuations generated by inflation. While the simplest models predict an almost perfectly Gaussian distribution, more-general models predict a level of primordial non-Gaussianity (PNG) that observations might yet be sensitive enough to detect. Recent Planck Collaboration measurements of the CMB temperature anisotropy bispectrum significantly tighten the observational limits, but they are still far from the PNG level predicted by the simplest models of inflation. Probing levels below CMB sensitivities will require other methods, such as searching for the statistical imprint of PNG on galactic halo clustering. During the epoch of reionization (EoR), the first stars and galaxies released radiation into the intergalactic medium (IGM) that created ionized patches whose large-scale geometry and evolution reflected the underlying abundance and large-scale clustering of the star-forming galaxies. This statistical connection between ionized patches in the IGM and galactic halos suggests that observing reionization may be another way to constrain PNG. We employ the linear perturbation theory of reionization and semi-analytic models based on the excursion-set formalism to model the effects of PNG on the EoR. We quantify the effects of PNG on the large-scale structure of reionization by deriving the ionized density bias, i.e. ratio of ionized atomic to total matter overdensities in Fourier space, at small wavenumber. Just as previous studies found that PNG creates a scale-dependent signature in the halo bias, so, too, we find a scale-dependent signature in the ionized density bias. Our results, which differ significantly from previous attempts in the literature to characterize this PNG signature, will be applied elsewhere to predict its observable consequences, e.g. in the cosmic 21cm background.
Here we review the present status of modelling of and searching for primordial non-Gaussianity of cosmological perturbations. After introducing the models for non-Gaussianity generation during inflation, we discuss the search for non-Gaussian signatures in the Cosmic Microwave Background and in the Large-Scale Structure of the Universe.
We apply a new method to measure primordial non-Gaussianity, using the cross-correlation between galaxy surveys and the CMB lensing signal to measure galaxy bias on very large scales, where local-type primordial non-Gaussianity predicts a $k^2$ divergence. We use the CMB lensing map recently published by the Planck collaboration, and measure its external correlations with a suite of six galaxy catalogues spanning a broad redshift range. We then consistently combine correlation functions to extend the recent analysis by Giannantonio et al. (2013), where the density-density and the density-CMB temperature correlations were used. Due to the intrinsic noise of the Planck lensing map, which affects the largest scales most severely, we find that the constraints on the galaxy bias are similar to the constraints from density-CMB temperature correlations. Including lensing constraints only improves the previous statistical measurement errors marginally, and we obtain $ f_{mathrm{NL}} = 12 pm 21 $ (1$sigma$) from the combined data set. However, the lensing measurements serve as an excellent test of systematic errors: we now have three methods to measure the large-scale, scale-dependent bias from a galaxy survey: auto-correlation, and cross-correlation with both CMB temperature and lensing. As the publicly available Planck lensing maps have had their largest-scale modes at multipoles $l<10$ removed, which are the most sensitive to the scale-dependent bias, we consider mock CMB lensing data covering all multipoles. We find that, while the effect of $f_{mathrm{NL}}$ indeed increases significantly on the largest scales, so do the contributions of both cosmic variance and the intrinsic lensing noise, so that the improvement is small.
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