Optimal dataset combining in f_nl constraints from large scale structure in an idealised case

We consider the problem of optimal weighting of tracers of structure for the purpose of constraining the non-Gaussianity parameter f_NL. We work within the Fisher matrix formalism expanded around fiducial model with f_NL=0 and make several simplifying assumptions. By slicing a general sample into infinitely many samples with different biases, we derive the analytic expression for the relevant Fisher matrix element. We next consider weighting schemes that construct two effective samples from a single sample of tracers with a continuously varying bias. We show that a particularly simple ansatz for weighting functions can recover all information about f_NL in the initial sample that is recoverable using a given bias observable and that simple division into two equal samples is considerably suboptimal when sampling of modes is good, but only marginally suboptimal in the limit where Poisson errors dominate.Comment: 6 pages, 5 figures; v2: comment on weighting for PS determination, fixed a couple of typos; v3: revised, matches version accepted by JCA

Measuring primordial non-gaussianity without cosmic variance

Non-gaussianity in the initial conditions of the universe is one of the most powerful mechanisms to discriminate among the competing theories of the early universe. Measurements using bispectrum of cosmic microwave background anisotropies are limited by the cosmic variance, i.e. available number of modes. Recent work has emphasized the possibility to probe non-gaussianity of local type using the scale dependence of large scale bias from highly biased tracers of large scale structure. However, this power spectrum method is also limited by cosmic variance, finite number of structures on the largest scales, and by the partial degeneracy with other cosmological parameters that can mimic the same effect. Here we propose an alternative method that solves both of these problems. It is based on the idea that on large scales halos are biased, but not stochastic, tracers of dark matter: by correlating a highly biased tracer of large scale structure against an unbiased tracer one eliminates the cosmic variance error, which can lead to a high signal to noise even from the structures comparable to the size of the survey. The square of error improvement on non-gaussianity parameter f_nl relative to the power spectrum method scales as Pn/2, where P and n is the power spectrum and the number density of the biased tracer, respectively. For an ideal survey out to z=2 the error reduction can be as large as a factor of seven, which should guarantee a detection of non-gaussianity from an all sky survey of this type. The improvements could be even larger if high density tracers that are sensitive to non-gaussianity can be identified and measured over a large volume.Comment: 7 page

Reconstructing large-scale structure with neutral hydrogen surveys

Upcoming 21-cm intensity surveys will use the hyperfine transition in emission to map out neutral hydrogen in large volumes of the universe. Unfortunately, large spatial scales are completely contaminated with spectrally smooth astrophysical foregrounds which are orders of magnitude brighter than the signal. This contamination also leaks into smaller radial and angular modes to form a foreground wedge, further limiting the usefulness of 21-cm observations for different science cases, especially cross-correlations with tracers that have wide kernels in the radial direction. In this paper, we investigate reconstructing these modes within a forward modeling framework. Starting with an initial density field, a suitable bias parameterization and non-linear dynamics to model the observed 21-cm field, our reconstruction proceeds by {combining} the likelihood of a forward simulation to match the observations (under given modeling error and a data noise model) {with the Gaussian prior on initial conditions and maximizing the obtained posterior}. For redshifts z=2 and 4, we are able to reconstruct 21cm field with cross correlation, rc > 0.8 on all scales for both our optimistic and pessimistic assumptions about foreground contamination and for different levels of thermal noise. The performance deteriorates slightly at z=6. The large-scale line-of-sight modes are reconstructed almost perfectly. We demonstrate how our method also provides a technique for density field reconstruction for baryon acoustic oscillations, outperforming standard methods on all scales. We also describe how our reconstructed field can provide superb clustering redshift estimation at high redshifts, where it is otherwise extremely difficult to obtain dense spectroscopic samples, as well as open up a wealth of cross-correlation opportunities with projected fields (e.g. lensing) which are restricted to modes transverse to the line of sight

Sterile neutrinos as subdominant warm dark matter

In light of recent findings which seem to disfavor a scenario with (warm) dark matter entirely constituted of sterile neutrinos produced via the Dodelson-Widrow (DW) mechanism, we investigate the constraints attainable for this mechanism by relaxing the usual hypothesis that the relic neutrino abundance must necessarily account for all of the dark matter. We first study how to reinterpret the limits attainable from X-ray non-detection and Lyman-alpha forest measurements in the case that sterile neutrinos constitute only a fraction fs of the total amount of dark matter. Then, assuming that sterile neutrinos are generated in the early universe solely through the DW mechanism, we show how the X-ray and Lyman-alpha results jointly constrain the mass-mixing parameters governing their production. Furthermore, we show how the same data allow us to set a robust upper limit fs < 0.7 at the 2 sigma level, rejecting the case of dominant dark matter (fs = 1) at the ~ 3 sigma level.Comment: Minor changes; added references; version accepted for publication in Phys. Rev.

Non-Gaussianity and large-scale structure in a two-field inflationary model

Single field inflationary models predict nearly Gaussian initial conditions and hence a detection of non-Gaussianity would be a signature of the more complex inflationary scenarios. In this paper we study the effect on the cosmic microwave background and on large scale structure from primordial non-Gaussianity in a two-field inflationary model in which both the inflaton and curvaton contribute to the density perturbations. We show that in addition to the previously described enhancement of the galaxy bias on large scales, this setup results in large-scale stochasticity. We provide joint constraints on the local non-Gaussianity parameter $\tilde f_{\rm NL}$ and the ratio $\xi$ of the amplitude of primordial perturbations due to the inflaton and curvaton using WMAP and SDSS data

Inverted initial conditions: Exploring the growth of cosmic structure and voids

We introduce and explore "paired" cosmological simulations. A pair consists of an A and B simulation with initial conditions related by the inversion δAðx; tinitialÞ ¼ −δBðx; tinitialÞ (underdensities substituted for overdensities and vice versa). We argue that the technique is valuable for improving our understanding of cosmic structure formation. The A and B fields are by definition equally likely draws from ΛCDM initial conditions, and in the linear regime evolve identically up to the overall sign. As nonlinear evolution takes hold, a region that collapses to form a halo in simulation A will tend to expand to create a void in simulation B. Applications include (i) contrasting the growth of A-halos and B-voids to test excursion-set theories of structure formation, (ii) cross-correlating the density field of the A and B universes as a novel test for perturbation theory, and (iii) canceling error terms by averaging power spectra between the two boxes. Generalizations of the method to more elaborate field transformations are suggested

Bias, redshift space distortions and primordial nongaussianity of nonlinear transformations: application to Lyman alpha forest

On large scales a nonlinear transformation of matter density field can be viewed as a biased tracer of the density field itself. A nonlinear transformation also modifies the redshift space distortions in the same limit, giving rise to a velocity bias. In models with primordial nongaussianity a nonlinear transformation generates a scale dependent bias on large scales. We derive analytic expressions for these for a general nonlinear transformation. These biases can be expressed entirely in terms of the one point distribution function (PDF) of the final field and the parameters of the transformation. Our analysis allows one to devise nonlinear transformations with nearly arbitrary bias properties, which can be used to increase the signal in the large scale clustering limit. We apply the results to the ionizing equilibrium model of Lyman-alpha forest, in which Lyman-alpha flux F is related to the density perturbation delta via a nonlinear transformation. Velocity bias can be expressed as an average over the Lyman-alpha flux PDF. At z=2.4 we predict the velocity bias of -0.1, compared to the observed value of -0.13 +/- 0.03. Bias and primordial nongaussianity bias depend on the parameters of the transformation. Measurements of bias can thus be used to constrain these parameters, and for reasonable values of the ionizing background intensity we can match the predictions to observations. Matching to the observed values we predict the ratio of primordial nongaussianity bias to bias to have the opposite sign and lower magnitude than the corresponding values for the highly biased galaxies, but this depends on the model parameters and can also vanish or change the sign.Comment: 18 pages, 1 figur