537 research outputs found
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 and the ratio
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
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