107 research outputs found
How closely do baryons follow dark matter on large scales?
We investigate the large-scale clustering and gravitational interaction of
baryons and dark matter (DM) over cosmic time using a set of collisionless
N-body simulations. Both components, baryons and DM, are evolved from distinct
primordial density and velocity power spectra as predicted by early-universe
physics. We first demonstrate that such two-component simulations require an
unconventional match between force and mass resolution (i.e. force softening on
at least the mean particle separation scale). Otherwise, the growth on any
scale is not correctly recovered because of a spurious coupling between the two
species at the smallest scales. With these simulations, we then demonstrate how
the primordial differences in the clustering of baryons and DM are
progressively diminished over time. In particular, we explicitly show how the
BAO signature is damped in the spatial distribution of baryons and imprinted in
that of DM. This is a rapid process, yet it is still not fully completed at low
redshifts. On large scales, the overall shape of the correlation function of
baryons and DM differs by 2% at z = 9 and by 0.2% at z = 0. The differences in
the amplitude of the BAO peak are approximately a factor of 5 larger: 10% at z
= 9 and 1% at z = 0. These discrepancies are, however, smaller than effects
expected to be introduced by galaxy formation physics in both the shape of the
power spectrum and in the BAO peak, and are thus unlikely to be detected given
the precision of the next generation of galaxy surveys. Hence, our results
validate the standard practice of modelling the observed galaxy distribution
using predictions for the total mass clustering in the Universe.Comment: 9 pages, 6 figures. Replaced with version published in MNRA
The One-Loop Matter Bispectrum in the Effective Field Theory of Large Scale Structures
Given the importance of future large scale structure surveys for delivering
new cosmological information, it is crucial to reliably predict their
observables. The Effective Field Theory of Large Scale Structures (EFTofLSS)
provides a manifestly convergent perturbative scheme to compute the clustering
of dark matter in the weakly nonlinear regime in an expansion in , where is the wavenumber of interest and is the
wavenumber associated to the nonlinear scale. It has been recently shown that
the EFTofLSS matches to level the dark matter power spectrum at redshift
zero up to Mpc and Mpc at one
and two loops respectively, using only one counterterm that is fit to data.
Similar results have been obtained for the momentum power spectrum at one loop.
This is a remarkable improvement with respect to former analytical techniques.
Here we study the prediction for the equal-time dark matter bispectrum at one
loop. We find that at this order it is sufficient to consider the same
counterterm that was measured in the power spectrum. Without any remaining free
parameter, and in a cosmology for which is smaller than in the
previously considered cases (), we find that the prediction from
the EFTofLSS agrees very well with -body simulations up to Mpc, given the accuracy of the measurements, which is of order a few
percent at the highest 's of interest. While the fit is very good on average
up to Mpc, the fit performs slightly worse on
equilateral configurations, in agreement with expectations that for a given
maximum , equilateral triangles are the most nonlinear.Comment: 39 pages, 12 figures; v2: JCAP published version, improved numerical
data, added explanation and clarification
Noiseless Gravitational Lensing Simulations
The microphysical properties of the DM particle can, in principle, be
constrained by the properties and abundance of substructures in DM halos, as
measured through strong gravitational lensing. Unfortunately, there is a lack
of accurate theoretical predictions for the lensing signal of substructures,
mainly because of the discreteness noise inherent to N-body simulations. Here
we present Recursive-TCM, a method that is able to provide lensing predictions
with an arbitrarily low discreteness noise, without any free parameters or
smoothing scale. This solution is based on a novel way of interpreting the
results of N-body simulations, where particles simply trace the evolution and
distortion of Lagrangian phase-space volume elements. We discuss the advantages
of this method over the widely used cloud-in-cells and adaptive-kernel
smoothing density estimators. Applying the new method to a cluster-sized DM
halo simulated in warm and cold DM scenarios, we show how the expected
differences in their substructure population translate into differences in the
convergence and magnification maps. We anticipate that our method will provide
the high-precision theoretical predictions required to interpret and fully
exploit strong gravitational lensing observations.Comment: 13 pages, 13 figures. Updated fig 12, references adde
Precision modelling of the matter power spectrum in a Planck-like Universe
We use a suite of high-resolution N-body simulations and state-of-the-art perturbation theory to improve the code halofit, which predicts the nonlinear matter power spectrum. We restrict attention to parameters in the vicinity of the Planck Collaboration’s best fit. On large-scales (k≲ 0.07 h Mpc−1), our model evaluates the 2-loop calculation from the Multi-point Propagator Theory of Bernardeau et al. (2012). On smaller scales (k≳ 0.7 h Mpc−1), we transition to a smoothing-spline-fit model, that characterises the differences between the Takahashi et al. (2012) recalibration of halofit2012 and our simulations. We use an additional suite of simulations to explore the response of the power spectrum to variations in the cosmological parameters. In particular, we examine: the time evolution of the dark energy equation of state (w0, wa); the matter density Ωm; the physical densities of CDM and baryons (ωc, ωb); and the primordial power spectrum amplitude As, spectral index ns, and its running α. We construct correction functions, which improve halofit’s dependence on cosmological parameters. Our newly calibrated model reproduces all of our data with ≲ 1% precision. Including various systematic errors, such as choice of N-body code, resolution, and through inspection of the scaled second order derivatives, we estimate the accuracy to be ≲ 3% over the hyper-cube: w0 ∈ { − 1.05, −0.95}, wa ∈ { − 0.4, 0.4}, Ωm, 0 ∈ {0.21, 0.4}, ωc ∈ {0.1, 0.13}, ωb ∈ {2.0, 2.4}, ns ∈ {0.85, 1.05}, As ∈ {1.72 × 10−9, 2.58 × 10−9}, α ∈ { − 0.2, 0.2} up to k = 9.0 h Mpc−1 and out to z = 3. Outside of this range the model reverts to halofit2012. We release all power spectra data with the C-code NGenHalofit at: https://[email protected]/ngenhalofitteam/ngenhalofitpublic.git
The effects of halo alignment and shape on the clustering of galaxies
We investigate the effects of halo shape and its alignment with larger scale
structure on the galaxy correlation function. We base our analysis on the
galaxy formation models of Guo et al., run on the Millennium Simulations. We
quantify the importance of these effects by randomizing the angular positions
of satellite galaxies within haloes, either coherently or individually, while
keeping the distance to their respective central galaxies fixed. We find that
the effect of disrupting the alignment with larger scale structure is a ~2 per
cent decrease in the galaxy correlation function around r=1.8 Mpc/h. We find
that sphericalizing the ellipsoidal distributions of galaxies within haloes
decreases the correlation function by up to 20 per cent for r<1 Mpc/h and
increases it slightly at somewhat larger radii. Similar results apply to power
spectra and redshift-space correlation functions. Models based on the Halo
Occupation Distribution, which place galaxies spherically within haloes
according to a mean radial profile, will therefore significantly underestimate
the clustering on sub-Mpc scales. In addition, we find that halo assembly bias,
in particular the dependence of clustering on halo shape, propagates to the
clustering of galaxies. We predict that this aspect of assembly bias should be
observable through the use of extensive group catalogues.Comment: 8 pages, 6 figures. Accepted for publication in MNRAS. Minor changes
relative to v1. Note: this is an revised and considerably extended
resubmission of http://arxiv.org/abs/1110.4888; please refer to the current
version rather than the old on
Matched filter optimization of kSZ measurements with a reconstructed cosmological flow field
We develop and test a new statistical method to measure the kinematic
Sunyaev-Zel'dovich (kSZ) effect. A sample of independently detected clusters is
combined with the cosmic flow field predicted from a galaxy redshift survey in
order to derive a matched filter that optimally weights the kSZ signal for the
sample as a whole given the noise involved in the problem. We apply this
formalism to realistic mock microwave skies based on cosmological -body
simulations, and demonstrate its robustness and performance. In particular, we
carefully assess the various sources of uncertainty, cosmic microwave
background primary fluctuations, instrumental noise, uncertainties in the
determination of the velocity field, and effects introduced by miscentring of
clusters and by uncertainties of the mass-observable relation (normalization
and scatter). We show that available data (\plk\ maps and the MaxBCG catalogue)
should deliver a detection of the kSZ. A similar cluster catalogue
with broader sky coverage should increase the detection significance to . We point out that such measurements could be binned in order to
study the properties of the cosmic gas and velocity fields, or combined into a
single measurement to constrain cosmological parameters or deviations of the
law of gravity from General Relativity.Comment: 17 pages, 10 figures, 3 tables. Submitted to MNRAS. Comments are
welcome
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