197 research outputs found
The Impact of Wrong Assumptions in BAO Reconstruction
The process of density field reconstruction enhances the statistical power of
distance scale measurements using baryon acoustic oscillations (BAO). During
this process a fiducial cosmology is assumed in order to convert sky
coordinates and redshifts into distances; fiducial bias and
redshift-space-distortion parameters are also assumed in this procedure. We
analytically assess the impact of incorrect cosmology and bias assumptions on
the post-reconstruction power spectra using low-order Lagrangian perturbation
theory, deriving general expressions for the incorrectly reconstructed spectra.
We find that the BAO peak location appears to shift only by a negligible amount
due to wrong assumptions made during reconstruction. However, the shape of the
BAO peak and the quadrupole amplitude can be affected by such errors (at the
percent- and five-percent-level respectively), which potentially could cause
small biases in parameter inference for future surveys; we outline solutions to
such complications.Comment: 18 pages, 3 figures; comments welcome. v2 matches JCAP accepted
versio
The Shift of the Baryon Acoustic Oscillation Scale: A Simple Physical Picture
A shift of the baryon acoustic oscillation (BAO) scale to smaller values than
predicted by linear theory was observed in simulations. In this paper, we try
to provide an intuitive physical understanding of why this shift occurs,
explaining in more pedagogical detail earlier perturbation theory calculations.
We find that the shift is mainly due to the following physical effect. A
measurement of the BAO scale is more sensitive to regions with long wavelength
overdensities than underdensities, because (due to non-linear growth and bias)
these overdense regions contain larger fluctuations and more tracers and hence
contribute more to the total correlation function. In overdense regions the BAO
scale shrinks because such regions locally behave as positively curved closed
universes, and hence a smaller scale than predicted by linear theory is
measured in the total correlation function. Other effects which also contribute
to the shift are briefly discussed. We provide approximate analytic expressions
for the non-linear shift including a brief discussion of biased tracers and
explain why reconstruction should entirely reverse the shift. Our expressions
and findings are in agreement with simulation results, and confirm that
non-linear shifts should not be problematic for next-generation BAO
measurements.Comment: 10 pages, replaced with version accepted by Phys. Rev.
A bias to CMB lensing measurements from the bispectrum of large-scale structure
The rapidly improving precision of measurements of gravitational lensing of
the Cosmic Microwave Background (CMB) also requires a corresponding increase in
the precision of theoretical modeling. A commonly made approximation is to
model the CMB deflection angle or lensing potential as a Gaussian random field.
In this paper, however, we analytically quantify the influence of the
non-Gaussianity of large-scale structure lenses, arising from nonlinear
structure formation, on CMB lensing measurements. In particular, evaluating the
impact of the non-zero bispectrum of large-scale structure on the relevant CMB
four-point correlation functions, we find that there is a bias to estimates of
the CMB lensing power spectrum. For temperature-based lensing reconstruction
with CMB Stage-III and Stage-IV experiments, we find that this lensing power
spectrum bias is negative and is of order one percent of the signal. This
corresponds to a shift of multiple standard deviations for these upcoming
experiments. We caution, however, that our numerical calculation only evaluates
two of the largest bias terms and thus only provides an approximate estimate of
the full bias. We conclude that further investigation into lensing biases from
nonlinear structure formation is required and that these biases should be
accounted for in future lensing analyses.Comment: 15+19 pages, 9 figures. Comments welcom
Reconstructing Small Scale Lenses from the Cosmic Microwave Background Temperature Fluctuations
Cosmic Microwave Background (CMB) lensing is a powerful probe of the matter
distribution in the Universe. The standard quadratic estimator, which is
typically used to measure the lensing signal, is known to be suboptimal for
low-noise polarization data from next-generation experiments. In this paper we
explain why the quadratic estimator will also be suboptimal for measuring
lensing on very small scales, even for measurements in temperature where this
estimator typically performs well. Though maximum likelihood methods could be
implemented to improve performance, we explore a much simpler solution,
revisiting a previously proposed method to measure lensing which involves a
direct inversion of the background gradient. An important application of this
simple formalism is the measurement of cluster masses with CMB lensing. We find
that directly applying a gradient inversion matched filter to simulated lensed
images of the CMB can tighten constraints on cluster masses compared to the
quadratic estimator. While the difference is not relevant for existing surveys,
for future surveys it can translate to significant improvements in mass
calibration for distant clusters, where galaxy lensing calibration is
ineffective due to the lack of enough resolved background galaxies.
Improvements can be as large as for a cluster at and a
next-generation CMB experiment with 1K-arcmin noise, and over an order of
magnitude for lower noise levels. For future surveys, this simple
matched-filter or gradient inversion method approaches the performance of
maximum likelihood methods, at a fraction of the computational cost.Comment: 11 pages, 7 figure
Improving small-scale CMB lensing reconstruction
Over the past decade, the gravitational lensing of the Cosmic Microwave
Background (CMB) has become a powerful tool for probing the matter distribution
in the Universe. The standard technique used to reconstruct the CMB lensing
signal employs the quadratic estimator (QE) method, which has recently been
shown to be suboptimal for lensing measurements on very small scales in
temperature and polarization data. We implement a simple, more optimal method
for the small-scale regime, which involves taking the direct inverse of the
background gradient. We derive new techniques to make continuous maps of
lensing using this "Gradient-Inversion" (GI) method and validate our method
with simulated data, finding good agreement with predictions. For idealized
simulations of lensing cross- and autospectra that neglect foregrounds, we
demonstrate that our method performs significantly better than previous
quadratic estimator methods in temperature; at , it reduces errors
on the lensing auto-power spectrum by a factor of for both idealized
CMB-S4 and Simons Observatory-like experiments and by a factor of
for cross-correlations of CMB-S4-like lensing reconstruction and the true
lensing field. We caution that the level of the neglected small-scale
foreground power, while low in polarization, is very high in temperature;
though we briefly outline foreground mitigation methods, further work on this
topic is required. Nevertheless, our results show the future potential for
improved small-scale CMB lensing measurements, which could provide stronger
constraints on cosmological parameters and astrophysics at high redshifts
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