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Benjamin D. Wandelt

Publications and source records attributed to Benjamin D. Wandelt.

At least 109 records · Page 6Linked to original sources

Making maps of cosmological parameters

We provide a fast algorithm to diagnose any directional dependence in the cosmological parameters by calculating maps of local cosmological parameter estimates and their joint errors. The technique implements a fast quadratic estimator technique based on Wiener filtering and convolution of the sky with a patch shape. It uses only three map-resolution spherical harmonic transforms per parameter and applies to any data set with full sky or a partial sky coverage. We apply this method to Planck SMICA-2015 and obtain fluctuation map for six cosmological parameters. Our estimate shows that the Planck data is consistent with a single global value of the cosmological parameters and is not influenced by any severe local contaminations. This method is applicable also to other angular or 3D data sets of future missions to scrutinize any local variation in the cosmological parameters.

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FSD: Frequency Space Differential measurement of CMB spectral distortions

Although the Cosmic Microwave Background agrees with a perfect blackbody spectrum within the current experimental limits, it is expected to exhibit certain spectral distortions with known spectral properties. We propose a new method, Frequency Space Differential (FSD) to measure the spectral distortions in the CMB spectrum by using the inter-frequency differences of the brightness temperature. The difference between the observed CMB temperature at different frequencies must agree with the frequency derivative of the blackbody spectrum, in the absence of any distortion. However, in the presence of spectral distortions, the measured inter-frequency differences would also exhibit deviations from blackbody which can be modeled for known sources of spectral distortions like $y\,\&\,μ$. Our technique uses FSD information for the CMB blackbody, $y$, $μ$ or any other sources of spectral distortions to model the observed signal. Successful application of this method in future CMB missions can provide an alternative method to extract spectral distortion signals and can potentially make it feasible to measure spectral distortions without an internal blackbody calibrator.

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Bayesian delensing of CMB temperature and polarization

We develop the first algorithm able to jointly compute the maximum {\it a posteriori} estimate of the Cosmic Microwave Background (CMB) temperature and polarization fields, the gravitational potential by which they are lensed, and cosmological parameters such as the tensor-to-scalar ratio, $r$. This is an important step towards sampling from the joint posterior probability function of these quantities, which, assuming Gaussianity of the CMB fields and lensing potential, contains all available cosmological information and would yield theoretically optimal constraints. Attaining such optimal constraints will be crucial for next-generation CMB surveys like CMB-S4, where limits on $r$ could be improved by factors of a few over currently used sub-optimal quadratic estimators. The maximization procedure described here depends on a newly developed lensing algorithm, which we term \textsc{LenseFlow}, and which lenses a map by solving a system of ordinary differential equations. This description has conceptual advantages, such as allowing us to give a simple non-perturbative proof that the lensing determinant is equal to unity in the weak-lensing regime. The algorithm itself maintains this property even on pixelized maps, which is crucial for our purposes and unique to \textsc{LenseFlow} as compared to other lensing algorithms we have tested. It also has other useful properties such as that it can be trivially inverted (i.e. delensing) for the same computational cost as the forward operation, and can be used to compute lensing adjoint, Jacobian, and Hessian operators. We test and validate the maximization procedure on flat-sky simulations covering up to 600\,deg$^2$ with non-uniform noise and masking.

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Statistical simulations of the dust foreground to CMB polarization

The characterization of the dust polarization foreground to the Cosmic Microwave Background (CMB) is a necessary step towards the detection of the B-mode signal associated with primordial gravitational waves. We present a method to simulate maps of polarized dust emission on the sphere, similarly to what is done for the CMB anisotropies. This method builds on the understanding of Galactic polarization stemming from the analysis of Planck data. It relates the dust polarization sky to the structure of the Galactic magnetic field and its coupling with interstellar matter and turbulence. The Galactic magnetic field is modelled as a superposition of a mean uniform field and a random component with a power-law power spectrum of exponent $α_{\rm M}$. The model parameters are constrained to fit the power spectra of dust polarization EE, BB and TE measured using Planck data. We find that the slopes of the E and B power spectra of dust polarization are matched for $α_{\rm M} = -2.5$. The model allows us to compute multiple realizations of the Stokes Q and U maps for different realizations of the random component of the magnetic field, and to quantify the variance of dust polarization spectra for any given sky area outside of the Galactic plane. The simulations reproduce the scaling relation between the dust polarization power and the mean total dust intensity including the observed dispersion around the mean relation. We also propose a method to carry out multi-frequency simulations including the decorrelation measured recently by Planck, using a given covariance matrix of the polarization maps. These simulations are well suited to optimize component separation methods and to quantify the confidence with which the dust and CMB B-modes can be separated in present and future experiments. We also provide an astrophysical perspective on our modeling of the dust polarization spectra.

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Wiener filter reloaded: fast signal reconstruction without preconditioning

We present a high performance solution to the Wiener filtering problem via a formulation that is dual to the recently developed messenger technique. This new dual messenger algorithm, like its predecessor, efficiently calculates the Wiener filter solution of large and complex data sets without preconditioning and can account for inhomogeneous noise distributions and arbitrary mask geometries. We demonstrate the capabilities of this scheme in signal reconstruction by applying it on a simulated cosmic microwave background (CMB) temperature data set. The performance of this new method is compared to that of the standard messenger algorithm and the preconditioned conjugate gradient (PCG) approach, using a series of well-known convergence diagnostics and their processing times, for the particular problem under consideration. This variant of the messenger algorithm matches the performance of the PCG method in terms of the effectiveness of reconstruction of the input angular power spectrum and converges smoothly to the final solution. The dual messenger algorithm outperforms the standard messenger and PCG methods in terms of execution time, as it runs to completion around 2 and 3-4 times faster than the respective methods, for the specific problem considered.

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Void profile from Planck lensing potential map

We use the lensing potential map from Planck CMB lensing reconstruction analysis and the "Public Cosmic Void Catalog" to measure the stacked void lensing potential. In this profile, four parameters are needed to describe the shape of voids with different characteristic radii $R_V$. However, we have found that after reducing the background noise by subtracting the average background, there is a residue lensing power left in the data. The inclusion of the environment shifting parameter, $γ_V$, is necessary to get a better fit to the data with the residue lensing power. We divide the voids into two redshift bins: cmass1 ($0.45 < z < 0.5$) and cmass2 ($0.5 < z < 0.6$). Our best-fit parameters are $α= 1.989\pm0.149$, $β= 12.61\pm0.56$, $δ_c=-0.697\pm0.025$, $R_S/R_V=1.039\pm0.030$, $γ_v=(-7.034\pm0.150) \times 10^{-2}$ for the cmass1 sample with 123 voids and $α= 1.956\pm0.165$, $β= 12.91\pm0.60$, $δ_c=-0.673\pm0.027$, $R_S/R_V=1.115\pm0.032$, $γ_v=(-4.512\pm0.114) \times 10^{-2}$ for the cmass2 sample with 393 voids at 68% C.L. The addition of the environment parameter is consistent with the conjecture that the Sloan Digital Sky Survey voids reside in an underdense region.

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Constraints on Cosmology and Gravity from the Dynamics of Voids

The Universe is mostly composed of large and relatively empty domains known as cosmic voids, whereas its matter content is predominantly distributed along their boundaries. The remaining material inside them, either dark or luminous matter, is attracted to these boundaries and causes voids to expand faster and to grow emptier over time. Using the distribution of galaxies centered on voids identified in the Sloan Digital Sky Survey and adopting minimal assumptions on the statistical motion of these galaxies, we constrain the average matter content $Ω_\mathrm{m}=0.281\pm0.031$ in the Universe today, as well as the linear growth rate of structure $f/b=0.417\pm0.089$ at median redshift $\bar{z}=0.57$, where $b$ is the galaxy bias ($68\%$ C.L.). These values originate from a percent-level measurement of the anisotropic distortion in the void-galaxy cross-correlation function, $\varepsilon = 1.003\pm0.012$, and are robust to consistency tests with bootstraps of the data and simulated mock catalogs within an additional systematic uncertainty of half that size. They surpass (and are complementary to) existing constraints by unlocking cosmological information on smaller scales through an accurate model of nonlinear clustering and dynamics in void environments. As such, our analysis furnishes a powerful probe of deviations from Einstein's general relativity in the low-density regime which has largely remained untested so far. We find no evidence for such deviations in the data at hand.

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Cosmological parameter constraints from CMB lensing with cosmic voids

We investigate the potential of using cosmic voids as a probe to constrain cosmological parameters through the gravitational lensing effect of the cosmic microwave background (CMB) and make predictions for the next generation surveys. By assuming the detection of a series of $\approx 5 - 10$ voids along a line of sight within a square-degree patch of the sky, we found that they can be used to break the degeneracy direction of some of the cosmological parameter constraints (for example $ω_b$ and $Ω_Λ$) in comparison with the constraints from random CMB skies with the same size area for a survey with extensive integration time. This analysis is based on our current knowledge of the average void profile and analytical estimates of the void number function. We also provide combined cosmological parameter constraints between a sky patch where series of voids are detected and a patch without voids (a randomly selected patch). The full potential of this technique relies on an accurate determination of the void profile to $\approx 10$% level. For a small-area CMB observation with extensive integration time and a high signal-to-noise ratio, CMB lensing with such series of voids will provide a complementary route to cosmological parameter constraints to the CMB observations. Example of parameter constraints with a series of five voids on a $1.0^{\circ} \times 1.0^{\circ}$ patch of the sky are $100ω_b = 2.20 \pm 0.27$, $ω_c = 0.120 \pm 0.022$, $Ω_Λ= 0.682 \pm 0.078$, $Δ_{\mathcal{R}}^2 = \left(2.22 \pm 7.79\right) \times 10^{-9}$, $n_s = 0.962 \pm 0.097$ and $τ= 0.925 \pm 1.747$ at 68% C.L.

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Bayesian semi-blind component separation for foreground removal in interferometric 21-cm observations

We present in this paper a new Bayesian semi-blind approach for foreground removal in observations of the 21-cm signal with interferometers. The technique, which we call HIEMICA (HI Expectation-Maximization Independent Component Analysis), is an extension of the Independent Component Analysis (ICA) technique developed for two-dimensional (2D) CMB maps to three-dimensional (3D) 21-cm cosmological signals measured by interferometers. This technique provides a fully Bayesian inference of power spectra and maps and separates the foregrounds from signal based on the diversity of their power spectra. Only relying on the statistical independence of the components, this approach can jointly estimate the 3D power spectrum of the 21-cm signal and, the 2D angular power spectrum and the frequency dependence of each foreground component, without any prior assumptions about foregrounds. This approach has been tested extensively by applying it to mock data from interferometric 21-cm intensity mapping observations under idealized assumptions of instrumental effects. We also discuss the impact when the noise properties are not known completely. As a first step toward solving the 21 cm power spectrum analysis problem we compare the semi-blind HIEMICA technique with the commonly used Principal Component Analysis (PCA). Under the same idealized circumstances the proposed technique provides significantly improved recovery of the power spectrum. This technique can be applied straightforwardly to all 21-cm interferometric observations, including epoch of reionization measurements, and can be extended to single-dish observations as well.

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Probing cosmology and gravity with redshift-space distortions around voids

Cosmic voids in the large-scale structure of the Universe affect the peculiar motions of objects in their vicinity. Although these motions are difficult to observe directly, the clustering pattern of their surrounding tracers in redshift space is influenced in a unique way. This allows to investigate the interplay between densities and velocities around voids, which is solely dictated by the laws of gravity. With the help of $N$-body simulations and derived mock-galaxy catalogs we calculate the average density fluctuations around voids identified with a watershed algorithm in redshift space and compare the results with the expectation from general relativity and the $Λ$CDM model. We find linear theory to work remarkably well in describing the dynamics of voids. Adopting a Bayesian inference framework, we explore the full posterior of our model parameters and forecast the achievable accuracy on measurements of the growth rate of structure and the geometric distortion through the Alcock-Paczynski effect. Systematic errors in the latter are reduced from $\sim15\%$ to $\sim5\%$ when peculiar velocities are taken into account. The relative parameter uncertainties in galaxy surveys with number densities comparable to the SDSS MAIN (CMASS) sample probing a volume of $1h^{-3}{\rm Gpc}^3$ yield $σ_{f/b}\left/(f/b)\right.\sim2\%$ ($20\%$) and $σ_{D_AH}/D_AH\sim0.2\%$ ($2\%$), respectively. At this level of precision the linear-theory model becomes systematics dominated, with parameter biases that fall beyond these values. Nevertheless, the presented method is highly model independent; its viability lies in the underlying assumption of statistical isotropy of the Universe.

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Real-space density profile reconstruction of stacked voids

We present a non-parametric, model-independent method to reconstruct the spherical density profiles of void stacks in real space, without redshift-space distortions. Our method uses the expected spherical symmetry of stacked voids to build the shape of the spherical density profile of cosmic voids in real space without any assumption about the cosmological model. We test the reconstruction algorithm with both a toy model and a full dark matter simulation. We present the result for the simulation: the reconstruction of the spherical density profile for a simulated stacked void in real space. We also present a first application of the algorithm to reconstruct real cosmic void stacks density profiles in real space from the Sloan Digital Sky Survey (Sutter et al. 2012b). We discuss capabilities of the algorithm and possible future improvements. Reconstructed density profiles from real voids open the way to the study of the spherically averaged dynamical structure of voids.

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Counting voids to probe dark energy

We show that the number of observed voids in galaxy redshift surveys is a sensitive function of the equation of state of dark energy. Using the Fisher matrix formalism we find the error ellipses in the $w_0-w_a$ plane when the equation of state of dark energy is assumed to be of the form $w_{CPL}(z)=w_0 +w_a z/(1+z)$. We forecast the number of voids to be observed with the ESA Euclid satellite and the NASA WFIRST mission, taking into account updated details of the surveys to reach accurate estimates of their power. The theoretical model for the forecast of the number of voids is based on matches between abundances in simulations and the analytical prediction. To take into account the uncertainties within the model, we marginalize over its free parameters when calculating the Fisher matrices. The addition of the void abundance constraints to the data from Planck, HST and supernova survey data noticeably tighten the $w_0-w_a$ parameter space. We thus quantify the improvement in the constraints due to the use of voids and demonstrate that the void abundance is a sensitive new probe for the dark energy equation of state.

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Bayesian inference on the sphere beyond statistical isotropy

We present a general method for Bayesian inference of the underlying covariance structure of random fields on a sphere. We employ the Bipolar Spherical Harmonic (BipoSH) representation of general covariance structure on the sphere. We illustrate the efficacy of the method as a principled approach to assess violation of statistical isotropy (SI) in the sky maps of Cosmic Microwave Background (CMB) fluctuations. SI violation in observed CMB maps arise due to known physical effects such as Doppler boost and weak lensing; yet unknown theoretical possibilities like cosmic topology and subtle violations of the cosmological principle, as well as, expected observational artefacts of scanning the sky with a non-circular beam, masking, foreground residuals, anisotropic noise, etc. We explicitly demonstrate the recovery of the input SI violation signals with their full statistics in simulated CMB maps. Our formalism easily adapts to exploring parametric physical models with non-SI covariance, as we illustrate for the inference of the parameters of a Doppler boosted sky map. Our approach promises to provide a robust quantitative evaluation of the evidence for SI violation related anomalies in the CMB sky by estimating the BipoSH spectra along with their complete posterior.

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Using cosmic voids to distinguish f(R) gravity in future galaxy surveys

We use properties of void populations identified in $N$-body simulations to forecast the ability of upcoming galaxy surveys to differentiate models of f(R) gravity from \lcdm~cosmology. We analyze multiple simulation realizations, which were designed to mimic the expected number densities, volumes, and redshifts of the upcoming Euclid satellite and a lower-redshift ground-based counterpart survey, using the public {\tt VIDE} toolkit. We examine void abundances, ellipicities, radial density profiles, and radial velocity profiles at redshifts 1.0 and 0.43. We find that stronger f(R) coupling strengths eliminates small voids and produces voids up to $\sim 20\%$ larger in radius, leading to a significant tilt in the void number function. Additionally, under the influence of modified gravity, voids at all scales tend to be measurably emptier with correspondingly higher compensation walls. The velocity profiles reflect this, showing increased outflows inside voids and increased inflows outside voids. Using the void number function as an example, we forecast that future surveys can constrain the modified gravity coupling strength to $\sim 3 \times 10^{-5}$ using voids.

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The Linear Perturbation Theory of Reionization in Position-Space: Cosmological Radiative Transfer Along the Light-Cone

The linear perturbation theory of inhomogeneous reionization (LPTR) has been developed as an analytical tool for predicting the global ionized fraction and large-scale power spectrum of ionized density fluctuations during reionization. In the original formulation of the LPTR, the ionization balance and radiative transfer equations are linearized and solved in Fourier space. However, the LPTR's approximation to the full solution of the radiative transfer equation is not straightforward to interpret, since the latter is most intuitively conceptualized in position space. To bridge the gap between the LPTR and the language of numerical radiative transfer, we present a new, equivalent, position-space formulation of the LPTR that clarifies the approximations it makes and facilitates its interpretation. We offer a comparison between the LPTR and the excursion-set model of reionization (ESMR), and demonstrate the built-in capability of the LPTR to explore a wide range of reionization scenarios, and to go beyond the ESMR in exploring scenarios involving X-rays.

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Using hybrid GPU/CPU kernel splitting to accelerate spherical convolutions

We present a general method for accelerating by more than an order of magnitude the convolution of pixelated functions on the sphere with a radially-symmetric kernel. Our method splits the kernel into a compact real-space component and a compact spherical harmonic space component. These components can then be convolved in parallel using an inexpensive commodity GPU and a CPU. We provide models for the computational cost of both real-space and Fourier space convolutions and an estimate for the approximation error. Using these models we can determine the optimum split that minimizes the wall clock time for the convolution while satisfying the desired error bounds. We apply this technique to the problem of simulating a cosmic microwave background (CMB) anisotropy sky map at the resolution typical of the high resolution maps produced by the Planck mission. For the main Planck CMB science channels we achieve a speedup of over a factor of ten, assuming an acceptable fractional rms error of order 1.e-5 in the power spectrum of the output map.

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sCOLA: The N-body COLA Method Extended to the Spatial Domain

We present sCOLA -- an extension of the N-body COmoving Lagrangian Acceleration (COLA) method to the spatial domain. Similar to the original temporal-domain COLA, sCOLA is an N-body method for solving for large-scale structure in a frame that is comoving with observers following trajectories calculated in Lagrangian Perturbation Theory. Incorporating the sCOLA method in an N-body code allows one to gain computational speed by capturing the gravitational potential from the far field using perturbative techniques, while letting the N-body code solve only for the near field. The far and near fields are completely decoupled, effectively localizing gravity for the N-body side of the code. Thus, running an N-body code for a small simulation volume using sCOLA can reproduce the results of a standard N-body run for the same small volume embedded inside a much larger simulation. We demonstrate that sCOLA can be safely combined with the original temporal-domain COLA. sCOLA can be used as a method for performing zoom-in simulations. It also allows N-body codes to be made embarrassingly parallel, thus allowing for efficiently tiling a volume of interest using grid computing. Moreover, sCOLA can be useful for cheaply generating large ensembles of accurate mock halo catalogs required to study galaxy clustering. Surveys that will benefit the most are ones with large aspect ratios, such as pencil-beam surveys, where sCOLA can easily capture the effects of large-scale transverse modes without the need to substantially increase the simulated volume. As an illustration of the method, we present proof-of-concept zoom-in simulations using a freely available sCOLA-based N-body code.

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Testing cosmic geometry without dynamic distortions using voids

We propose a novel technique to probe the expansion history of the Universe based on the clustering statistics of cosmic voids. In particular, we compute their two-point statistics in redshift space on the basis of realistic mock galaxy catalogs and apply the Alcock-Paczynski test. In contrast to galaxies, we find void auto-correlations to be marginally affected by peculiar motions, providing a model-independent measure of cosmological parameters without systematics from redshift-space distortions. Because only galaxy-galaxy and void-galaxy correlations have been considered in these types of studies before, the presented method improves both statistical and systematic uncertainties on the product of angular diameter distance and Hubble rate, furnishing the potentially cleanest probe of cosmic geometry available to date.

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