High precision simulations of weak lensing effect on Cosmic Microwave Background polarization

We study accuracy, robustness and self-consistency of pixel-domain simulations of the gravitational lensing effect on the primordial CMB anisotropies due to the large-scale structure of the Universe. In particular, we investigate dependence of the results precision on some crucial parameters of such techniques and propose a semi-analytic framework to determine their values so the required precision is a priori assured and the numerical workload simultaneously optimized. Our focus is on the B-mode signal but we discuss also other CMB observables, such as total intensity, T, and E-mode polarization, emphasizing differences and similarities between all these cases. Our semi-analytic considerations are backed up by extensive numerical results. Those are obtained using a code, nicknamed lenS2HAT -- for Lensing using Scalable Spherical Harmonic Transforms (S2HAT) -- which we have developed in the course of this work. The code implements a version of the pixel-domain approach of Lewis (2005) and permits performing the simulations at very high resolutions and data volumes, thanks to its efficient parallelization provided by the S2HAT library -- a parallel library for a calculation of the spherical harmonic transforms. The code is made publicly available.Comment: 20 pages, 14 figures, submitted to A&A, matches version accepted for publication in A&

Astrophysical foregrounds and primordial tensor-to-scalar ratio constraints from CMB B-mode polarization observations

We study the effects of astrophysical foregrounds on the ability of CMB B-mode polarization experiments to constrain the primordial tensor-to-scalar ratio, r. To clean the foreground contributions we use parametric, maximum likelihood component separation technique, and consider experimental setups optimized to render a minimal level of the foreground residuals in the recovered CMB map. We consider nearly full-sky observations, include two diffuse foreground components, dust and synchrotron, and study cases with and without calibration errors, spatial variability of the foreground properties, and partial or complete B-mode lensing signal removal. In all these cases we find that in the limit of very low noise level and in the absence of the intrumental or modeling systematic effects, the foreground residuals do not lead to a limit on the lowest detectable value of r. But the need to control the foreground residuals will play a major role in determining the minimal noise levels necessary to permit a robust detection of r < 0.1 and therefore in optimizing and forecasting the performance of the future missions. For current and proposed experiments noise levels, the foreground residuals are found non-negligible and potentially can affect our ability to set constraints on r. We also show how the constraints can be significantly improved on by restricting the post component separation processing to a smaller sky area. This procedure applied to a case of a COrE-like satellite mission is shown to result potentially in over an order of magnitude improvement in the detectable value of r. With sufficient knowledge of the experimental bandpasses as well as foreground component scaling laws, our conclusions are found to be independent on the assumed overall normalization of the foregrounds and only quantitatively depend on specific parametrizations assumed for the foreground components.Comment: 5 pages, 2 figure

Accelerating Cosmic Microwave Background map-making procedure through preconditioning

Estimation of the sky signal from sequences of time ordered data is one of the key steps in Cosmic Microwave Background (CMB) data analysis, commonly referred to as the map-making problem. Some of the most popular and general methods proposed for this problem involve solving generalised least squares (GLS) equations with non-diagonal noise weights given by a block-diagonal matrix with Toeplitz blocks. In this work we study new map-making solvers potentially suitable for applications to the largest anticipated data sets. They are based on iterative conjugate gradient (CG) approaches enhanced with novel, parallel, two-level preconditioners. We apply the proposed solvers to examples of simulated non-polarised and polarised CMB observations, and a set of idealised scanning strategies with sky coverage ranging from nearly a full sky down to small sky patches. We discuss in detail their implementation for massively parallel computational platforms and their performance for a broad range of parameters characterising the simulated data sets. We find that our best new solver can outperform carefully-optimised standard solvers used today by a factor of as much as 5 in terms of the convergence rate and a factor of up to $4$ in terms of the time to solution, and to do so without significantly increasing the memory consumption and the volume of inter-processor communication. The performance of the new algorithms is also found to be more stable and robust, and less dependent on specific characteristics of the analysed data set. We therefore conclude that the proposed approaches are well suited to address successfully challenges posed by new and forthcoming CMB data sets.Comment: 19 pages // Final version submitted to A&

Tentative Appraisal of Compatibility of Small-Scale CMB Anisotropy Detections in the Context of COBE-DMR-Normalized Open and Flat Λ\Lambda CDM Cosmogonies

Goodness-of-fit statistics are used to quantitatively establish the compatibility of CMB anisotropy predictions in a wide range of DMR-normalized, open and spatially-flat $\Lambda$, CDM cosmogonies with the set of all presently available small-scale CMB anisotropy detection data. Conclusions regarding model viability depend sensitively on the prescription used to account for the 1$\sigma$ uncertainty in the assumed value of the DMR normalization, except for low-density, $\Omega_0 \sim 0.3$ -- 0.4, open models which are compatible with the data for all prescriptions used. While large baryon-density (\Omega_B \gap 0.0175 h^{-2}), old (t_0 \gap 15 -- 16 Gyr), low-density ($\Omega_0 \sim 0.2$ -- 0.4), flat-$\Lambda$ models might be incompatible, no model is incompatible with the data for all prescriptions. In fact, some open models seem to fit the data better than should be expected, and this might be an indication that some error bars are mildly overconservative.Comment: 15 page PostScript file, including 6 included figures. Also available via anonymous ftp from ftp://astro.caltech.edu/users/kmg/chi.p

Spherical harmonic transform with GPUs

We describe an algorithm for computing an inverse spherical harmonic transform suitable for graphic processing units (GPU). We use CUDA and base our implementation on a Fortran90 routine included in a publicly available parallel package, S2HAT. We focus our attention on the two major sequential steps involved in the transforms computation, retaining the efficient parallel framework of the original code. We detail optimization techniques used to enhance the performance of the CUDA-based code and contrast them with those implemented in the Fortran90 version. We also present performance comparisons of a single CPU plus GPU unit with the S2HAT code running on either a single or 4 processors. In particular we find that use of the latest generation of GPUs, such as NVIDIA GF100 (Fermi), can accelerate the spherical harmonic transforms by as much as 18 times with respect to S2HAT executed on one core, and by as much as 5.5 with respect to S2HAT on 4 cores, with the overall performance being limited by the Fast Fourier transforms. The work presented here has been performed in the context of the Cosmic Microwave Background simulations and analysis. However, we expect that the developed software will be of more general interest and applicability

Python I, II, and III CMB Anisotropy Measurement Constraints on Open and Flat-Lambda CDM Cosmogonies

We use Python I, II, and III cosmic microwave background anisotropy data to constrain cosmogonies. We account for the Python beamwidth and calibration uncertainties. We consider open and spatially-flat-Lambda cold dark matter cosmogonies, with nonrelativistic-mass density parameter Omega_0 in the range 0.1--1, baryonic-mass density parameter Omega_B in the range (0.005--0.029) h^{-2}, and age of the universe t_0 in the range (10--20) Gyr. Marginalizing over all parameters but Omega_0, the combined Python data favors an open (spatially-flat-Lambda) model with Omega_0 simeq 0.2 (0.1). At the 2 sigma confidence level model normalizations deduced from the combined Python data are mostly consistent with those drawn from the DMR, UCSB South Pole 1994, ARGO, MAX 4 and 5, White Dish, and SuZIE data sets.Comment: 20 pages, 7 figures, accepted by Ap

Iterative destriping and photometric calibration for Planck-HFI, polarized, multi-detector map-making

We present an iterative scheme designed to recover calibrated I, Q, and U maps from Planck-HFI data using the orbital dipole due to the satellite motion with respect to the Solar System frame. It combines a map reconstruction, based on a destriping technique, juxtaposed with an absolute calibration algorithm. We evaluate systematic and statistical uncertainties incurred during both these steps with the help of realistic, Planck-like simulations containing CMB, foreground components and instrumental noise, and assess the accuracy of the sky map reconstruction by considering the maps of the residuals and their spectra. In particular, we discuss destriping residuals for polarization sensitive detectors similar to those of Planck-HFI under different noise hypotheses and show that these residuals are negligible (for intensity maps) or smaller than the white noise level (for Q and U Stokes maps), for l > 50. We also demonstrate that the combined level of residuals of this scheme remains comparable to those of the destriping-only case except at very low l where residuals from the calibration appear. For all the considered noise hypotheses, the relative calibration precision is on the order of a few 10e-4, with a systematic bias of the same order of magnitude.Comment: 18 pages, 21 figures. Match published versio

Accelerating Cosmic Microwave Background map-making procedure through preconditioning

Estimation of the sky signal from sequences of time ordered data is one of the key steps in Cosmic Microwave Background (CMB) data analysis, commonly referred to as the map-making problem. Some of the most popular and general methods proposed for this problem involve solving generalised least squares (GLS) equations with non-diagonal noise weights given by a block-diagonal matrix with Toeplitz blocks. In this work we study new map-making solvers potentially suitable for applications to the largest anticipated data sets. They are based on iterative conjugate gradient (CG) approaches enhanced with novel, parallel, two-level preconditioners. We apply the proposed solvers to examples of simulated non-polarised and polarised CMB observations, and a set of idealised scanning strategies with sky coverage ranging from nearly a full sky down to small sky patches. We discuss in detail their implementation for massively parallel computational platforms and their performance for a broad range of parameters characterising the simulated data sets. We find that our best new solver can outperform carefully-optimised standard solvers used today by a factor of as much as 5 in terms of the convergence rate and a factor of up to $4$ in terms of the time to solution, and to do so without significantly increasing the memory consumption and the volume of inter-processor communication. The performance of the new algorithms is also found to be more stable and robust, and less dependent on specific characteristics of the analysed data set. We therefore conclude that the proposed approaches are well suited to address successfully challenges posed by new and forthcoming CMB data sets.Comment: 19 pages // Final version submitted to A&

ARGO CMB Anisotropy Measurement Constraints on Open and Flat-Lambda CDM Cosmogonies

We use data from the ARGO cosmic microwave background (CMB) anisotropy experiment to constrain cosmogonies. We account for the ARGO beamwidth and calibration uncertainties, and marginalize over the offset removed from the data. Our derived amplitudes of the CMB anisotropy detected by the ARGO experiment are smaller than those derived previously. We consider open and spatially-flat-Lambda cold dark matter cosmogonies, with clustered-mass density parameter Omega_0 in the range 0.1-1, baryonic-mass density parameter Omega_B in the range (0.005-0.029)h^{-2}, and age of the universe t_0 in the range (10--20) Gyr. Marginalizing over all parameters but Omega_0, the ARGO data favors an open (spatially-flat-Lambda) model with Omega_0= 0.23 (0.1). However, these numerical values are model dependent. At the 2 sigma confidence level model normalizations deduced from the ARGO data are consistent with those drawn from the UCSB South Pole 1994, MAX 4+5, White Dish, and SuZIE data sets. The ARGO open model normalizations are also consistent with those deduced from the DMR data. However, for most spatially-flat-Lambda models the DMR normalizations are more than 2 sigma above the ARGO ones.Comment: 21 pages of latex. Uses aaspp4.sty. 8 figures included. ApJ in pres