Making maps of cosmic microwave background polarization for B-mode studies: the POLARBEAR example

Analysis of cosmic microwave background (CMB) datasets typically requires some filtering of the raw time-ordered data. For instance, in the context of ground-based observations, filtering is frequently used to minimize the impact of low frequency noise, atmospheric contributions and/or scan synchronous signals on the resulting maps. In this work we have explicitly constructed a general filtering operator, which can unambiguously remove any set of unwanted modes in the data, and then amend the map-making procedure in order to incorporate and correct for it. We show that such an approach is mathematically equivalent to the solution of a problem in which the sky signal and unwanted modes are estimated simultaneously and the latter are marginalized over. We investigated the conditions under which this amended map-making procedure can render an unbiased estimate of the sky signal in realistic circumstances. We then discuss the potential implications of these observations on the choice of map-making and power spectrum estimation approaches in the context of B-mode polarization studies. Specifically, we have studied the effects of time-domain filtering on the noise correlation structure in the map domain, as well as impact it may haveon the performance of the popular pseudo-spectrum estimators. We conclude that although maps produced by the proposed estimators arguably provide the most faithful representation of the sky possible given the data, they may not straightforwardly lead to the best constraints on the power spectra of the underlying sky signal and special care may need to be taken to ensure this is the case. By contrast, simplified map-makers which do not explicitly correct for time-domain filtering, but leave it to subsequent steps in the data analysis, may perform equally well and be easier and faster to implement. We focused on polarization-sensitive measurements targeting the B-mode component of the CMB signal and apply the proposed methods to realistic simulations based on characteristics of an actual CMB polarization experiment, POLARBEAR. Our analysis and conclusions are however more generally applicable

Forecasting performance of CMB experiments in the presence of complex foreground contaminations

We present a new, semianalytic framework for estimating the level of residuals present in cosmic microwave background (CMB) maps derived from multifrequency CMB data and forecasting their impact on cosmological parameters. The data are assumed to contain non-negligible signals of astrophysical and/or Galactic origin, which we clean using a parametric component separation technique. We account for discrepancies between the foreground model assumed during the separation procedure and the true one, allowing for differences in scaling laws and/or their spatial variations. Our estimates and their uncertainties include both systematic and statistical effects and are averaged over the instrumental noise and CMB signal realizations. The framework can be further extended to account self-consistently for existing uncertainties in the foreground models. We demonstrate and validate the framework on simple study cases which aim at estimating the tensor-to-scalar ratio, r. The proposed approach is computationally efficient permitting an investigation of hundreds of setups and foreground models on a single CPU

Iterative map-making with two-level preconditioning for polarized cosmic microwave background data sets. A worked example for ground-based experiments

An estimation of the sky signal from streams of Time Ordered Data (TOD) acquired by Cosmic Microwave Background (cmb) experiments is one of the most important steps in the context of cmb data analysis referred to as the map-making problem. The continuously growing cmb data sets render the cmb map-making problem more challenging in terms of computational cost and memory in particular in the context of ground based experiments. In this context, we study a novel class of the Preconditioned Conjugate Gradient (PCG) solvers which invoke two-level preconditioners. We compare them against PCG solvers commonly used in the map-making context considering their precision and time-to-solution. We compare these new methods on realistic, simulated data sets reflecting the characteristics of current and forthcoming cmb ground-based experiment. We develop an embarrassingly parallel implementation of the approach where each processor performs a sequential map-making for a subset of the TOD. We find that considering the map level residuals the new class of solvers permits achieving tolerance of up to 3 orders of magnitude better than the standard approach, where the residual level often saturates before convergence is reached. This corresponds to an important improvement in the precision of recovered power spectra in particular on the largest angular scales. The new method also typically requires fewer iterations to reach a required precision and thus shorter runtimes for a single map-making solution. However, the construction of an appropriate two-level preconditioner can be as costly as a single standard map-making run. Nevertheless, if the same problem needs to be solved multiple times, e.g., as in Monte Carlo simulations, this cost has to be incurred only once, and the method should be competitive not only as far as its precision but also its performance is concerned

The Simons Observatory: Galactic Science Goals and Forecasts

Observing in six frequency bands from 27 to 280 GHz over a large sky area, the Simons Observatory (SO) is poised to address many questions in Galactic astrophysics in addition to its principal cosmological goals. In this work, we provide quantitative forecasts on astrophysical parameters of interest for a range of Galactic science cases. We find that SO can: constrain the frequency spectrum of polarized dust emission at a level of $\Delta\beta_d \lesssim 0.01$ and thus test models of dust composition that predict that $\beta_d$ in polarization differs from that measured in total intensity; measure the correlation coefficient between polarized dust and synchrotron emission with a factor of two greater precision than current constraints; exclude the non-existence of exo-Oort clouds at roughly 2.9$\sigma$ if the true fraction is similar to the detection rate of giant planets; map more than 850 molecular clouds with at least 50 independent polarization measurements at 1 pc resolution; detect or place upper limits on the polarization fractions of CO(2-1) emission and anomalous microwave emission at the 0.1% level in select regions; and measure the correlation coefficient between optical starlight polarization and microwave polarized dust emission in $1^\circ$ patches for all lines of sight with $N_{\rm H} \gtrsim 2\times10^{20}$ cm$^{-2}$. The goals and forecasts outlined here provide a roadmap for other microwave polarization experiments to expand their scientific scope via Milky Way astrophysics.Comment: Submitted to AAS journals. 33 pages, 10 figure

Structured reporting for fibrosing lung disease: a model shared by radiologist and pulmonologist

Objectives: To apply the Delphi exercise with iterative involvement of radiologists and pulmonologists with the aim of defining a structured reporting template for high-resolution computed tomography (HRCT) of patients with fibrosing lung disease (FLD). Methods: The writing committee selected the HRCT criteria\ue2\u80\u94the Delphi items\ue2\u80\u94for rating from both radiology panelists (RP) and pulmonology panelists (PP). The Delphi items were first rated by RPs as \ue2\u80\u9cessential\ue2\u80\u9d, \ue2\u80\u9coptional\ue2\u80\u9d, or \ue2\u80\u9cnot relevant\ue2\u80\u9d. The items rated \ue2\u80\u9cessential\ue2\u80\u9d by < 80% of the RP were selected for the PP rating. The format of reporting was rated by both RP and PP. Results: A total of 42 RPs and 12 PPs participated to the survey. In both Delphi round 1 and 2, 10/27 (37.7%) items were rated \ue2\u80\u9cessential\ue2\u80\u9d by more than 80% of RP. The remaining 17/27 (63.3%) items were rated by the PP in round 3, with 2/17 items (11.7%) rated \ue2\u80\u9cessential\ue2\u80\u9d by the PP. PP proposed additional items for conclusion domain, which were rated by RPs in the fourth round. Poor consensus was observed for the format of reporting. Conclusions: This study provides a template for structured report of FLD that features essential items as agreed by expert thoracic radiologists and pulmonologists

Making maps of cosmic microwave background polarization for B-mode studies: The POLARBEAR example

Analysis of cosmic microwave background (CMB) datasets typically requires some filtering of the raw time-ordered data. For instance, in the context of ground-based observations, filtering is frequently used to minimize the impact of low frequency noise, atmospheric contributions and/or scan synchronous signals on the resulting maps. In this work we have explicitly constructed a general filtering operator, which can unambiguously remove any set of unwanted modes in the data, and then amend the map-making procedure in order to incorporate and correct for it. We show that such an approach is mathematically equivalent to the solution of a problem in which the sky signal and unwanted modes are estimated simultaneously and the latter are marginalized over. We investigated the conditions under which this amended map-making procedure can render an unbiased estimate of the sky signal in realistic circumstances. We then discuss the potential implications of these observations on the choice of map-making and power spectrum estimation approaches in the context of B-mode polarization studies. Specifically, we have studied the effects of time-domain filtering on the noise correlation structure in the map domain, as well as impact it may haveon the performance of the popular pseudo-spectrum estimators. We conclude that although maps produced by the proposed estimators arguably provide the most faithful representation of the sky possible given the data, they may not straightforwardly lead to the best constraints on the power spectra of the underlying sky signal and special care may need to be taken to ensure this is the case. By contrast, simplified map-makers which do not explicitly correct for time-domain filtering, but leave it to subsequent steps in the data analysis, may perform equally well and be easier and faster to implement. We focused on polarization-sensitive measurements targeting the B-mode component of the CMB signal and apply the proposed methods to realistic simulations based on characteristics of an actual CMB polarization experiment, POLARBEAR. Our analysis and conclusions are however more generally applicable. \ua9 ESO, 2017

Prolonged higher dose methylprednisolone vs. conventional dexamethasone in COVID-19 pneumonia: a randomised controlled trial (MEDEAS)

Dysregulated systemic inflammation is the primary driver of mortality in severe COVID-19 pneumonia. Current guidelines favor a 7-10-day course of any glucocorticoid equivalent to dexamethasone 6 mg·day-1. A comparative RCT with a higher dose and a longer duration of intervention was lacking

Réalisation de cartes à haute fidélité de la polarisation du fond diffus cosmologique à partir des deux premières saisons de l'expérience POLARBEAR ainsi que leur exploitation statistique

Cette thèse s'intéresse au problème de la production des cartes du fond diffus cosmologique (CMB) en présence du filtrage. Les observations du CMB ont constamment affiné notre compréhension de l'univers au cours des dernières décennies. La caractérisation de la composante rotationnelle de sa polarisation, les modes-B, devrait apporter des informations précieuses sur l'univers primordial et récent, ainsi que sur la physique fondamentale.Afin d'extraire ces contraintes uniques à partir du faible signal des modes B, la qualité et la taillé des données des expériences CMB ont invariablement augmenté. Leur traitement pose de sérieuses difficultés. La reconstruction de la carte du ciel observée réduit par plusieurs ordres de grandeur le volume des données, tout en essayant de préserver l'information cosmologique. Dans ce processus, les données brutes sont généralement filtrées afin d'éliminer les signaux parasites d'origines instrumentales ou astrophysiques. Cette thèse illustre le formalisme permettant d'effectuer des opérations générales de filtrage et de les incorporer dans la procédure de cartographie. Les conditions réalistes dans lesquelles cette estimation non biaisée du ciel peut réussir sont également étudiées, à la fois de manière général et dans le contexte spécifique des expériences au sol. Ce nouveau formalisme a été implémenté dans un code, extrêmement parallélisé, pour la production des cartes. Il est capable de reconstruire le ciel observé de manière fidèle et de caractériser ses propriétés statistiques. La méthodologie et l'outil sont ensuite appliqués à la première et deuxième saison de POLARBEAR, une des expériences de premier plan dans la chasse aux modes-BThis thesis concerns the cosmic microwave background (CMB) map-making problem in the presence of filtering. The observations of the CMB kept refining our understanding of the universe over the past decades. The characterisation of its curl-like polarisation pattern - the so-called B-modes - is expected to convey invaluable information on both the primordial and the late universe as well as on fundamental physics.In order to extract these unique constraints from the faint B-mode signal, the quality and the size of CMB datasets have been constantly increasing, posing serious challenges for data analysis. The reconstruction of the map of the observed sky compresses by many orders of magnitude the data volume, white striving for preserving ail the cosmological information. In this process, the raw data are typically filtered in order to remove unwanted signais of instrumental or astrophysical origins. This thesis illustrates the formalism for performing general filtering operations and for incorporating them in the map-making procedure. The realistic circumstances under which this unbiased estimation of the sky signal can succeed are also investigated, both in general and in the specific context of ground-based experiments. This new formalism has been innplemented in a massively parallel map-making code, capable of producing high fidelity renditions of the sky as well as their detailed statistical characterisation. The methodology and the tool are then applied to the analysis of the first and second season data POLARBEAR, one of the leading experiments in the B-modes ques

D.: DSL Evolution through Composition

The use of domain specific languages (DSL), instead of general purpose languages introduces a number of advantages in software development even if could be problematic to maintain the DSL consistent with the evolution of the domain. Traditionally, to develop a compiler/interpreter from scratch but also to modify an existing compiler to support the novel DSL is a long and difficult task. We have developed Neverlang to simplify and speed up the development and maintenance of DSLs. The framework presented in this article not only allows to develop the syntax and the semantic of a new language from scratch but it is particularly focused on the reusability of the language definition. The interpreters/compilers produced with such a framework are modular and it is easy to add remove or modify their sections. This allows to modify the DSL definition in order to follow the evolution of the underneath domain. In this work, we explore the Neverlang framework and try out the adaptability of its language definition. 1