arXiv subjects

Alessandro Carones

Publications and source records attributed to Alessandro Carones.

16 recordsLinked to original sources

arXiv2026

Combining Systematic Effects in CMB Polarization Experiments through map-based simulations: application to LiteBIRD's HWP non-idealities and detectors non-linearity

We quantify the impact of coupled instrumental systematics on next-generation CMB polarization experiments targeting primordial $B$-mode polarization, with a focus on the forthcoming \textit{LiteBIRD} satellite mission. We study the interplay between the non-linear response of Transition-Edge Sensor (TES) bolometers and Half-Wave Plate (HWP) non-idealities, in particular synchronous signals arising from differential emissivity. We develop a map-based formalism that captures the resulting intensity-to-polarization leakage by explicitly solving the binning map-making equations, avoiding the need for computationally expensive time-ordered data simulations. We apply this framework to \textit{LiteBIRD}, adopting its baseline scanning strategy and frequency configuration, and perform analyses at both single- and multi-frequency levels, including Galactic foregrounds and blind component separation. We find that while detector non-linearity and HWP non-idealities individually induce negligible bias on the tensor-to-scalar ratio $r$, their coupling can generate non-trivial contamination, driven by large signals such as the solar dipole and amplified in high-frequency channels by foreground leakage. From these results, we derive joint requirements on detector non-linearity and HWP differential emission, and discuss their implications for the instrument design and calibration strategy of \textit{LiteBIRD} and future CMB polarization missions targeting $r \lesssim 10^{-3}$.

astro-ph.CO↗

arXiv2026

Status and future development of the COSMOCal Project for absolute CMB polarization calibration

Cosmic Microwave Background (CMB) polarization measurements are pushing instrumental sensitivities to levels where calibration systematics become a dominant limitation. The large dynamic range between cosmological and Galactic emission prevents future experiments from relying only on diffuse sky measurements or standard celestial calibrators. To address this challenge, the COSmological Microwave Observations Calibrator (COSMOCal) project proposes an artificial calibration source deployed as a guest payload on a geostationary satellite, scheduled for launch by the Eutelsat group by 2030. This source will provide stable, well-characterized polarized microwave signals accessible to multiple ground-based observatories. In this work, we present the status of the project, the updated development timeline, and the refined scientific and technical requirements, defined with the observatories that plan to use this calibration source. Furthermore, we investigate the interplay between instrumental systematics and component separation in the presence of complex models of interstellar dust emission. We discuss in this paper how this can impact the recovery of the primordial signal, and whether residual calibration errors can degrade the performance of foreground cleaning algorithms.

astro-ph.IM↗

arXiv2026

BROOM: a python package for model-independent analysis of microwave astronomical data

We present BROOM, a new python package for the application of blind, minimum-variance component-separation techniques to microwave observations. The package enables the reconstruction of signals with known spectral energy distributions, such as the Cosmic Microwave Background (CMB), Sunyaev--Zeldovich distortions, or foreground moments, in both temperature and polarization through a suite of Internal Linear Combination (ILC) implementations, in the presence of astrophysical and instrumental contaminants. In addition, BROOM supports the blind reconstruction of coherent emission components with unknown covariance properties via a Generalized ILC (GILC) framework. Beyond component separation, the package provides tools to diagnose foreground complexity and to estimate residual contamination leaking into reconstructed maps across angular scales and sky regions. It also includes utilities to generate realistic microwave simulations for arbitrary CMB experiments and to compute angular power spectra of the resulting products. We present a comprehensive description and validation of the implemented pipelines in two representative experimental configurations: a full-sky satellite mission and a ground-based experiment. BROOM is publicly available, fully documented, and easily installable at https://github.com/alecarones/broom

astro-ph.CO↗

arXiv2026

Blind mitigation of foreground-induced biases on primordial $B$ modes for ground-based CMB experiments

Observations of the Cosmic Microwave Background (CMB) B-mode polarisation provide a unique probe of inflationary physics. Extracting a reliable constraint on the tensor-to-scalar ratio $r$ nonetheless demands stringent suppression of diffuse Galactic foregrounds, whose residuals can bias the inferred signal. This work introduces and evaluates two extensions of the Needlet Internal Linear Combination (NILC) framework aimed at reducing foreground-induced biases on $r$. The first extension implements the deprojection of selected foreground moments directly within the component-separation step. The second performs a likelihood-level marginalisation over residual foreground power using a data-driven template. Using Simons Observatory Small Aperture Telescope (SO-SAT) - like simulations, we show that both methods effectively control residual contamination, yielding unbiased estimates of $r$ and a consistent reconstruction of the lensing B-mode amplitude. These results indicate that enhanced foreground-mitigation strategies will be useful for next-generation CMB polarisation analyses seeking a robust detection of primordial B-modes.

astro-ph.CO↗

arXiv2025

Debiasing cosmological parameters from large-scale foreground contamination in Cosmic Microwave Background data

Current and future Cosmic Microwave Background (CMB) experiments aim to achieve high-precision reconstruction of the CMB polarization signal, with the most ambitious objective being the detection of primordial $B$ modes sourced by cosmic inflation. Given the expected low amplitude of the signal, its estimate-parametrized by the tensor-to-scalar ratio $r$-is highly susceptible to contamination from Galactic foreground residuals that remain after component separation. In this work, we introduce a model-independent procedure to construct a spectral template of residual foreground contamination in the observed angular power spectrum. Specifically, a cleaned multifrequency set of foreground-emission maps is blindly reconstructed from the observed data using the Generalized Needlet Internal Linear Combination (GNILC) technique. These maps are then combined with the weights adopted for CMB reconstruction, yielding an estimate of the spatial distribution of foreground residuals after component separation. The power spectrum of this estimated residual map is incorporated into the spectral model of the cosmological likelihood. We validate the proposed method using realistic simulations of a LiteBIRD-like experiment processed with two Internal Linear Combination (ILC) component-separation techniques, focusing on constraints on the tensor-to-scalar ratio. When the foreground contribution is not included in the model, the resulting $r$ posteriors are biased, irrespective of its input value, the assumed foreground model, or the adopted masking strategy. Conversely, when the residual template is included in the likelihood, the analysis yields unbiased estimates of $r$ for all considered cases, thereby demonstrating the robustness of the proposed procedure. The pipeline has been made publicly available as part of the BROOM Python package (https://github.com/alecarones/broom).

astro-ph.CO↗

arXiv2025

$B$-sure I: Minkowski functionals as robustness test for tensor-to-scalar ratio detection from CMB observations

The detection of primordial $B$-mode polarisation of the Cosmic Microwave Background (CMB) is a major observational goal in modern Cosmology, offering a potential window into inflationary physics through the measurement of the tensor-to-scalar ratio $r$. However, the presence of Galactic foregrounds poses significant challenges, possibly biasing the $r$ estimate. In this study we explore the viability of using Minkowski functionals (MFs) as a robustness test to validate a potential $r$ detection by identifying non-Gaussian features associated with foregrounds contamination. To do so, we simulate sky maps as observed by a LiteBIRD-like CMB experiment, with realistic instrumental and foregrounds modelling. The CMB $B$-mode signal is recovered through blind component separation algorithms, and the obtained (biased) value of $r$ is used to generate Gaussian realisation of CMB signal. Their MFs are then compared with those computed on maps contaminated by foreground residual left by component separation, looking for a detection of non-Gaussianity. Our results demonstrate that, with the experimental configuration considered here, MFs can not be reliably adopted as a robustness test of an eventual $r$ detection, as we find that in the majority of the cases MFs are not able to raise significant warnings about the non-Gaussianity induced by the presence of foreground residuals. In the most realistic and refined scenario we adopted, the test is able to flag non-Gaussianity in $\sim 26\%$ of the simulations, meaning that there is no warning on the biased tensor-to-scalar ratio in $\sim 74\%$ of cases. These results suggest that more advanced statistics than MFs must be considered to look for non-Gaussian signatures of foregrounds, in order to be able to perform reliable null tests in future CMB missions.

astro-ph.CO↗

arXiv2025

The Simons Observatory: Assessing the Impact of Dust Complexity on the Recovery of Primordial $B$-modes

We investigate how dust foreground complexity can affect measurements of the tensor-to-scalar ratio, $r$, in the context of the Simons Observatory, using a cross-spectrum component separation analysis. Employing a suite of simulations with realistic Galactic dust emission, we find that spatial variation in the dust frequency spectrum, parametrized by $\beta_d$, can bias the estimate for $r$ when modeled using a low-order moment expansion to capture this spatial variation. While this approach performs well across a broad range of dust complexity, the bias increases with more extreme spatial variation in dust frequency spectrum, reaching as high as $r\sim0.03$ for simulations with no primordial tensors and a spatial dispersion of $\sigma(\beta_d)\simeq0.3$ -- the most extreme case considered, yet still consistent with current observational constraints. This bias is driven by changes in the $\ell$-dependence of the dust power spectrum as a function of frequency that can mimic a primordial $B$-mode tensor signal. Although low-order moment expansions fail to capture the full effect when the spatial variations of $\beta_d$ become large and highly non-Gaussian, our results show that extended parametric methods can still recover unbiased estimates of $r$ under a wide range of dust complexities. We further find that the bias in $r$, at the highest degrees of dust complexity, is largely insensitive to the spatial structure of the dust amplitude and is instead dominated by spatial correlations between $\beta_d$ and dust amplitude, particularly at higher orders. If $\beta_d$ does spatially vary at the highest levels investigated here, we would expect to use more flexible foreground models to achieve an unbiased constraint on $r$ for the noise levels anticipated from the Simons Observatory.

astro-ph.CO↗

arXiv2025

The Simons Observatory: Quantifying the impact of beam chromaticity on large-scale B-mode science

The Simons Observatory (SO) Small Aperture Telescopes (SATs) will observe the Cosmic Microwave Background (CMB) temperature and polarization at six frequency bands. Within these bands, the angular response of the telescope (beam) is convolved with the instrument's spectral response (commonly called bandpass) and the signal from the sky, which leads to the band-averaged telescope beam response, which is sampled and digitized. The spectral properties of the band-averaged beam depend on the natural variation of the beam within the band, referred to as beam chromaticity. In this paper, we quantify the impact of the interplay of beam chromaticity and intrinsic frequency scaling from the various components that dominate the polarized sky emission on the tensor-to-scalar ratio, $r$, and foreground parameters. We do so by employing a parametric power-spectrum-based foreground component separation algorithm, namely BBPower, to which we provide beam-convolved time domain simulations performed with the beamconv software while assuming an idealized version of the SO SAT optics. We find a small, $0.02\sigma$, bias on $r$, due to beam chromaticity, which seems to mostly impact the dust spatial parameters, causing a maximum $0.77 \sigma$ bias on the dust $B$-mode spectra amplitude, $A_{d}$, when employing Gaussian foreground simulations. However, we find all parameter biases to be smaller than $1\sigma$ at all times, independently of the foreground model. This includes the case where we introduce additional uncertainty on the bandpass shape, which accounts for approximately half of the total allowed gain uncertainty, as estimated in previous work for the SO SATs.

astro-ph.CO↗

arXiv2024

How bad could it be? Modelling the 3D complexity of the polarised dust signal using moment expansion

The variation of the physical conditions across the three dimensions of our Galaxy is a major source of complexity for the modelling of the foreground signal facing the cosmic microwave background (CMB). In the present work, we demonstrate that the spin-moment expansion formalism provides a powerful framework to model and understand this complexity, with a special focus on that arising from variations of the physical conditions along each line-of-sight on the sky. We perform the first application of the moment expansion to reproduce a thermal dust model largely used by the CMB community, demonstrating its power as a minimal tool to compress, understand and model the information contained within any foreground model. Furthermore, we use this framework to produce new models of thermal dust emission containing the maximal amount of complexity allowed by the current data, remaining compatible with the observed angular power-spectra by the $Planck$ mission. By assessing the impact of these models on the performance of component separation methodologies, we conclude that the additional complexity contained within the third dimension could represent a significant challenge for future CMB experiments and that different component separation approaches are sensitive to different properties of the moments.

astro-ph.CO↗

arXiv2024

Optimizing blind reconstruction of CMB B-modes for future experiments

The detection of primordial polarization $B$ modes of the Cosmic Microwave Background (CMB) requires exquisite control of Galactic foreground contamination. The Needlet Internal Linear Combination (NILC) method has proven effective in reconstructing CMB $B$ modes without suffering from mis-modeling errors of Galactic emission. However, with the most complex foreground models, residual Galactic contamination from NILC is proved to bias, especially at large angular scales, the recovered CMB $B$ modes from simulated data of future CMB experiments. We therefore present two new extensions of NILC, Multi-Clustering NILC (MC-NILC) and optimized constrained Moment ILC (ocMILC), which allow to enhance foreground subtraction in the reconstructed CMB signal.

astro-ph.CO↗

arXiv2024

Optimization of foreground moment deprojection for semi-blind CMB polarization reconstruction

Upcoming Cosmic Microwave Background (CMB) experiments, aimed at measuring primordial CMB B-modes, require exquisite control of Galactic foreground contamination. Minimum-variance techniques, like the Needlet Internal Linear Combination (NILC), have proven effective in reconstructing the CMB polarization signal and mitigating foregrounds across diverse sky models without suffering from mismodelling errors. Still, residual contamination may bias the recovered CMB polarization at large angular scales when confronted with the most complex foreground scenarios. By adding constraints to NILC to deproject moments of the Galactic emission, the Constrained Moment ILC (cMILC) method has proven to enhance foreground subtraction, albeit with an associated increase in overall noise variance. Faced with this trade-off between foreground bias reduction and overall variance minimization, there is still no recipe on which moments to deproject and which are better suited for blind variance minimization. To address this, we introduce the optimized cMILC (ocMILC) pipeline, which performs full optimization of the required number and set of foreground moments to deproject, pivot parameter values, and deprojection coefficients across the sky and angular scales, depending on the actual sky complexity, available frequency coverage, and experiment sensitivity. The optimal number of deprojected moments, before paying significant noise penalty, is determined through a data diagnosis inspired by the Generalized NILC (GNILC) method. Validated on B-mode simulations of the PICO space mission concept with four challenging foreground models, ocMILC exhibits lower foreground contamination compared to NILC and cMILC at all angular scales, with limited noise penalty. This multi-layer optimization enables the ocMILC pipeline to achieve unbiased posteriors of the tensor-to-scalar ratio, regardless of foreground complexity.

astro-ph.CO↗

arXiv2023

Minkowski Functionals in $SO(3)$ for the spin-2 CMB polarisation field

The study of the angular power spectrum of Cosmic Microwave Background (CMB) anisotropies, both in intensity and in polarisation, has led to the tightest constraints on cosmological parameters. However, this statistical quantity is not sensitive to any deviation from Gaussianity and statistical isotropy in the CMB data. Minkowski Functionals (MFs) have been adopted as one of the most powerful statistical tools to study such deviations, since they characterise the topology and geometry of the field of interest. In this paper, we extend the application of MFs to CMB polarisation data by introducing a new formalism, where we lift the spin $2$ polarisation field to a scalar function in a higher-dimensional manifold: the group of rotations of the sphere, $SO(3)$. Such a function is defined as $f = Q \cos(2ψ) - U \sin(2ψ)$. We analytically obtain the expected values for the MFs of $f$ in the case of Gaussian isotropic polarisation maps. Furthermore, we present a new pipeline which estimates these MFs from input HEALPix polarisation maps. We apply it to CMB simulations in order to validate the theoretical results and the methodology. The pipeline is to be included in the publicly available Python package $\texttt{Pynkowski}$ available at https://github.com/javicarron/pynkowski.

astro-ph.CO↗

arXiv2022

Multi-Clustering Needlet-ILC for CMB B-modes component separation

The Cosmic Microwave Background (CMB) primordial B-modes signal is predicted to be much lower than the polarized Galactic emission (foregrounds) in any region of the sky pointing to the need for sophisticated component separation methods. Among them, the blind Needlet-ILC (NILC) has great relevance given our current poor knowledge of the B-modes foregrounds. However the expected level of spatial variability of the foreground spectral properties complicates the NILC subtraction of the Galactic contamination. In order to reach the ambitious targets of future CMB experiments, we therefore propose a novel extension of the NILC approach, the Multi-Clustering NILC (MC-NILC), which performs NILC variance minimization on separate regions of the sky (clusters) properly chosen to have similar spectral properties of the B-modes foregrounds emission. Clusters are identified thresholding the ratio of B-modes maps at two separate frequencies which is used as tracer of the spatial distribution of the spectral indices of the Galactic emission in B modes. We consider ratios either of simulated foregrounds-only B modes (ideal case) or of cleaned templates of Galactic emission obtained from realistic simulations. In this work we present an application of MC-NILC to the future LiteBIRD satellite, which targets the observation of both reionization and recombination peaks of the primordial B-modes angular power spectrum with a total error on the tensor-to-scalar ratio $\delta r < 0.001$. We show that MC-NILC provides a CMB solution with residual foregrounds and noise contamination that is significantly reduced with respect to NILC and lower than the primordial signal targeted by LiteBIRD at all angular scales for the ideal case and at the reionization peak for a realistic ratio. Thus, MC-NILC will represent a powerful method to mitigate B-modes foregrounds for future CMB polarization experiments.

astro-ph.CO↗

arXiv2022

Minkowski Functionals of CMB polarisation intensity with Pynkowski: theory and application to Planck and future data

The angular power spectrum of the Cosmic Microwave Background (CMB) anisotropies is a key tool to study the Universe. However, it is blind to the presence of non--Gaussianities and deviations from statistical isotropy, which instead can be detected with other statistics such as Minkowski Functionals (MFs). These tools have been applied to CMB temperature and $E$-mode anisotropies with no detection of deviations from Gaussianity and isotropy. In this work, we extend the MFs formalism to the CMB polarisation intensity, $P^2=Q^2+U^2$. We use the Gaussian Kinematic Formula to derive the theoretical predictions of MFs for Gaussian isotropic fields. We develop a software that computes MFs on $P^2$ HEALPix maps and apply it to simulations to verify the robustness of both theory and methodology. We then estimate MFs of $P^2$ maps from Planck, both in pixel space and needlet domain, comparing them with realistic simulations which include CMB and instrumental noise residuals. We find no significant deviations from Gaussianity or isotropy in Planck CMB polarisation intensity. However, MFs could play an important role in the analysis of CMB polarisation measurements from upcoming experiments with improved sensitivity. Therefore we forecast the ability of MFs applied to $P^2$ maps to detect much fainter non-Gaussian anisotropic signals than with Planck data for two future complementary experiments: the LiteBIRD satellite and the ground-based Simons Observatory. We publicly release the software to compute MFs in arbitrary scalar HEALPix maps as a fully-documented Python package called $\texttt{Pynkowski}$ (https://github.com/javicarron/pynkowski).

astro-ph.CO↗

arXiv2022

Analysis of NILC performance on B-modes data of sub-orbital experiments

The observation of primordial B-modes in the Cosmic Microwave Background (CMB) represents the main scientific goal of most of the future CMB experiments. This signal is predicted to be much lower than polarised Galactic emission (foregrounds) in any region of the sky pointing to the need for effective components separation methods, such as the Needlet-ILC (NILC). In this work, we explore the possibility of employing NILC for B-mode maps reconstructed from partial-sky data of sub-orbital experiments, addressing the complications that such an application yields: E-B leakage, needlet filtering and beam convolution. We consider two complementary simulated datasets from future experiments: the balloon-borne SWIPE telescope of the Large Scale Polarization Explorer, which targets the observation of both reionisation and recombination peaks of the primordial B-mode angular power spectrum, and the ground-based Small Aperture Telescope of Simons Observatory, which is designed to observe only the recombination bump. We assess the performance of two alternative techniques to correct for the CMB E-B leakage: the recycling technique (Liu et al. 2019) and the ZB method (Zhao & Baskaran 2010). We find that they both reduce the E-B leakage residuals at a negligible level given the sensitivity of the considered experiments, except for the recycling method in the SWIPE patch at $\ell < 20$. Thus, we implement two extensions of the pipeline, the iterative B-decomposition and the diffusive inpainting, which enable us to recover the input CMB B-mode power for $\ell \geq 5$. We demonstrate that needlet filtering and beam convolution do not affect the B-mode reconstruction. Finally, with an appropriate masking strategy, we find that NILC foregrounds subtraction allows to achieve sensitivities for the tensor-to-scalar ratio compatible to the targets of the considered CMB experiments.

astro-ph.CO↗

arXiv2022

In-flight polarization angle calibration for LiteBIRD: blind challenge and cosmological implications

We present a demonstration of the in-flight polarization angle calibration for the JAXA/ISAS second strategic large class mission, LiteBIRD, and estimate its impact on the measurement of the tensor-to-scalar ratio parameter, r, using simulated data. We generate a set of simulated sky maps with CMB and polarized foreground emission, and inject instrumental noise and polarization angle offsets to the 22 (partially overlapping) LiteBIRD frequency channels. Our in-flight angle calibration relies on nulling the EB cross correlation of the polarized signal in each channel. This calibration step has been carried out by two independent groups with a blind analysis, allowing an accuracy of the order of a few arc-minutes to be reached on the estimate of the angle offsets. Both the corrected and uncorrected multi-frequency maps are propagated through the foreground cleaning step, with the goal of computing clean CMB maps. We employ two component separation algorithms, the Bayesian-Separation of Components and Residuals Estimate Tool (B-SeCRET), and the Needlet Internal Linear Combination (NILC). We find that the recovered CMB maps obtained with algorithms that do not make any assumptions about the foreground properties, such as NILC, are only mildly affected by the angle miscalibration. However, polarization angle offsets strongly bias results obtained with the parametric fitting method. Once the miscalibration angles are corrected by EB nulling prior to the component separation, both component separation algorithms result in an unbiased estimation of the r parameter. While this work is motivated by the conceptual design study for LiteBIRD, its framework can be broadly applied to any CMB polarization experiment. In particular, the combination of simulation plus blind analysis provides a robust forecast by taking into account not only detector sensitivity but also systematic effects.

astro-ph.CO↗