arXiv subjects

Constant Auclair

Publications and source records attributed to Constant Auclair.

4 recordsLinked to original sources

arXiv2026

Separation of polarized dust emission in Planck observations with Scattering Transforms

Polarized dust emission is a major astrophysical foreground contaminant of the cosmic microwave background polarization (CMB), which must be accurately measured to look for the faint primordial polarization B-modes of inflationary origin. The available maps to date, obtained from Planck space mission data, are noise-dominated in the high Galactic latitude regions that are most relevant for CMB observations. The goal of this work is to obtain better dust polarization maps from Planck observations, by exploiting both the dependence between polarization and total intensity, as well as the non-Gaussian filamentary structure of the dust emission. To this end, we use scattering transforms, which provide a stable and interpretable representation of complex non-Gaussian textures, allowing for a data-driven analysis approach requiring no explicit priors on dust. The analysis is performed locally on Cartesian patches of sky, where Stokes linear polarization parameters, redefined in a local reference frame, are modeled as the sum of a signal of interest and a nuisance term. Using multiple realizations of the random nuisance term, we recover the polarized dust maps by minimizing a composite objective function that enforces multiple statistical constraints in scattering space. The proposed algorithm reconstructs maps of polarized dust emission whose statistics are consistent with those expected from the Planck data once random nuisance realizations are added. This is confirmed in a validation test using a high signal-to-noise sky region as a test case. Comparisons with existing dust polarization maps and models show that our approach better recovers small-scale polarized dust emission, and that our reconstructed power and cross-spectra closely match those of the dust polarization maps. A second set of maps that deterministically reproduce the features of the dust polarized emission is also produced.

astro-ph.CO↗

arXiv2024

Comparing the morphology of molecular clouds without supervision

Molecular clouds show complex structures reflecting their non-linear dynamics. Many studies investigating the bridge between their morphology and physical properties have shown the value of non-Gaussian higher-order statistics in capturing physical information. Yet, as this bridge is usually characterized in the supervised world of simulations, transferring it to observations can be hazardous, especially when the discrepancy between simulations and observations remains unknown. In this paper, we aim to identify relevant summary statistics, directly from the observation data. To do so, we developed a test to compare the informative power of two sets of summary statistics for a given unlabeled dataset. Contrary to supervised approaches, this test does not require knowledge of any class label or parameter associated with the data. Instead, it evaluates and compares the degeneracy levels of the summary statistics based on a notion of statistical compatibility. We applied this test to column density maps of 14 nearby molecular clouds observed by Herschel and iteratively compared different sets of typical summary statistics. We show that a standard Gaussian description of these clouds is highly degenerate but can be substantially improved when being estimated on the logarithm of the maps. This illustrates that low-order statistics, when properly used, remain very powerful. We further show that such descriptions still exhibit a small quantity of degeneracies, some of which are lifted by the higher-order statistics provided by reduced wavelet scattering transforms. These degeneracies quantitatively differ between observations and state-of-the-art simulations of dense cloud collapse, and they are not present for logFBM models. Finally, we show how to cooperatively use the summary statistics identified to build a morphological distance, which is evaluated visually and gives convincing results.

astro-ph.GA↗

arXiv2023

Separation of dust emission from the Cosmic Infrared Background in Herschel observations with Wavelet Phase Harmonics

The low brightness dust emission at high Galactic latitude is of interest to study the interplay between physical processes in shaping the structure of the interstellar medium (ISM), as well as to statistically characterize dust emission as a foreground to the Cosmic Microwave Background (CMB). Progress in this avenue of research have been hampered by the difficulty of separating the dust emission from the Cosmic Infrared Background (CIB). We demonstrate that dust and CIB may be effectively separated based on their different structure on the sky and use the separation to characterize the structure of diffuse dust emission on angular scales where CIB is a significant component in terms of power. We use scattering transform statistics, the Wavelet Phase Harmonics (WPH), to perform a statistical component separation using Herschel SPIRE observations. This component separation is done only from observational data using non-Gaussian properties as a lever arm, and is done at a single 250 microns frequency. This method, that we validate on mock data, gives us access to non-Gaussian statistics of the interstellar dust and an output dust map essentially free from CIB contamination. Our statistical modelling characterizes the non-Gaussian structure of the diffuse ISM down to the smallest scales observed by Herschel. We recover the power-law shape of the dust power spectrum up to a wavenumber of 2 arcmin$^{-1}$ where the dust signal represents 2 percent of the total power. The output dust map reveals coherent structures at the smallest scales which were hidden by the CIB anisotropies. It opens new observational perspectives on the formation of structure in the diffuse ISM which we discuss with reference to past work. We have succeeded to perform a statistical separation from observational data only at a single frequency by using non-Gaussian statistics.

astro-ph.GA↗

arXiv2022

Generative Models of Multi-channel Data from a Single Example -- Application to Dust Emission

The quest for primordial $B$-modes in the cosmic microwave background has emphasized the need for refined models of the Galactic dust foreground. Here, we aim at building a realistic statistical model of the multi-frequency dust emission from a single example. We introduce a generic methodology relying on microcanonical gradient descent models conditioned by an extended family of wavelet phase harmonic (WPH) statistics. To tackle the multi-channel aspect of the data, we define cross-WPH statistics, quantifying non-Gaussian correlations between maps. Our data-driven methodology could apply to various contexts, and we have updated the software PyWPH, on which this work relies, accordingly. Applying this to dust emission maps built from a magnetohydrodynamics simulation, we construct and assess two generative models of: 1) a $(I, E, B)$ multi-observable input, 2) a $\{I_ν\}_ν$ multi-frequency input. The samples exhibit consistent features compared to the original maps. A statistical analysis of 1) shows that the power spectra, distributions of pixels, and Minkowski functionals are captured to a good extent. We analyze 2) by fitting the spectral energy distribution (SED) of both the synthetic and original maps with a modified blackbody (MBB) law. The maps are equally well fitted, and a comparison of the MBB parameters shows that our model succeeds in capturing the spatial variations of the SED from the data. Besides the perspectives of this work for dust emission modeling, the introduction of cross-WPH statistics opens a new avenue to characterize non-Gaussian interactions across different maps, which we believe will be fruitful for astrophysics.

astro-ph.CO↗