Description of turbulent dynamics in the interstellar medium: Multifractal microcanonical analysis: II. Sparse filtering of Herschel observation maps and visualization of filamentary structures at different length scales

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Hauptverfasser: Rashidi, A., Yahia, H., Bontemps, S., Schneider, N., Bonne, L., Hennebelle, P., Scholtys, J., Attuel, G., Turiel, A., Simon, R., Cailly, A., Zebadua, A., Cherif, A., Lacroix, C., Martin, M., Aouni, A. El, Sakka, C., Maji, S. K.
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Veröffentlicht: 2024
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author Rashidi, A.
Yahia, H.
Bontemps, S.
Schneider, N.
Bonne, L.
Hennebelle, P.
Scholtys, J.
Attuel, G.
Turiel, A.
Simon, R.
Cailly, A.
Zebadua, A.
Cherif, A.
Lacroix, C.
Martin, M.
Aouni, A. El
Sakka, C.
Maji, S. K.
author_facet Rashidi, A.
Yahia, H.
Bontemps, S.
Schneider, N.
Bonne, L.
Hennebelle, P.
Scholtys, J.
Attuel, G.
Turiel, A.
Simon, R.
Cailly, A.
Zebadua, A.
Cherif, A.
Lacroix, C.
Martin, M.
Aouni, A. El
Sakka, C.
Maji, S. K.
contents We present significant improvements to our previous work on noise reduction in {\sl Herschel} observation maps by defining sparse filtering tools capable of handling, in a unified formalism, a significantly improved noise reduction as well as a deconvolution in order to reduce effects introduced by the limited instrumental response (beam). We implement greater flexibility by allowing a wider choice of parsimonious priors in the noise-reduction process. More precisely, we introduce a sparse filtering and deconvolution approach approach of type $l^2$-$l^p$, with $p > 0$ variable and apply it to a larger set of molecular clouds using {\sl Herschel} 250 $μ$m data in order to demonstrate their wide range of application. In the {\sl Herschel} data, we are able to use this approach to highlight extremely fine filamentary structures and obtain singularity spectra that tend to show a significantly less $\log$-normal behavior and a filamentary nature in the less dense regions. We also use high-resolution adaptive magneto-hydrodynamic simulation data to assess the quality of deconvolution in such a simulated beaming framework.
format Preprint
id arxiv_https___arxiv_org_abs_2406_00893
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Description of turbulent dynamics in the interstellar medium: Multifractal microcanonical analysis: II. Sparse filtering of Herschel observation maps and visualization of filamentary structures at different length scales
Rashidi, A.
Yahia, H.
Bontemps, S.
Schneider, N.
Bonne, L.
Hennebelle, P.
Scholtys, J.
Attuel, G.
Turiel, A.
Simon, R.
Cailly, A.
Zebadua, A.
Cherif, A.
Lacroix, C.
Martin, M.
Aouni, A. El
Sakka, C.
Maji, S. K.
Astrophysics of Galaxies
85-02
We present significant improvements to our previous work on noise reduction in {\sl Herschel} observation maps by defining sparse filtering tools capable of handling, in a unified formalism, a significantly improved noise reduction as well as a deconvolution in order to reduce effects introduced by the limited instrumental response (beam). We implement greater flexibility by allowing a wider choice of parsimonious priors in the noise-reduction process. More precisely, we introduce a sparse filtering and deconvolution approach approach of type $l^2$-$l^p$, with $p > 0$ variable and apply it to a larger set of molecular clouds using {\sl Herschel} 250 $μ$m data in order to demonstrate their wide range of application. In the {\sl Herschel} data, we are able to use this approach to highlight extremely fine filamentary structures and obtain singularity spectra that tend to show a significantly less $\log$-normal behavior and a filamentary nature in the less dense regions. We also use high-resolution adaptive magneto-hydrodynamic simulation data to assess the quality of deconvolution in such a simulated beaming framework.
title Description of turbulent dynamics in the interstellar medium: Multifractal microcanonical analysis: II. Sparse filtering of Herschel observation maps and visualization of filamentary structures at different length scales
topic Astrophysics of Galaxies
85-02
url https://arxiv.org/abs/2406.00893