Description of turbulent dynamics in the interstellar medium: Multifractal microcanonical analysis

Author:

Rashidi A.,Yahia H.ORCID,Bontemps S.ORCID,Schneider N.,Bonne L.,Hennebelle P.,Scholtys J.,Attuel G.,Turiel A.ORCID,Simon R.ORCID,Cailly A.,Zebadua A.,Cherif A.,Lacroix C.,Martin M.,El Aouni A.,Sakka C.,Maji S. K.

Abstract

We present significant improvements to our previous work on noise reduction in 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 l2-lp, with p > 0 variable and apply it to a larger set of molecular clouds using Herschel 250 μm data in order to demonstrate their wide range of application. In the 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.

Funder

German Reseach Foundation

Agence Nationale de la Recherche

Deutsche Forschungsgemeinschaft

Innovation Lab

Publisher

EDP Sciences

Reference79 articles.

1. From filamentary clouds to prestellar cores to the stellar IMF: Initial highlights from theHerschelGould Belt Survey

2. André P., Di Francesco J., Ward-Thompson D., et al. 2014, in Protostars and Planets VI, eds. Beuther H., Klessen R. S., Dullemond C. P., & Henning T. (Tucson: University of Arizona Press), 27

3. Characterizing interstellar filaments withHerschelin IC 5146

4. Optimization with Sparsity-Inducing Penalties

5. Badri H. 2015, PhD Thesis, Université de Bordeaux, France

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3