Gaussian decomposition of $\ion{H}{i}$ surveys

Haud, U.; Kalberla, P. M. W.

doi:10.1051/0004-6361:20065796

Cited by 54 publications

(62 citation statements)

References 24 publications

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“…The energy equipartition assumption between thermal and turbulent kinetic energy is consistent with the turbulent velocity dispersions calculated for Galactic H i (Verschuur 2004;Haud & Kalberla 2007).…”

Section: Turbulence Setupsupporting

confidence: 81%

Formation of Cold Filamentary Structure From Wind-Blown Superbubbles

Ntormousi¹,

Burkert²,

Fierlinger³

et al. 2011

ApJ

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The expansion and collision of two wind-blown superbubbles is investigated numerically. Our models go beyond previous simulations of molecular cloud formation from converging gas flows by exploring this process with realistic flow parameters, sizes, and timescales. The superbubbles are blown by time-dependent winds and supernova explosions, calculated from population synthesis models. They expand into a uniform or turbulent diffuse medium. We find that dense, cold gas clumps and filaments form naturally in the compressed collision zone of the two superbubbles. Their shapes resemble the elongated, irregular structure of observed cold, molecular gas filaments, and clumps. At the end of the simulations, between 65% and 80% of the total gas mass in our simulation box is contained in these structures. The clumps are found in a variety of physical states, ranging from pressure equilibrium with the surrounding medium to highly underpressured clumps with large irregular internal motions and structures which are rotationally supported.

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Section: Turbulence Setupsupporting

confidence: 81%

Formation of Cold Filamentary Structure From Wind-Blown Superbubbles

Ntormousi¹,

Burkert²,

Fierlinger³

et al. 2011

ApJ

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“…In earlier papers of this series, we described the Gaussian decomposition of large H i 21-cm line surveys (Haud 2000, here-after Paper I) and the use of the obtained GCs for detecting of different observational and reductional problems , hereafter Paper II), for separating thermal phases in the interstellar medium (ISM; Haud & Kalberla 2007, hereafter Paper III) and for studying intermediate and highvelocity hydrogen clouds (IVCs and HVCs; Haud 2008, hereafter Paper IV). A detailed justification for the use of Gaussian decomposition in these studies was provided in Paper III.…”

Section: Introductionmentioning

confidence: 99%

Gaussian decomposition of $\ion{H}{i}$ surveys

Haud¹

2010

A&A

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Context. In the previous papers of this series, we decomposed all the H i 21-cm line profiles of the Leiden-Argentina-Bonn (LAB) database into Gaussian components (GCs), and studied the statistical distributions of the obtained GCs. Aims. Now we are interested in separating the "clouds" of similar closely spaced GCs from the general database of the components. In this paper we examine the most complicated case for our new cloud-finding algorithm -the clouds of very narrow GCs. Methods. To separate the clouds of similar GCs, we started with the single-link hierarchical clustering procedure in five-dimensional (longitude, latitude, velocity, GC width, and height) space, but made some modifications to accommodate it to the large number of components. We also used the requirement that each cloud may be represented at any observed sky position by only one GC and take the similarity of global properties of the merging clouds into account. We demonstrate that the proposed algorithm enables us to find the features in gas distribution, which are described by similar GCs. As a test, we applied the algorithm for finding the clouds of the narrowest H i 21-cm line components. Results. Using the full sky search for cold clouds, we easily detected the coldest known H i clouds and demonstrate that actually they are a part of a long narrow ribbon of cold clouds. We modeled these clouds as a part of a planar gas ring, then deduce their spatial placement and discuss their relation to supernova shells in the solar neighborhood. Many other narrow-lined H i structures are also found. We conclude that the proposed algorithm satisfactorily solves the posed task. In testing the algorithm, we found a long ribbon of very cold H i clouds and demonstrated that all the observed properties of this band of clouds are described very well by the planar ring model. Conclusions.We also guess that the study of the narrowest H i 21-cm line components may be a useful tool for finding the structure of neutral gas in solar neighborhood.

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“…Upper limits of the velocity-shears estimated for the three pairs (i.e. not corrected for projection effects) include the largest values ever measured in non-starforming regions, up to 780 km s −1 pc −1 : two velocity components separated by 3.5 km s −1 , a value of the order of the rms velocity dispersion of the CNM (Haud & Kalberla 2007), share an interface as thin as 4.5 mpc (in projection) with no shock signature nor density enhancement. Finally, the PdBI-structures are almost straight and their different position angles, P A = 60…”

Section: Milliparsec-scale Observations : Approaching the Dissipationmentioning

confidence: 93%

“…The non-thermal contributions to the total pressure are due to supersonic turbulence and magnetic fields, in rough equipartition, as shown by measurements of magnetic field intensity (Crutcher et al, 2010) and HI linewidths (Haud & Kalberla, 2007). The distribution of thermal pressures in the solar neighbourhood, inferred from [CI] fine-structure absorption lines towards nearby stars (Jenkins & Tripp, 2011) peaks at about P th /k ∼ 3×10 3 cm −3 K, with large fluctuations, up to a few 10 4 cm −3 K. It is interesting that the total non-thermal pressure in the Galactic plane is of the same order as the largest thermal pressure observed, suggesting that the non-thermal energy eventually and occasionally degrades into thermal energy.…”

Section: Thermal and Non-thermal Pressuresmentioning

confidence: 99%

Turbulence in the Diffuse Interstellar Medium

2011

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Abstract. The diffuse interstellar medium (ISM) hosts the first steps of interstellar chemistry and the seeds of dense structures. Since its turbulent pressure by far exceeds its thermal pressure, turbulence must play a prominent role in its evolution. Fed at galactic scales, turbulent energy cascades down to the dissipation scales, but as in both laboratory and atmospheric turbulence, it does so in an intermittent way : only a tiny fraction of the small-scales is fed by the turbulent cascade, so that dissipation occurs in bursts. In diffuse molecular clouds, where they can be observed, the signatures of intermittency are: (1) the non-Gaussian statistics of velocity increments, and (2) the existence of coherent structures of intense velocity-shear that appear to channel the large-scale turbulent energy down to milliparsec scales. Attempts at modelling the warm chemistry triggered in the diffuse ISM by bursts of turbulent dissipation are promising : in this framework, the so far unexplained molecular richness observed in this medium is naturally understood, in particular its CH + , HCO + and CO abundances. Turbulent dissipation is also likely at the origin of the H2 rotational line emission of the diffuse ISM and of a significant fraction of its [C ii] emission.

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Gaussian decomposition of $\ion{H}{i}$ surveys

Cited by 54 publications

References 24 publications

Formation of Cold Filamentary Structure From Wind-Blown Superbubbles

Formation of Cold Filamentary Structure From Wind-Blown Superbubbles

Gaussian decomposition of $\ion{H}{i}$ surveys

Turbulence in the Diffuse Interstellar Medium

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