Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userGraph-based interpretation of the Molecular Interstellar Medium Segmentation
89
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
We present a generalization of the Giant Molecular Cloud (GMC) identification problem based on cluster analysis. The method we designed, SCIMES (Spectral Clustering for Interstellar Molecular Emission Segmentation) considers the dendrogram of emission in the broader framework of graph theory and utilizes spectral clustering to find discrete regions with similar emission properties. For Galactic molecular cloud structures, we show that the characteristic volume and/or integrated CO luminosity are useful criteria to define the clustering, yielding emission structures that closely reproduce by-eye identification results. SCIMES performs best on well-resolved, high-resolution data, making it complementary to other available algorithms. Using 12CO(1-0) data for the Orion-Monoceros complex, we demonstrate that SCIMES provides robust results against changes of the dendrogram-construction parameters, noise realizations and degraded resolution. By comparing SCIMES with other cloud decomposition approaches, we show that our method is able to identify all canonical clouds of the Orion-Monoceros region, avoiding the over-division within high resolution survey data that represents a common limitation of several decomposition algorithms. The Orion-Monoceros objects exhibit hierarchies and size-line width relationships typical to the turbulent gas in molecular clouds, although the Scissors region deviates from this common description. SCIMES represents a significant step forward in moving away from pixel-based cloud segmentation towards a more physical-oriented approach, where virtually all properties of the ISM can be used for the segmentation of discrete objects.
rate research
Read More
The density structure of the interstellar medium (ISM) determines where stars form and release energy, momentum, and heavy elements, driving galaxy evolution. Density variations are seeded and amplified by gas motion, but the exact nature of this motion is unknown across spatial scale and galactic environment. Although dense star-forming gas likely emerges from a combination of instabilities, convergent flows, and turbulence, establishing the precise origin is challenging because it requires quantifying gas motion over many orders of magnitude in spatial scale. Here we measure the motion of molecular gas in the Milky Way and in nearby galaxy NGC 4321, assembling observations that span an unprecedented spatial dynamic range ($10^{-1}{-}10^3$ pc). We detect ubiquitous velocity fluctuations across all spatial scales and galactic environments. Statistical analysis of these fluctuations indicates how star-forming gas is assembled. We discover oscillatory gas flows with wavelengths ranging from $0.3{-}400$ pc. These flows are coupled to regularly-spaced density enhancements that likely form via gravitational instabilities. We also identify stochastic and scale-free velocity and density fluctuations, consistent with the structure generated in turbulent flows. Our results demonstrate that ISM structure cannot be considered in isolation. Instead, its formation and evolution is controlled by nested, interdependent flows of matter covering many orders of magnitude in spatial scale.
Magnetohydrodynamic (MHD) turbulence is a crucial component of the current paradigms of star formation, dynamo theory, particle transport, magnetic reconnection and evolution of structure in the interstellar medium (ISM) of galaxies. Despite the importance of turbulence to astrophysical fluids, a full theoretical framework based on solutions to the Navier-Stokes equations remains intractable. Observations provide only limited line-of-sight information on densities, temperatures, velocities and magnetic field strengths and therefore directly measuring turbulence in the ISM is challenging. A statistical approach has been of great utility in allowing comparisons of observations, simulations and analytic predictions. In this review article we address the growing importance of MHD turbulence in many fields of astrophysics and review statistical diagnostics for studying interstellar and interplanetary turbulence. In particular, we will review statistical diagnostics and machine learning algorithms that have been developed for observational data sets in order to obtain information about the turbulence cascade, fluid compressibility (sonic Mach number), and magnetization of fluid (Alfvenic Mach number). These techniques have often been tested on numerical simulations of MHD turbulence, which may include the creation of synthetic observations, and are often formulated on theoretical expectations for compressible magnetized turbulence. We stress the use of multiple techniques, as this can provide a more accurate indication of the turbulence parameters of interest. We conclude by describing several open-source tools for the astrophysical community to use when dealing with turbulence.
We present the detection and analysis of molecular hydrogen emission toward ten interstellar regions in the Large Magellanic Cloud. We examined low-resolution infrared spectral maps of twelve regions obtained with the Spitzer infrared spectrograph (IRS). The pure rotational 0--0 transitions of H$_2$ at 28.2 and 17.1${,rm mu m}$ are detected in the IRS spectra for ten regions. The higher level transitions are mostly upper limit measurements except for three regions, where a 3$sigma$ detection threshold is achieved for lines at 12.2 and 8.6${,rm mu m}$. The excitation diagrams of the detected H$_2$ transitions are used to determine the warm H$_2$ gas column density and temperature. The single-temperature fits through the lower transition lines give temperatures in the range $86-137,{rm K}$. The bulk of the excited H$_2$ gas is found at these temperatures and contributes $sim$5-17% to the total gas mass. We find a tight correlation of the H$_2$ surface brightness with polycyclic aromatic hydrocarbon and total infrared emission, which is a clear indication of photo-electric heating in photodissociation regions. We find the excitation of H$_2$ by this process is equally efficient in both atomic and molecular dominated regions. We also present the correlation of the warm H$_2$ physical conditions with dust properties. The warm H$_2$ mass fraction and excitation temperature show positive correlations with the average starlight intensity, again supporting H$_2$ excitation in photodissociation regions.
We discuss the absorption due to various constituents of the interstellar medium of M82 seen in moderately high resolution, high signal-to-noise ratio optical spectra of SN 2014J. Complex absorption from M82 is seen, at velocities 45 $le$ $v_{rm LSR}$ $le$ 260 km s$^{-1}$, for Na I, K I, Ca I, Ca II, CH, CH$^+$, and CN; many of the diffuse interstellar bands (DIBs) are also detected. Comparisons of the column densities of the atomic and molecular species and the equivalent widths of the DIBs reveal both similarities and differences in relative abundances, compared to trends seen in the ISM of our Galaxy and the Magellanic Clouds. Of the ten relatively strong DIBs considered here, six (including $lambda$5780.5) have strengths within $pm$20% of the mean values seen in the local Galactic ISM, for comparable N(K I); two are weaker by 20--45% and two (including $lambda$5797.1) are stronger by 25--40%. Weaker than expected DIBs [relative to N(K I), N(Na I), and E(B-V)] in some Galactic sight lines and toward several other extragalactic supernovae appear to be associated with strong CN absorption and/or significant molecular fractions. While the N(CH)/N(K I) and N(CN)/N(CH) ratios seen toward SN 2014J are similar to those found in the local Galactic ISM, the combination of high N(CH$^+$)/N(CH) and high W(5797.1)/W(5780.5) ratios has not been seen elsewhere. The centroids of many of the M82 DIBs are shifted, relative to the envelope of the K I profile -- likely due to component-to-component variations in W(DIB)/N(K I) that may reflect the molecular content of the individual components. We compare estimates for the host galaxy reddening E(B-V) and visual extinction A$_{rm V}$ derived from the various interstellar species with the values estimated from optical and near-IR photometry of SN 2014J.
We use a set of magnetohydrodynamics (MHD) simulations of fully-developed (driven) turbulence to study the anisotropy in the velocity field that is induced by the presence of the magnetic field. In our models we study turbulence characterized by sonic Mach numbers M_s from 0.7 to 7.5, and Alfven Mach numbers M_A from 0.4 to 7.7. These are used to produce synthetic observations (centroid maps) that are analyzed. To study the effect of large scale density fluctuations and of white noise we have modified the density fields and obtained new centroid maps, which are analyzed. We show that restricting the range of scales at which the anisotropy is measured makes the method robust against such fluctuations. We show that the anisotropy in the structure function of the maps reveals the direction of the magnetic field for M_A lesssim 1.5, regardless of the sonic Mach number. We found that the degree of anisotropy can be used to determine the degree of magnetization (i.e. M_A) for M_A lesssim 1.5. To do this, one needs an additional measure of the sonic Mach number and an estimate of the LOS magnetic field, both feasible by other techniques, offering a new opportunity to study the magnetization state of the interstellar medium.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
