Search for: All records

Context. The formation of molecular gas in interstellar clouds is a slow process, but can be enhanced by gas compression. Magneto-hydrodynamic (MHD) waves can create compressed quasi-periodic linear structures, referred to as striations. Striations are observed at the column densities at which the transition from atomic to molecular gas takes place. Aims. We explore the role of MHD waves in the CO chemistry in regions with striations within molecular clouds. Methods. We targeted a region with striations in the Polaris Flare cloud. We conducted a CO J = 2−1 survey in order to probe the molecular gas properties. We used archival starlight polarization data and dust emission maps in order to probe the magnetic field properties and compare against the CO morphological and kinematic properties. We assessed the interaction of compressible MHD wave modes with CO chemistry by comparing their characteristic timescales. Results. The estimated magnetic field is 38–76 µG. In the CO integrated intensity map, we observe a dominant quasiperiodic intensity structure that tends to be parallel to the magnetic field orientation and has a wavelength of approximately one parsec. The periodicity axis is ~17° off from the mean magnetic field orientation and is also observed in the dust intensity map. The contrast in the CO integrated intensity map is ~2.4 times higher than the contrast of the column density map, indicating that CO formation is enhanced locally. We suggest that a dominant slow magnetosonic mode with an estimated period of 2.1–3.4 Myr and a propagation speed of 0.30–0.45 km s −1 is likely to have enhanced the formation of CO, hence created the observed periodic pattern. We also suggest that within uncertainties, a fast magnetosonic mode with a period of 0.48 Myr and a velocity of 2.0 km s −1 could have played some role in increasing the CO abundance. Conclusions. Quasiperiodic CO structures observed in striation regions may be the imprint of MHD wave modes. The Alfvénic speed sets the dynamical timescales of the compressible MHD modes and determines which wave modes are involved in the CO chemistry. 

Continuum polarization over the UV-to-microwave range is due to dichroic extinction (or emission) by asymmetric, aligned dust grains. Scattering can also be an important source of polarization, especially at short wavelengths. Because of both grain alignment and scattering physics, the wavelength dependence of the polarization, generally, traces the size of the aligned grains. Similarly because of the differing wavelength dependencies of dichroic extinction and scattering polarization, the two can generally be reliably separated. Ultraviolet (UV) polarimetry therefore provides a unique probe of the smallest dust grains (diameter$< 0.09~\upmu \text{m}$$<0.09\text{μm}$), their mineralogy and interaction with the environment. However, the current observational status of interstellar UV polarization is very poor with less than 30 lines of sight probed. With the modern, quantitative and well-tested, theory of interstellar grain alignment now available, we have the opportunity to advance the understanding of the interstellar medium (ISM) by executing a systematic study of the UV polarization in the ISM of the Milky Way and near-by galaxies. The Polstar mission will provide the sensitivity and observing time needed to carry out such a program (probing hundreds of stars in the Milky Way and dozens of stars in the LMC/SMC), addressing questions of dust composition as a function of size and location, radiation- and magnetic-field characteristics as well as unveiling the carrier of the 2175 Å extinction feature. In addition, using high-resolution UV line spectroscopy Polstar will search for and probe the alignment of, and polarization from, aligned atoms and ions - so called “Ground State Alignment”, a potentially powerful new probe of magnetic fields in the diffuse ISM.

 

Context. Atomic gas in the diffuse interstellar medium (ISM) is organized in filamentary structures. These structures usually host cold and dense molecular clumps. The Galactic magnetic field is considered to play an important role in the formation of these clumps. Aims. Our goal is to explore the role of the magnetic field in the H I -H 2 transition process. Methods. We targeted a diffuse ISM filamentary cloud toward the Ursa Major cirrus where gas transitions from atomic to molecular. We probed the magnetic field properties of the cloud with optical polarization observations. We performed multiwavelength spectroscopic observations of different species in order to probe the gas phase properties of the cloud. We observed the CO ( J = 1−0) and ( J = 2−1) lines in order to probe the molecular content of the cloud. We also obtained observations of the [C ii ] 157.6 µ m emission line in order to trace the CO-dark H 2 gas and estimate the mean volume density of the cloud. Results. We identified two distinct subregions within the cloud. One of the regions is mostly atomic, while the other is dominated by molecular gas, although most of it is CO-dark. The estimated plane-of-the-sky magnetic field strength between the two regions remains constant within uncertainties and lies in the range 13–30 µG. The total magnetic field strength does not scale with density. This implies that gas is compressed along the field lines. We also found that turbulence is trans-Alfvénic, with M A ≈ 1. In the molecular region, we detected an asymmetric CO clump whose minor axis is closer, with a 24° deviation, to the mean magnetic field orientation than the angle of its major axis. The H i velocity gradients are in general perpendicular to the mean magnetic field orientation except for the region close to the CO clump, where they tend to become parallel. This phenomenon is likely related to gas undergoing gravitational infall. The magnetic field morphology of the target cloud is parallel to the H i column density structure of the cloud in the atomic region, while it tends to become perpendicular to the H i structure in the molecular region. On the other hand, the magnetic field morphology seems to form a smaller offset angle with the total column density shape (including both atomic and molecular gas) of this transition cloud. Conclusions. In the target cloud where the H i –H 2 transition takes place, turbulence is trans-Alfvénic, and hence the magnetic field plays an important role in the cloud dynamics. Atomic gas probably accumulates preferentially along the magnetic field lines and creates overdensities where molecular gas can form. The magnetic field morphology is probed better by the total column density shape of the cloud, and not its H i column density shape. 

Context. Optical polarimeters are typically calibrated using measurements of stars with known and stable polarization parameters. However, there is a lack of such stars available across the sky. Many of the currently available standards are not suitable for medium and large telescopes due to their high brightness. Moreover, as we find, some of the polarimetric standards used are in fact variable or have polarization parameters that differ from their cataloged values. Aims. Our goal is to establish a sample of stable standards suitable for calibrating linear optical polarimeters with an accuracy down to 10 −3 in fractional polarization. Methods. For 4 yr, we have been running a monitoring campaign of a sample of standard candidates comprised of 107 stars distributed across the northern sky. We analyzed the variability of the linear polarization of these stars, taking into account the non-Gaussian nature of fractional polarization measurements. For a subsample of nine stars, we also performed multiband polarization measurements. Results. We created a new catalog of 65 stars (see Table 2) that are stable, have small uncertainties of measured polarimetric parameters, and can be used as calibrators of polarimeters at medium and large telescopes. 

We present the first Bayesian method for tomographic decomposition of the plane-of-sky orientation of the magnetic field with the use of stellar polarimetry and distance. This standalone tomographic inversion method presents an important step forward in reconstructing the magnetized interstellar medium (ISM) in three dimensions within dusty regions. We develop a model in which the polarization signal from the magnetized and dusty ISM is described by thin layers at various distances, a working assumption which should be satisfied in small-angular circular apertures. Our modeling makes it possible to infer the mean polarization (amplitude and orientation) induced by individual dusty clouds and to account for the turbulence-induced scatter in a generic way. We present a likelihood function that explicitly accounts for uncertainties in polarization and parallax. We develop a framework for reconstructing the magnetized ISM through the maximization of the log-likelihood using a nested sampling method. We test our Bayesian inversion method on mock data, representative of the high Galactic latitude sky, taking into account realistic uncertainties from Gaia and as expected for the optical polarization survey P ASIPHAE according to the currently planned observing strategy. We demonstrate that our method is effective at recovering the cloud properties as soon as the polarization induced by a cloud to its background stars is higher than ~0.1% for the adopted survey exposure time and level of systematic uncertainty. The larger the induced polarization is, the better the method’s performance, and the lower the number of required stars. Our method makes it possible to recover not only the mean polarization properties but also to characterize the intrinsic scatter, thus creating new ways to characterize ISM turbulence and the magnetic field strength. Finally, we apply our method to an existing data set of starlight polarization with known line-of-sight decomposition, demonstrating agreement with previous results and an improved quantification of uncertainties in cloud properties. 

Context. Filamentary structures in nearby molecular clouds have been found to exhibit a characteristic width of 0.1 pc, as observed in dust emission. Understanding the origin of this universal width has become a topic of central importance in the study of molecular cloud structure and the early stages of star formation. Aims. We investigate how the recovered widths of filaments depend on the distance from the observer by using previously published results from the Herschel Gould Belt Survey. Methods. We obtained updated estimates on the distances to nearby molecular clouds observed with Herschel by using recent results based on 3D dust extinction mapping and Gaia . We examined the widths of filaments from individual clouds separately, as opposed to treating them as a single population. We used these per-cloud filament widths to search for signs of variation amongst the clouds of the previously published study. Results. We find a significant dependence of the mean per-cloud filament width with distance. The distribution of mean filament widths for nearby clouds is incompatible with that of farther away clouds. The mean per-cloud widths scale with distance approximately as 4−5 times the beam size. We examine the effects of resolution by performing a convergence study of a filament profile in the Herschel image of the Taurus Molecular Cloud. We find that resolution can severely affect the shapes of radial profiles over the observed range of distances. Conclusions. We conclude that the data are inconsistent with 0.1 pc being the universal characteristic width of filaments. 

ABSTRACT Polarization measurements done using Imaging Polarimeters such as the Robotic Polarimeter are very sensitive to the presence of artefacts in images. Artefacts can range from internal reflections in a telescope to satellite trails that could contaminate an area of interest in the image. With the advent of wide-field polarimetry surveys, it is imperative to develop methods that automatically flag artefacts in images. In this paper, we implement a Convolutional Neural Network to identify the most dominant artefacts in the images. We find that our model can successfully classify sources with 98 per cent true positive and 97 per cent true negative rates. Such models, combined with transfer learning, will give us a running start in artefact elimination for near-future surveys like WALOP.