Theory of Star Formation

We review current understanding of star formation, outlining an overall theoretical framework and the observations that motivate it. A conception of star formation has emerged in which turbulence plays a dual role, both creating overdensities to initiate gravitational contraction or collapse, and countering the effects of gravity in these overdense regions. The key dynamical processes involved in star formation -- turbulence, magnetic fields, and self-gravity -- are highly nonlinear and multidimensional. Physical arguments are used to identify and explain the features and scalings involved in star formation, and results from numerical simulations are used to quantify these effects. We divide star formation into large-scale and small-scale regimes and review each in turn. Large scales range from galaxies to giant molecular clouds (GMCs) and their substructures. Important problems include how GMCs form and evolve, what determines the star formation rate (SFR), and what determines the initial mass function (IMF). Small scales range from dense cores to the protostellar systems they beget. We discuss formation of both low- and high-mass stars, including ongoing accretion. The development of winds and outflows is increasingly well understood, as are the mechanisms governing angular momentum transport in disks. Although outstanding questions remain, the framework is now in place to build a comprehensive theory of star formation that will be tested by the next generation of telescopes.Comment: 120 pages, to appear in ARAA. No changes from v1 text; permission statement adde

The stellar and sub-stellar IMF of simple and composite populations

The current knowledge on the stellar IMF is documented. It appears to become top-heavy when the star-formation rate density surpasses about 0.1Msun/(yr pc^3) on a pc scale and it may become increasingly bottom-heavy with increasing metallicity and in increasingly massive early-type galaxies. It declines quite steeply below about 0.07Msun with brown dwarfs (BDs) and very low mass stars having their own IMF. The most massive star of mass mmax formed in an embedded cluster with stellar mass Mecl correlates strongly with Mecl being a result of gravitation-driven but resource-limited growth and fragmentation induced starvation. There is no convincing evidence whatsoever that massive stars do form in isolation. Various methods of discretising a stellar population are introduced: optimal sampling leads to a mass distribution that perfectly represents the exact form of the desired IMF and the mmax-to-Mecl relation, while random sampling results in statistical variations of the shape of the IMF. The observed mmax-to-Mecl correlation and the small spread of IMF power-law indices together suggest that optimally sampling the IMF may be the more realistic description of star formation than random sampling from a universal IMF with a constant upper mass limit. Composite populations on galaxy scales, which are formed from many pc scale star formation events, need to be described by the integrated galactic IMF. This IGIMF varies systematically from top-light to top-heavy in dependence of galaxy type and star formation rate, with dramatic implications for theories of galaxy formation and evolution.Comment: 167 pages, 37 figures, 3 tables, published in Stellar Systems and Galactic Structure, Vol.5, Springer. This revised version is consistent with the published version and includes additional references and minor additions to the text as well as a recomputed Table 1. ISBN 978-90-481-8817-

Gaia Data Release 2. Kinematics of globular clusters and dwarf galaxies around the Milky Way

AIMS: The goal of this paper is to demonstrate the outstanding quality of the second data release of the Gaia mission and its power for constraining many different aspects of the dynamics of the satellites of the Milky Way. We focus here on determining the proper motions of 75 Galactic globular clusters, nine dwarf spheroidal galaxies, one ultra-faint system, and the Large and Small Magellanic Clouds. METHODS: Using data extracted from the Gaia archive, we derived the proper motions and parallaxes for these systems, as well as their uncertainties. We demonstrate that the errors, statistical and systematic, are relatively well understood. We integrated the orbits of these objects in three different Galactic potentials, and characterised their properties. We present the derived proper motions, space velocities, and characteristic orbital parameters in various tables to facilitate their use by the astronomical community. RESULTS: Our limited and straightforward analyses have allowed us for example to (i) determine absolute and very precise proper motions for globular clusters; (ii) detect clear rotation signatures in the proper motions of at least five globular clusters; (iii) show that the satellites of the Milky Way are all on high-inclination orbits, but that they do not share a single plane of motion; (iv) derive a lower limit for the mass of the Milky Way of 9.1{_₂.₆⁺⁶·²} x 10¹¹ M⊙ based on the assumption that the Leo I dwarf spheroidal is bound; (v) derive a rotation curve for the Large Magellanic Cloud based solely on proper motions that is competitive with line-of-sight velocity curves, now using many orders of magnitude more sources; and (vi) unveil the dynamical effect of the bar on the motions of stars in the Large Magellanic Cloud. CONCLUSIONS: All these results highlight the incredible power of the Gaia astrometric mission, and in particular of its second data release

Gaia Data Release 2 Variable stars in the colour-absolute magnitude diagram

Context. The ESA Gaia mission provides a unique time-domain survey for more than 1.6 billion sources with G ≲ 21 mag. Aims. We showcase stellar variability in the Galactic colour-absolute magnitude diagram (CaMD). We focus on pulsating, eruptive, and cataclysmic variables, as well as on stars that exhibit variability that is due to rotation and eclipses. Methods. We describe the locations of variable star classes, variable object fractions, and typical variability amplitudes throughout the CaMD and show how variability-related changes in colour and brightness induce “motions”. To do this, we use 22 months of calibrated photometric, spectro-photometric, and astrometric Gaia data of stars with a significant parallax. To ensure that a large variety of variable star classes populate the CaMD, we crossmatched Gaia sources with known variable stars. We also used the statistics and variability detection modules of the Gaia variability pipeline. Corrections for interstellar extinction are not implemented in this article. Results. Gaia enables the first investigation of Galactic variable star populations in the CaMD on a similar, if not larger, scale as was previously done in the Magellanic Clouds. Although the observed colours are not corrected for reddening, distinct regions are visible in which variable stars occur. We determine variable star fractions to within the current detection thresholds of Gaia. Finally, we report the most complete description of variability-induced motion within the CaMD to date. Conclusions. Gaia enables novel insights into variability phenomena for an unprecedented number of stars, which will benefit the understanding of stellar astrophysics. The CaMD of Galactic variable stars provides crucial information on physical origins of variability in a way that has previously only been accessible for Galactic star clusters or external galaxies. Future Gaia data releases will enable significant improvements over this preview by providing longer time series, more accurate astrometry, and additional data types (time series BP and RP spectra, RVS spectra, and radial velocities), all for much larger samples of stars

電腦斷層攝影大全

International audienceThis work proposes a new unsupervised deep generative model for system logs. It is designed to be generic and may be used in various downstream anomaly detection tasks, such as system failure or intrusion detection. It is based on the (reasonable) assumption that most log lines follow rather fixed syntactic structures, which enables us to replace the costly traditional convolutional and recurrent architectures by a much faster component: a deep averaging network. Our model still exploits a standard recurrent model with attention to capture the dependencies between successive log lines. We experimentally validate the proposed generative model on a real dataset obtained from a state-of-the-art High Performance Computing cluster and show the effectiveness of the proposed approach in modeling the "normal" behaviour of the system

Mesorhizobium alhagi sp. nov., isolated from wild Alhagi sparsifolia in north-western China

International audienceEleven strains that formed symbiotic root nodules on Alhagi sparsifolia, designated previously as genospecies II, were identified as a new lineage of Mesorhizobium (Alphaproteobacteria) that could be differentiated from all previously recognized species of the genus Mesorhizobium by using 16S rRNA gene sequences (,97.8 % similarity), DNA–DNA hybridization (,45 %), dnaJ, dnaK, recA, glnA, nifH, nodA and nodC gene sequences, fatty acid profiles (C 18 : 1 v7c, 35 %;11-methyl C 18 : 1 v7c, 30 %) and numerical taxonomy. These strains are therefore considered to represent a novel species, for which the name Mesorhizobium alhagi sp. nov. is proposed, with isolate CCNWXJ12-2 T (5ACCC 15461 T 5HAMBI 3019 T) as the type strain