The X-ray emission of the gamma Cassiopeiae stars

Long considered as the "odd man out" among X-ray emitting Be stars, \gamma Cas (B0.5e IV) is now recognized as the prototype of a class of stars that emit hard thermal X-rays. Our classification differs from the historical use of the term "gamma Cas stars" defined from optical properties alone. The luminosity output of this class contributes significantly to the hard X-ray production in massive stars in the Galaxy. The gamma Cas stars have light curves showing variability on a few broadly-defined timescales and spectra indicative of an optically thin plasma consisting of one or more hot thermal components. By now 9--13 Galactic \approx B0-1.5e main sequence stars are judged to be members or candidate members of the \gamma Cas class. Conservative criteria for this designation are for a \approxB0-1.5e III-V star to have an X-ray luminosity of 10^{32}--10^{33} ergs s^{-1}, a hot thermal spectrum containing the short wavelength Ly \alpha FeXXV and FeXXVI lines and the fluorescence FeK feature all in emission. If thermality cannot be demonstrated, for example from either the presence of these Ly \alpha lines or curvature of the hard continuum; these are the gamma Cas candidates. We discuss the history of the discovery of the complicated characteristics of the variability in the optical, UV, and X-ray domains, leading to suggestions for the physical cause of the production of hard X-rays. These include scenarios in which matter from the Be star accretes onto a degenerate secondary star and interactions between magnetic fields on the Be star and its decretion disk. The greatest aid to the choice of the causal mechanism is the temporal correlations of X-ray light curves and spectra with diagnostics in the optical and UV wavebands. We show why the magnetic star-disk interaction scenario is the most tenable explanation for the creation of hard X-rays on these stars.Comment: Review paper for "X-ray Emissions from Hot Stars and their Winds" compendium to be published by Advances in Space Research in mid-2016. Paper is comprised of 66 pages, 15 figure

Towards Data-Driven Autonomics in Data Centers

Continued reliance on human operators for managing data centers is a major impediment for them from ever reaching extreme dimensions. Large computer systems in general, and data centers in particular, will ultimately be managed using predictive computational and executable models obtained through data-science tools, and at that point, the intervention of humans will be limited to setting high-level goals and policies rather than performing low-level operations. Data-driven autonomics, where management and control are based on holistic predictive models that are built and updated using generated data, opens one possible path towards limiting the role of operators in data centers. In this paper, we present a data-science study of a public Google dataset collected in a 12K-node cluster with the goal of building and evaluating a predictive model for node failures. We use BigQuery, the big data SQL platform from the Google Cloud suite, to process massive amounts of data and generate a rich feature set characterizing machine state over time. We describe how an ensemble classifier can be built out of many Random Forest classifiers each trained on these features, to predict if machines will fail in a future 24-hour window. Our evaluation reveals that if we limit false positive rates to 5%, we can achieve true positive rates between 27% and 88% with precision varying between 50% and 72%. We discuss the practicality of including our predictive model as the central component of a data-driven autonomic manager and operating it on-line with live data streams (rather than off-line on data logs). All of the scripts used for BigQuery and classification analyses are publicly available from the authors' website.Comment: 12 pages, 6 figure

Stellar Intensity Interferometry: Prospects for sub-milliarcsecond optical imaging

Using kilometric arrays of air Cherenkov telescopes, intensity interferometry may increase the spatial resolution in optical astronomy by an order of magnitude, enabling images of rapidly rotating stars with structures in their circumstellar disks and winds, or mapping out patterns of nonradial pulsations across stellar surfaces. Intensity interferometry (pioneered by Hanbury Brown and Twiss) connects telescopes only electronically, and is practically insensitive to atmospheric turbulence and optical imperfections, permitting observations over long baselines and through large airmasses, also at short optical wavelengths. The required large telescopes with very fast detectors are becoming available as arrays of air Cherenkov telescopes, distributed over a few square km. Digital signal handling enables very many baselines to be synthesized, while stars are tracked with electronic time delays, thus synthesizing an optical interferometer in software. Simulated observations indicate limiting magnitudes around m(v)=8, reaching resolutions ~30 microarcsec in the violet. The signal-to-noise ratio favors high-temperature sources and emission-line structures, and is independent of the optical passband, be it a single spectral line or the broad spectral continuum. Intensity interferometry provides the modulus (but not phase) of any spatial frequency component of the source image; for this reason image reconstruction requires phase retrieval techniques, feasible if sufficient coverage of the interferometric (u,v)-plane is available. Experiments are in progress; test telescopes have been erected, and trials in connecting large Cherenkov telescopes have been carried out. This paper reviews this interferometric method in view of the new possibilities offered by arrays of air Cherenkov telescopes, and outlines observational programs that should become realistic already in the rather near future.Comment: New Astronomy Reviews, in press; 101 pages, 11 figures, 185 reference