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Register a new userHI in Local Group analogs: what does it tell us about galaxy formation?
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We present the results of our HI survey of six loose groups of galaxies analogous to the Local Group. The survey was conducted using the Parkes telescope and the Australia Telescope Compact Array to produce a census of all the gas-rich galaxies and potential analogs to the high-velocity clouds (HVCs) within these groups down to M(HI)<10^7 M(sun) as a test of models of galaxy formation. We present the HI mass function and halo mass function for these analogous groups and compare them with the Local Group and other environments. We also demonstrate that our non-detection of HVC analogs in these groups implies that they must have low HI masses and be clustered tightly around galaxies, including around our own Milky Way, and are not distributed throughout the Local Group.
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Planck data has not found the smoking gun of non-Gaussianity that would have necessitated consideration of inflationary models beyond the simplest canonical single field scenarios. This raises the important question of what these results do imply for more general models, and in particular, multi-field inflation. In this paper we revisit four ways in which two-field scenarios can behave differently from single field models; two-field slow-roll dynamics, curvaton-type behaviour, inflation ending on an inhomogeneous hypersurface and modulated reheating. We study the constraints that Planck data puts on these classes of behaviour, focusing on the latter two which have been least studied in the recent literature. We show that these latter classes are almost equivalent, and extend their previous analyses by accounting for arbitrary evolution of the isocurvature mode which, in particular, places important limits on the Gaussian curvature of the reheating hypersurface. In general, however, we find that Planck bispectrum results only constrain certain regions of parameter space, leading us to conclude that inflation sourced by more than one scalar field remains an important possibility.
The free energy principle has been proposed as a unifying account of brain function. It is closely related, and in some cases subsumes, earlier unifying ideas such as Bayesian inference, predictive coding, and active learning. This article clarifies these connections, teasing apart distinctive and shared predictions.
Understanding classifier decision under novel environments is central to the community, and a common practice is evaluating it on labeled test sets. However, in real-world testing, image annotations are difficult and expensive to obtain, especially when the test environment is changing. A natural question then arises: given a trained classifier, can we evaluate its accuracy on varying unlabeled test sets? In this work, we train semantic classification and rotation prediction in a multi-task way. On a series of datasets, we report an interesting finding, i.e., the semantic classification accuracy exhibits a strong linear relationship with the accuracy of the rotation prediction task (Pearsons Correlation r > 0.88). This finding allows us to utilize linear regression to estimate classifier performance from the accuracy of rotation prediction which can be obtained on the test set through the freely generated rotation labels.
In this paper we analyse tiebreak results from some tennis players in order to investigate whether we are able to identify some strategy in this crucial moment of the game. We compared the observed results with a binomial distribution considering that the probabilities of winning or losing a point are equal. Using a $chi^2$ test we found that, excepting some players, the greatest part of the results agrees with our hypothesis that there is no hidden strategy and the points in tiebreaks are merely aleatory.
Gaia will provide parallaxes and proper motions with accuracy ranging from 10 to 1000 microarcsecond on up to one billion stars. Most of these will be disk stars: for an unreddened K giant at 6 kpc, it will measure the distance accurate to 15% and the transverse velocity to an accuracy of about 1 km/s. Gaia will observe tracers of Galactic structure across the whole HR diagram, including Cepheids, RR Lyrae, white dwarfs, F dwarfs and HB stars. Onboard low resolution spectrophotometry will permit -- in addition to a Teff estimate -- dwarf/giant discrimination, metallicity measurement and extinction determination. For the first time, then, Gaia will provide us with a 3D spatial/properties map and at least a 2D velocity map of these tracers (RVs will be obtained too for brighter stars.) This will be a goldmine of information from which to learn about the origin and evolution of the Galactic disk. I briefly review the Gaia mission, and then show how the expected astrometric accuracies translate into distance and velocity accuracies and statistics. I examine the impact Gaia should have on a few scientific areas relevant to the Galactic disk. I discuss how a better determination of the spiral arm locations and pattern speed, plus a better reconstruction of the Suns orbit over the past billion years (from integration through the Gaia-measured gravitational potential) will allow us to assess the possible role of spiral arm crossings in ice ages and mass extinctions on the Earth.
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