Automatic Detection of Expanding HI Shells Using Artificial Neural Networks

The identification of expanding HI shells is difficult because of their variable morphological characteristics. The detection of HI bubbles on a global scale therefore never has been attempted. In this paper, an automatic detector for expanding HI shells is presented. The detection is based on the more stable dynamical characteristics of expanding shells and is performed in two stages. The first one is the recognition of the dynamical signature of an expanding bubble in the velocity spectra, based on the classification of an artificial neural network. The pixels associated with these recognized spectra are identified on each velocity channel. The second stage consists in looking for concentrations of those pixels that were firstly pointed out, and to decide if they are potential detections by morphological and 21-cm emission variation considerations. Two test bubbles are correctly detected and a potentially new case of shell that is visually very convincing is discovered. About 0.6% of the surveyed pixels are identified as part of a bubble. These may be false detections, but still constitute regions of space with high probability of finding an expanding shell. The subsequent search field is thus significantly reduced. We intend to conduct in the near future a large scale HI shells detection over the Perseus Arm using our detector.Comment: 39 pages, 11 figures, accepted by PAS

Extremal Configurations of Hinge Structures

We study body-and-hinge and panel-and-hinge chains in R^d, with two marked points: one on the first body, the other on the last. For a general chain, the squared distance between the marked points gives a Morse-Bott function on a torus configuration space. Maximal configurations, when the distance between the two marked points reaches a global maximum, have particularly simple geometrical characterizations. The three-dimensional case is relevant for applications to robotics and molecular structures

Weighing wimps with kinks at colliders: invisible particle mass measurements from endpoints

We consider the application of endpoint techniques to the problem of mass determination for new particles produced at a hadron collider, where these particles decay to an invisible particle of unknown mass and one or more visible particles of known mass. We also consider decays of these types for pair-produced particles and in each case consider situations both with and without initial state radiation. We prove that, in most (but not all) cases, the endpoint of an appropriate transverse mass observable, considered as a function of the unknown mass of the invisible particle, has a kink at the true value of the invisible particle mass. The co-ordinates of the kink yield the masses of the decaying particle and the invisible particle. We discuss the prospects for implementing this method at the LHC

Dark Matter Direct Detection with Non-Maxwellian Velocity Structure

The velocity distribution function of dark matter particles is expected to show significant departures from a Maxwell-Boltzmann distribution. This can have profound effects on the predicted dark matter - nucleon scattering rates in direct detection experiments, especially for dark matter models in which the scattering is sensitive to the high velocity tail of the distribution, such as inelastic dark matter (iDM) or light (few GeV) dark matter (LDM), and for experiments that require high energy recoil events, such as many directionally sensitive experiments. Here we determine the velocity distribution functions from two of the highest resolution numerical simulations of Galactic dark matter structure (Via Lactea II and GHALO), and study the effects for these scenarios. For directional detection, we find that the observed departures from Maxwell-Boltzmann increase the contrast of the signal and change the typical direction of incoming DM particles. For iDM, the expected signals at direct detection experiments are changed dramatically: the annual modulation can be enhanced by more than a factor two, and the relative rates of DAMA compared to CDMS can change by an order of magnitude, while those compared to CRESST can change by a factor of two. The spectrum of the signal can also change dramatically, with many features arising due to substructure. For LDM the spectral effects are smaller, but changes do arise that improve the compatibility with existing experiments. We find that the phase of the modulation can depend upon energy, which would help discriminate against background should it be found.Comment: 34 pages, 16 figures, submitted to JCAP. Tables of g(v_min), the integral of f(v)/v from v_min to infinity, derived from our simulations, are available for download at http://astro.berkeley.edu/~mqk/dmdd

Models with short and long-range interactions: phase diagram and reentrant phase

We study the phase diagram of two different Hamiltonians with competiting local, nearest-neighbour, and mean-field couplings. The first example corresponds to the HMF Hamiltonian with an additional short-range interaction. The second example is a reduced Hamiltonian for dipolar layered spin structures, with a new feature with respect to the first example, the presence of anisotropies. The two examples are solved in both the canonical and the microcanonical ensemble using a combination of the min-max method with the transfer operator method. The phase diagrams present typical features of systems with long-range interactions: ensemble inequivalence, negative specific heat and temperature jumps. Moreover, in a given range of parameters, we report the signature of phase reentrance. This can also be interpreted as the presence of azeotropy with the creation of two first order phase transitions with ensemble inequivalence, as one parameter is varied continuously