Photoionisation and Heating of a Supernova Driven, Turbulent, Interstellar Medium

The Diffuse Ionised Gas (DIG) in galaxies traces photoionisation feedback from massive stars. Through three dimensional photoionisation simulations, we study the propagation of ionising photons, photoionisation heating and the resulting distribution of ionised and neutral gas within snapshots of magnetohydrodynamic simulations of a supernova driven turbulent interstellar medium. We also investigate the impact of non-photoionisation heating on observed optical emission line ratios. Inclusion of a heating term which scales less steeply with electron density than photoionisation is required to produce diagnostic emission line ratios similar to those observed with the Wisconsin H{\alpha} Mapper. Once such heating terms have been included, we are also able to produce temperatures similar to those inferred from observations of the DIG, with temperatures increasing to above 15000 K at heights |z| > 1 kpc. We find that ionising photons travel through low density regions close to the midplane of the simulations, while travelling through diffuse low density regions at large heights. The majority of photons travel small distances (< 100pc); however some travel kiloparsecs and ionise the DIG.Comment: 10 pages, 13 figures, accepted to MNRA

Adaptive sampling in context-aware systems: a machine learning approach

As computing systems become ever more pervasive, there is an increasing need for them to understand and adapt to the state of the environment around them: that is, their context. This understanding comes with considerable reliance on a range of sensors. However, portable devices are also very constrained in terms of power, and hence the amount of sensing must be minimised. In this paper, we present a machine learning architecture for context awareness which is designed to balance the sampling rates (and hence energy consumption) of individual sensors with the significance of the input from that sensor. This significance is based on predictions of the likely next context. The architecture is implemented using a selected range of user contexts from a collected data set. Simulation results show reliable context identification results. The proposed architecture is shown to significantly reduce the energy requirements of the sensors with minimal loss of accuracy in context identification

Application of mathematical and machine learning techniques to analyse eye tracking data enabling better understanding of children’s visual cognitive behaviours

In this research, we aimed to investigate the visual-cognitive behaviours of a sample of 106 children in Year 3 (8.8 ± 0.3 years) while completing a mathematics bar-graph task. Eye movements were recorded while children completed the task and the patterns of eye movements were explored using machine learning approaches. Two different techniques of machine-learning were used (Bayesian and K-Means) to obtain separate model sequences or average scanpaths for those children who responded either correctly or incorrectly to the graph task. Application of these machine-learning approaches indicated distinct differences in the resulting scanpaths for children who completed the graph task correctly or incorrectly: children who responded correctly accessed information that was mostly categorised as critical, whereas children responding incorrectly did not. There was also evidence that the children who were correct accessed the graph information in a different, more logical order, compared to the children who were incorrect. The visual behaviours aligned with different aspects of graph comprehension, such as initial understanding and orienting to the graph, and later interpretation and use of relevant information on the graph. The findings are discussed in terms of the implications for early mathematics teaching and learning, particularly in the development of graph comprehension, as well as the application of machine learning techniques to investigations of other visual-cognitive behaviours.Peer reviewe

Brewster-angle measurements of sea-surface reflectance using a high resolution spectroradiometer

This paper describes the design, construction and testing of a ship-borne spectroradiometer based on an imaging spectrograph and cooled CCD array with a wavelength range of 350-800 nm and 4 nm spectral sampling. The instrument had a minimum spectral acquisition time of 0.1 s, but in practice data were collected over periods of 10 s to allow averaging of wave effects. It was mounted on a ship's superstructure so that it viewed the sea surface from a height of several metres at the Brewster angle (53 degrees) through a linear polarizing filter. Comparison of sea-leaving spectra acquired with the polarizer oriented horizontally and vertically enabled estimation of the spectral composition of sky light reflected directly from the sea surface. A semi-empirical correction procedure was devised for retrieving water-leaving radiance spectra from these measurements while minimizing the influence of reflected sky light. Sea trials indicated that reflectance spectra obtained by this method were consistent with the results of radiance transfer modelling of case 2 waters with similar concentrations of chlorophyll and coloured dissolved organic matter. Surface reflectance signatures measured at three locations containing blooms of different phytoplankton species were easily discriminated and the instrument was sufficiently sensitive to detect solar-stimulated fluorescence from surface chlorophyll concentrations down to 1 mg m−3

How Sandcastles Fall

Capillary forces significantly affect the stability of sandpiles. We analyze the stability of sandpiles with such forces, and find that the critical angle is unchanged in the limit of an infinitely large system; however, this angle is increased for finite-sized systems. The failure occurs in the bulk of the sandpile rather than at the surface. This is related to a standard result in soil mechanics. The increase in the critical angle is determined by the surface roughness of the particles, and exhibits three regimes as a function of the added-fluid volume. Our theory is in qualitative agreement with the recent experimental results of Hornbaker et al., although not with the interpretation they make of these results.Comment: 4 pages, 2 figures, revte

Predicion of charge separation in GaAs/AlAs cylindrical Russian Doll nanostructures

We have contrasted the quantum confinement of (i) multiple quantum wells of flat GaAs and AlAs layers, i.e. (\GaAs)_{m}/(\AlAs)_n/(\GaAs)_p/(\AlAs)_q, with (ii) ``cylindrical Russian Dolls'' -- an equivalent sequence of wells and barriers arranged as concentric wires. Using a pseudopotential plane-wave calculation, we identified theoretically a set of numbers ($m,n,p$ and $q$) such that charge separation can exist in ``cylindrical Russian Dolls'': the CBM is localized in the inner GaAs layer, while the VBM is localized in the outer GaAs layer.Comment: latex, 8 page

Dark Matter in the Coming Decade: Complementary Paths to Discovery and Beyond

In this report we summarize the many dark matter searches currently being pursued through four complementary approaches: direct detection, indirect detection, collider experiments, and astrophysical probes. The essential features of broad classes of experiments are described, each with their own strengths and weaknesses. The complementarity of the different dark matter searches is discussed qualitatively and illustrated quantitatively in two simple theoretical frameworks. Our primary conclusion is that the diversity of possible dark matter candidates requires a balanced program drawing from all four approaches.Comment: Report prepared for the Community Summer Study (Snowmass) 2013, on behalf of Cosmic Frontier Working Groups 1-4 (CF1: WIMP Dark Matter Direct Detection, CF2: WIMP Dark Matter Indirect Detection, CF3: Non-WIMP Dark Matter, and CF4: Dark Matter Complementarity); published versio