Spherically symmetric model stellar atmospheres and limb darkening II: limb-darkening laws, gravity-darkening coefficients and angular diameter corrections for FGK dwarf stars

Limb darkening is a fundamental ingredient for interpreting observations of planetary transits, eclipsing binaries, optical/infrared interferometry and microlensing events. However, this modeling traditionally represents limb darkening by a simple law having one or two coefficients that have been derived from plane-parallel model stellar atmospheres, which has been done by many researchers. More recently, researchers have gone beyond plane-parallel models and considered other geometries. We previously studied the limb-darkening coefficients from spherically symmetric and plane-parallel model stellar atmospheres for cool giant and supergiant stars, and in this investigation we apply the same techniques to FGK dwarf stars. We present limb-darkening coefficients, gravity-darkening coefficients and interferometric angular diameter corrections from Atlas and SAtlas model stellar atmospheres. We find that sphericity is important even for dwarf model atmospheres, leading to significant differences in the predicted coefficients.Comment: 9 pages, 8 figures. Accepted for publication in A&

Separation of Carbon from Deinking Waste by Means of Flotation

The technique of froth flotation, as practiced in the separation of mineral ores, has been applied to the separation of carbon black from the deinking waste of the paper industry. On the theory that carbon black (from ink) has a positive charge in water, and clay and cellulose fibers have negative charges in water, experiments were of two types. First, it was attempted to float the carbon from the clay and cellulose fibers. Second, it was attempted to float the clay and cellulose fibers from the carbon. Several possible formulas were found for separating carbon black from deinking waste. Favorable results were obtained in both types of experiments

Chaotic Advection at the Pore Scale: Mechanisms, Upscaling and Implications for Macroscopic Transport

The macroscopic spreading and mixing of solute plumes in saturated porous media is ultimately controlled by processes operating at the pore scale. Whilst the conventional picture of pore-scale mechanical dispersion and molecular diffusion leading to persistent hydrodynamic dispersion is well accepted, this paradigm is inherently two-dimensional (2D) in nature and neglects important three-dimensional (3D) phenomena. We discuss how the kinematics of steady 3D flow at the porescale generate chaotic advection, involving exponential stretching and folding of fluid elements,the mechanisms by which it arises and implications of microscopic chaos for macroscopic dispersion and mixing. Prohibited in steady 2D flow due to topological constraints, these phenomena are ubiquitous due to the topological complexity inherent to all 3D porous media. Consequently 3D porous media flows generate profoundly different fluid deformation and mixing processes to those of 2D flow. The interplay of chaotic advection and broad transit time distributions can be incorporated into a continuous-time random walk (CTRW) framework to predict macroscopic solute mixing and spreading. We show how these results may be generalised to real porous architectures via a CTRW model of fluid deformation, leading to stochastic models of macroscopic dispersion and mixing which both honour the pore-scale kinematics and are directly conditioned on the pore-scale tomography.Comment: 43 page

Indicators of Mass in Spherical Stellar Atmospheres

Mass is the most important stellar parameter, but it is not directly observable for a single star. Spherical model stellar atmospheres are explicitly characterized by their luminosity ($L_\star$), mass ($M_\star$) and radius ($R_\star$), and observations can now determine directly $L_\star$ and $R_\star$. We computed spherical model atmospheres for red giants and for red supergiants holding $L_\star$ and $R_\star$ constant at characteristic values for each type of star but varying $M_\star$, and we searched the predicted flux spectra and surface-brightness distributions for features that changed with mass. For both stellar classes we found similar signatures of the star's mass in both the surface-brightness distribution and the flux spectrum. The spectral features have been use previously to determine $\log_{10} (g)$, and now that the luminosity and radius of a non-binary red giant or red supergiant can be observed, spherical model stellar atmospheres can be used to determine the star's mass from currently achievable spectroscopy. The surface-brightness variations with mass are slightly smaller than can be resolved by current stellar imaging, but they offer the advantage of being less sensitive to the detailed chemical composition of the atmosphere.Comment: 24 pages, 9 figure

The optimization of force inputs for active structural acoustic control using a neural network

This paper investigates the use of a neural network to determine which force actuators, of a multi-actuator array, are best activated in order to achieve structural-acoustic control. The concept is demonstrated using a cylinder/cavity model on which the control forces, produced by piezoelectric actuators, are applied with the objective of reducing the interior noise. A two-layer neural network is employed and the back propagation solution is compared with the results calculated by a conventional, least-squares optimization analysis. The ability of the neural network to accurately and efficiently control actuator activation for interior noise reduction is demonstrated

Inelastic Collisions in an Ultracold quasi-2D Gas

We present a formalism for rigorous calculations of cross sections for inelastic and reactive collisions of ultracold atoms and molecules confined by laser fields in quasi-2D geometry. Our results show that the elastic-to-inelastic ratios of collision cross sections are enhanced in the presence of a laser confinement and that the threshold energy dependence of the collision cross sections can be tuned by varying the confinement strength and external magnetic fields. The enhancement of the elastic-to-inelastic ratios is inversely proportional to $\sqrt{\epsilon/\hbar \omega_0}$, where $\epsilon$ is the kinetic energy and $\omega_0$ is the oscillation frequency of the trapped particles in the confinement potential.Comment: 4 pages, 4 figure

Stochastic rounding and reduced-precision fixed-point arithmetic for solving neural ordinary differential equations

Although double-precision floating-point arithmetic currently dominates high-performance computing, there is increasing interest in smaller and simpler arithmetic types. The main reasons are potential improvements in energy efficiency and memory footprint and bandwidth. However, simply switching to lower-precision types typically results in increased numerical errors. We investigate approaches to improving the accuracy of reduced-precision fixed-point arithmetic types, using examples in an important domain for numerical computation in neuroscience: the solution of Ordinary Differential Equations (ODEs). The Izhikevich neuron model is used to demonstrate that rounding has an important role in producing accurate spike timings from explicit ODE solution algorithms. In particular, fixed-point arithmetic with stochastic rounding consistently results in smaller errors compared to single precision floating-point and fixed-point arithmetic with round-to-nearest across a range of neuron behaviours and ODE solvers. A computationally much cheaper alternative is also investigated, inspired by the concept of dither that is a widely understood mechanism for providing resolution below the least significant bit (LSB) in digital signal processing. These results will have implications for the solution of ODEs in other subject areas, and should also be directly relevant to the huge range of practical problems that are represented by Partial Differential Equations (PDEs).Comment: Submitted to Philosophical Transactions of the Royal Society