Current-spin coupling for ferromagnetic domain walls in fine wires

The coupling between a current and a domain wall is examined. In the presence of a finite current and the absence of a potential which breaks the translational symmetry, there is a perfect transfer of angular momentum from the conduction electrons to the wall. As a result, the ground state is in uniform motion. This remains the case when relaxation is accounted for. This is described by, appropriately modified, Landau-Lifshitz-Gilbert equations.Comment: 4 pqges, no figure

Contextual-based Image Inpainting: Infer, Match, and Translate

We study the task of image inpainting, which is to fill in the missing region of an incomplete image with plausible contents. To this end, we propose a learning-based approach to generate visually coherent completion given a high-resolution image with missing components. In order to overcome the difficulty to directly learn the distribution of high-dimensional image data, we divide the task into inference and translation as two separate steps and model each step with a deep neural network. We also use simple heuristics to guide the propagation of local textures from the boundary to the hole. We show that, by using such techniques, inpainting reduces to the problem of learning two image-feature translation functions in much smaller space and hence easier to train. We evaluate our method on several public datasets and show that we generate results of better visual quality than previous state-of-the-art methods.Comment: ECCV 2018 camera read

On optimality of kernels for approximate Bayesian computation using sequential Monte Carlo

Approximate Bayesian computation (ABC) has gained popularity over the past few years for the analysis of complex models arising in population genetics, epidemiology and system biology. Sequential Monte Carlo (SMC) approaches have become work-horses in ABC. Here we discuss how to construct the perturbation kernels that are required in ABC SMC approaches, in order to construct a sequence of distributions that start out from a suitably defined prior and converge towards the unknown posterior. We derive optimality criteria for different kernels, which are based on the Kullback-Leibler divergence between a distribution and the distribution of the perturbed particles. We will show that for many complicated posterior distributions, locally adapted kernels tend to show the best performance. We find that the added moderate cost of adapting kernel functions is easily regained in terms of the higher acceptance rate. We demonstrate the computational efficiency gains in a range of toy examples which illustrate some of the challenges faced in real-world applications of ABC, before turning to two demanding parameter inference problems in molecular biology, which highlight the huge increases in efficiency that can be gained from choice of optimal kernels. We conclude with a general discussion of the rational choice of perturbation kernels in ABC SMC settings

The development of direct payments in the UK: implications for social justice

Direct payments have been heralded by the disability movement as an important means to achieving independent living and hence greater social justice for disabled people through enhanced recognition as well as financial redistribution. Drawing on data from the ESRC funded project Disabled People and Direct Payments: A UK Comparative Perspective, this paper presents an analysis of policy and official statistics on use of direct payments across the UK. It is argued that the potential of direct payments has only partly been realised as a result of very low and uneven uptake within and between different parts of the UK. This is accounted for in part by resistance from some Labour-controlled local authorities, which regard direct payments as a threat to public sector jobs. In addition, access to direct payments has been uneven across impairment groups. However, from a very low base there has been a rapid expansion in the use of direct payments over the past three years. The extent to which direct payments are able to facilitate the ultimate goal of independent living for disabled people requires careful monitoring

PEPSI deep spectra. III. A chemical analysis of the ancient planet-host star Kepler-444

We obtained an LBT/PEPSI spectrum with very high resolution and high signal-to-noise ratio (S/N) of the K0V host Kepler-444, which is known to host 5 sub-Earth size rocky planets. The spectrum has a resolution of R=250,000, a continuous wavelength coverage from 4230 to 9120A, and S/N between 150 and 550:1 (blue to red). We performed a detailed chemical analysis to determine the photospheric abundances of 18 chemical elements, in order to use the abundances to place constraints on the bulk composition of the five rocky planets. Our spectral analysis employs the equivalent width method for most of our spectral lines, but we used spectral synthesis to fit a small number of lines that require special care. In both cases, we derived our abundances using the MOOG spectral analysis package and Kurucz model atmospheres. We find no correlation between elemental abundance and condensation temperature among the refractory elements. In addition, using our spectroscopic stellar parameters and isochrone fitting, we find an age of 10+/-1.5 Gyr, which is consistent with the asteroseismic age of 11+/-1 Gyr. Finally, from the photospheric abundances of Mg, Si, and Fe, we estimate that the typical Fe-core mass fraction for the rocky planets in the Kepler-444 system is approximately 24 per cent. If our estimate of the Fe-core mass fraction is confirmed by more detailed modeling of the disk chemistry and simulations of planet formation and evolution in the Kepler-444 system, then this would suggest that rocky planets in more metal-poor and alpha-enhanced systems may tend to be less dense than their counterparts of comparable size in more metal-rich systems.Comment: in press, 11 pages, 3 figures, data available from pepsi.aip.d