Observation of magnetization reversal in epitaxial Gd0.67Ca0.33MnO3 thin films

High quality epitaxial thin films of Gd0.67Ca0.33MnO3 have been deposited onto (100) SrTiO3 substrates by pulsed-laser deposition. Enhanced properties in comparison with bulk samples were observed. The magnetic transition temperature (Tc) of the as-grown films is much higher than the corresponding bulk values. Most interestingly, magnetization measurements performed under small applied fields, exhibit magnetization reversals below Tc, no matter whether the film is field-cooled (FC) or zero-field-cooled (ZFC). A rapid magnetization reversal occurs at 7 K when field cooled, while as for the ZFC process the magnetization decreases gradually with increasing temperatures, taking negative values above 7 K and changing to positive values again, above 83 K. In higher magnetic fields the magnetization does not change sign. The reversal mechanism is discussed in terms of a negative exchange f-d interaction and magnetic anisotropy, this later enhanced by strain effects induced by the lattice mismatch between the film and the substrate.Comment: 16 pages, 4 figure

Great cities look small

Great cities connect people; failed cities isolate people. Despite the fundamental importance of physical, face-to-face social-ties in the functioning of cities, these connectivity networks are not explicitly observed in their entirety. Attempts at estimating them often rely on unrealistic over-simplifications such as the assumption of spatial homogeneity. Here we propose a mathematical model of human interactions in terms of a local strategy of maximising the number of beneficial connections attainable under the constraint of limited individual travelling-time budgets. By incorporating census and openly-available online multi-modal transport data, we are able to characterise the connectivity of geometrically and topologically complex cities. Beyond providing a candidate measure of greatness, this model allows one to quantify and assess the impact of transport developments, population growth, and other infrastructure and demographic changes on a city. Supported by validations of GDP and HIV infection rates across United States metropolitan areas, we illustrate the effect of changes in local and city-wide connectivities by considering the economic impact of two contemporary inter- and intra-city transport developments in the United Kingdom: High Speed Rail 2 and London Crossrail. This derivation of the model suggests that the scaling of different urban indicators with population size has an explicitly mechanistic origin.Comment: 19 pages, 8 figure

Generalized Linear Models for Geometrical Current predictors. An application to predict garment fit

The aim of this paper is to model an ordinal response variable in terms of vector-valued functional data included on a vector-valued RKHS. In particular, we focus on the vector-valued RKHS obtained when a geometrical object (body) is characterized by a current and on the ordinal regression model. A common way to solve this problem in functional data analysis is to express the data in the orthonormal basis given by decomposition of the covariance operator. But our data present very important differences with respect to the usual functional data setting. On the one hand, they are vector-valued functions, and on the other, they are functions in an RKHS with a previously defined norm. We propose to use three different bases: the orthonormal basis given by the kernel that defines the RKHS, a basis obtained from decomposition of the integral operator defined using the covariance function, and a third basis that combines the previous two. The three approaches are compared and applied to an interesting problem: building a model to predict the fit of children’s garment sizes, based on a 3D database of the Spanish child population. Our proposal has been compared with alternative methods that explore the performance of other classifiers (Suppport Vector Machine and k-NN), and with the result of applying the classification method proposed in this work, from different characterizations of the objects (landmarks and multivariate anthropometric measurements instead of currents), obtaining in all these cases worst results

Spontaneous creation of discrete breathers in Josephson arrays

We report on the experimental generation of discrete breather states (intrinsic localized modes) in frustrated Josephson arrays. Our experiments indicate the formation of discrete breathers during the transition from the static to the dynamic (whirling) system state, induced by a uniform external current. Moreover, spatially extended resonant states, driven by a uniform current, are observed to evolve into localized breather states. Experiments were performed on single Josephson plaquettes as well as open-ended Josephson ladders with 10 and 20 cells. We interpret the breather formation as the result of the penetration of vortices into the system.Comment: 5 pages, 5 figure

Some Results of the Educational Experiment APIS (Cervantes Mission on Board ISS)

Some results of the analysis of the pictures taken along the performance of the Análisis de Propiedades Inerciales de Sólidos, Analysis of the Inertia Properties of Solid Bodies (APIS) experiment carried out in the Cervantes mission on board ISS, are presented. APIS was an educational experiment devoted to take advantage of the unique conditions of absence of relative gravity forces of a space platform such as ISS, to show some of the characteristics of the free rotational motion of a solid body, which are impossible to carry out on earth. This field of experimental research has application to aerospace engineering science (e.g. attitude control of spacecrafts), to astrophysical sciences (e.g. state of rotation and tumbling motions of asteroids) and to engineering education. To avoid the effect of the ambient atmosphere loads on the motion, the test body is placed inside a sphere, which reduces the effect of the aerodynamic forces to just friction. The drastic reduction of the effect of the surrounding air during the short duration of the experimental sequences allows us to compare the actual motion with the known solutions for the solid body rotation in vacuum. In this paper, some selected, relevant sequences of the sphere enclosing a body with a nominal cylindrical inertia tensor, put into rotation by the astronaut, are shown; the main problems to extract the information concerning the characteristic parameters of the motion are outlined, and some of the results obtained concerning the motion of the test probe are included, which show what seems to be a curious and unexpected solution of the Euler equations for the solid body rotation in vacuum, without energy dissipation, when the angular momentum is almost perpendicular to the axisymmetry axis

Stationary distributions of continuous-time Markov chains: a review of theory and truncation-based approximations

Computing the stationary distributions of a continuous-time Markov chain involves solving a set of linear equations. In most cases of interest, the number of equations is infinite or too large, and cannot be solved analytically or numerically. Several approximation schemes overcome this issue by truncating the state space to a manageable size. In this review, we first give a comprehensive theoretical account of the stationary distributions and their relation to the long-term behaviour of the Markov chain, which is readily accessible to non-experts and free of irreducibility assumptions made in standard texts. We then review truncation-based approximation schemes paying particular attention to their convergence and to the errors they introduce, and we illustrate their performance with an example of a stochastic reaction network of relevance in biology and chemistry. We conclude by elaborating on computational trade-offs associated with error control and some open questions

The exit time finite state projection scheme: bounding exit distributions and occupation measures of continuous-time Markov chains

We introduce the exit time finite state projection (ETFSP) scheme, a truncation- based method that yields approximations to the exit distribution and occupation measure associated with the time of exit from a domain (i.e., the time of first passage to the complement of the domain) of time-homogeneous continuous-time Markov chains. We prove that: (i) the computed approximations bound the measures from below; (ii) the total variation distances between the approximations and the measures decrease monotonically as states are added to the truncation; and (iii) the scheme converges, in the sense that, as the truncation tends to the entire state space, the total variation distances tend to zero. Furthermore, we give a computable bound on the total variation distance between the exit distribution and its approximation, and we delineate the cases in which the bound is sharp. We also revisit the related finite state projection scheme and give a comprehensive account of its theoretical properties. We demonstrate the use of the ETFSP scheme by applying it to two biological examples: the computation of the first passage time associated with the expression of a gene, and the fixation times of competing species subject to demographic noise

Bounding the stationary distributions of the chemical master equation via mathematical programming

The stochastic dynamics of biochemical networks are usually modelled with the chemical master equation (CME). The stationary distributions of CMEs are seldom solvable analytically, and numerical methods typically produce estimates with uncontrolled errors. Here, we introduce mathematical programming approaches that yield approximations of these distributions with computable error bounds which enable the verification of their accuracy. First, we use semidefinite programming to compute increasingly tighter upper and lower bounds on the moments of the stationary distributions for networks with rational propensities. Second, we use these moment bounds to formulate linear programs that yield convergent upper and lower bounds on the stationary distributions themselves, their marginals and stationary averages. The bounds obtained also provide a computational test for the uniqueness of the distribution. In the unique case, the bounds form an approximation of the stationary distribution with a computable bound on its error. In the non unique case, our approach yields converging approximations of the ergodic distributions. We illustrate our methodology through several biochemical examples taken from the literature: Schl¨ogl’s model for a chemical bifurcation, a two-dimensional toggle switch, a model for bursty gene expression, and a dimerisation model with multiple stationary distributions

Lower Critical Dimension of Ising Spin Glasses

Exact ground states of two-dimensional Ising spin glasses with Gaussian and bimodal (+- J) distributions of the disorder are calculated using a ``matching'' algorithm, which allows large system sizes of up to N=480^2 spins to be investigated. We study domain walls induced by two rather different types of boundary-condition changes, and, in each case, analyze the system-size dependence of an appropriately defined ``defect energy'', which we denote by DE. For Gaussian disorder, we find a power-law behavior DE ~ L^\theta, with \theta=-0.266(2) and \theta=-0.282(2) for the two types of boundary condition changes. These results are in reasonable agreement with each other, allowing for small systematic effects. They also agree well with earlier work on smaller sizes. The negative value indicates that two dimensions is below the lower critical dimension d_c. For the +-J model, we obtain a different result, namely the domain-wall energy saturates at a nonzero value for L\to \infty, so \theta = 0, indicating that the lower critical dimension for the +-J model exactly d_c=2.Comment: 4 pages, 4 figures, 1 table, revte