Magnetic chirality as probed by neutron scattering

We review the concept of chirality, at first briefly in a general context then in the specific framework of the spin networks. We next discuss to what extent neutron scattering appears as an unconvertible tool to probe magnetic chirality in the static and dynamical regimes of the spins. The remarkable chiral ground state and excitations of the Fe-langasite compound finally serves to illustrate the use of neutron polarimetry in the experimental studies of the magnetic chirality.Comment: 32 page

Are grain markets in Niger driven by speculation?

Over the last two decades, millet prices in Niger have enjoyed periods of spectacular increase during which they seem to go well above their fundamental value. These episodes of price bursts followed by rapid reversals could be attributed to the presence of rational speculative bubbles. Considering millet as a food asset we have developed a pricing model, and tested for the presence of periodically and partially collapsing bubbles for 15 millet markets in Niger. The test strategy consists of estimating the fundamental value of millet and investigating the dynamic properties of price deviations from fundamentals. A battery of unit root tests aimed at controlling for skewness and kurtosis, and for non linearity in the bubble process, is implemented. These tests do not reject the presence of rational bubbles for some of the sample markets, and allow the identification of expanding and collapsing phases in bubble processes. The results show that small markets, located in deficit and remote areas are more prone to speculation than large markets in the main producing and consuming regions.periodically collapsing bubbles, M-TAR, Markov switching ADF, Residual Augmented ADF test, Rolling ADF test, millet

Propagation and Ghosts in the Classical Kagome Antiferromagnet

We investigate the classical spin dynamics of the kagome antiferromagnet by combining Monte Carlo and spin dynamics simulations. We show that this model has two distinct low temperature dynamical regimes, both sustaining propagative modes. The expected gauge invariance type of the low energy low temperature out of plane excitations is also evidenced in the non linear regime. A detailed analysis of the excitations allows to identify ghosts in the dynamical structure factor, i.e propagating excitations with a strongly reduced spectral weight. We argue that these dynamical extinction rules are of geometrical origin.Comment: 4+ pages, 4 figures. Accepted for publication in the Physical Review Letter

Spectral analysis of unsteady flow simulation in a small VAWT

The vertical axis wind turbine studied in this paper combine two rotations: one rotating movement of each blade around its own axis and one rotating movement around turbine’s axis. The aim of this paper is to analyse the effect of this two combine movements on fields of pressure and on global forces on each blade with time. Preliminary calculations showed, for some initial blade stagger angles (angle between blade 1 and x axis), that flow is highly unsteady and sometimes hardly periodic. The main goal here is to present spectral analysis of unsteady results like temporal pressure on specific points in the domain and temporal forces on blades and to show the influence of the two combine movements for two different blade stagger angles for elliptic blades

ClustGeo: an R package for hierarchical clustering with spatial constraints

In this paper, we propose a Ward-like hierarchical clustering algorithm including spatial/geographical constraints. Two dissimilarity matrices $D_0$ and $D_1$ are inputted, along with a mixing parameter $\alpha \in [0,1]$. The dissimilarities can be non-Euclidean and the weights of the observations can be non-uniform. The first matrix gives the dissimilarities in the "feature space" and the second matrix gives the dissimilarities in the "constraint space". The criterion minimized at each stage is a convex combination of the homogeneity criterion calculated with $D_0$ and the homogeneity criterion calculated with $D_1$. The idea is then to determine a value of $\alpha$ which increases the spatial contiguity without deteriorating too much the quality of the solution based on the variables of interest i.e. those of the feature space. This procedure is illustrated on a real dataset using the R package ClustGeo