Discrete rearranging disordered patterns, part I: Robust statistical tools in two or three dimensions

Discrete rearranging patterns include cellular patterns, for instance liquid foams, biological tissues, grains in polycrystals; assemblies of particles such as beads, granular materials, colloids, molecules, atoms; and interconnected networks. Such a pattern can be described as a list of links between neighbouring sites. Performing statistics on the links between neighbouring sites yields average quantities (hereafter "tools") as the result of direct measurements on images. These descriptive tools are flexible and suitable for various problems where quantitative measurements are required, whether in two or in three dimensions. Here, we present a coherent set of robust tools, in three steps. First, we revisit the definitions of three existing tools based on the texture matrix. Second, thanks to their more general definition, we embed these three tools in a self-consistent formalism, which includes three additional ones. Third, we show that the six tools together provide a direct correspondence between a small scale, where they quantify the discrete pattern's local distortion and rearrangements, and a large scale, where they help describe a material as a continuous medium. This enables to formulate elastic, plastic, fluid behaviours in a common, self-consistent modelling using continuous mechanics. Experiments, simulations and models can be expressed in the same language and directly compared. As an example, a companion paper (Marmottant, Raufaste and Graner, joint paper) provides an application to foam plasticity

Estimation and decomposition of downside risk for portfolios with non-normal returns.

We propose a new estimator for Expected Shortfall that uses asymptotic expansions to account for the asymmetry and heavy tails in financial returns. We provide all the necessary formulas for decomposing estimators of Value at Risk and Expected Shortfall based on asymptotic expansions and show that this new methodology is very useful for analyzing and predicting the risk properties of portfolios of alternative investments.Alternative investments; Component expected shortfall; Cornish-Fisher expansion; Downside risk; Expected shortfall; Portfolio; Risk contribution; Value at risk;

Thermal and solutal convection with conduction effects inside a rectangular enclosure

We numerically investigate the effects of various boundary conditions on the flow field characteristics of the physical vapor transport process. We use a prescribed temperature profile as boundary condition on the enclosure walls, and we consider parametric variations applicable to ground-based and space microgravity conditions. For ground-based applications, density gradients in the fluid phase generate buoyancy-driven convection which in turn disrupts the uniformity of the mass flux at the interface depending on the orientation. Heat conduction in the crystal can affect the fluid flow near the interface of the crystal. When considering isothermal source and sink at the interfaces, we observe a diffusive mode and three modes (i.e., thermal, solutal, and thermo-solutal). The convective modes show opposing flow field trends between thermal and solutal convection; theoretically, these trends can be used to achieve a uniform mass flux near the crystal. However, under the physical conditions chosen, the mathematical condition necessary for uniform mass flux cannot be satisfied because of thermodynamic restrictions. When a longitudinal thermal gradient is prescribed on the boundary of the crystal, a non-uniform interface temperature results, which induces a symmetrical fluid flow near the interface for the vertical case. For space microgravity applications, we show that the flow field is dominated by the Stefan wind and a uniform mass flux results at the interface

Sparse classification boundaries

Given a training sample of size $m$ from a $d$-dimensional population, we wish to allocate a new observation $Z\in \R^d$ to this population or to the noise. We suppose that the difference between the distribution of the population and that of the noise is only in a shift, which is a sparse vector. For the Gaussian noise, fixed sample size $m$, and the dimension $d$ that tends to infinity, we obtain the sharp classification boundary and we propose classifiers attaining this boundary. We also give extensions of this result to the case where the sample size $m$ depends on $d$ and satisfies the condition $(\log m)/\log d \to \gamma$, $0\le \gamma<1$, and to the case of non-Gaussian noise satisfying the Cram\'er condition

Estimation and decomposition of downside risk for portfolios with non-normal returns.

Modied Value at Risk (VaR) is an estimator of VaR based on the Cornish-Fisher expansion. It is fast to compute and reliable for non-normal returns. In this paper, we introduce modified Expected Shortfall as a new analytical estimator for Expected Shortfall (ES), another popular measure of downside risk. We give all the necessary formulas for computing portfolio modified VaR and ES and for decomposing these risk measures into the contributions made by each of the portfolio holdings. This new methodology is shown to be very useful for analyzing the risk properties of portfolios of alternative investments.

Effect of connecting wires on the decoherence due to electron-electron interaction in a metallic ring

We consider the weak localization in a ring connected to reservoirs through leads of finite length and submitted to a magnetic field. The effect of decoherence due to electron-electron interaction on the harmonics of AAS oscillations is studied, and more specifically the effect of the leads. Two results are obtained for short and long leads regimes. The scale at which the crossover occurs is discussed. The long leads regime is shown to be more realistic experimentally.Comment: LaTeX, 4 pages, 4 eps figure

Weak localization in multiterminal networks of diffusive wires

We study the quantum transport through networks of diffusive wires connected to reservoirs in the Landauer-B\"uttiker formalism. The elements of the conductance matrix are computed by the diagrammatic method. We recover the combination of classical resistances and obtain the weak localization corrections. For arbitrary networks, we show how the cooperon must be properly weighted over the different wires. Its nonlocality is clearly analyzed. We predict a new geometrical effect that may change the sign of the weak localization correction in multiterminal geometries.Comment: 4 pages, LaTeX, 4 figures, 8 eps file

Approximating multiple class queueing models with loss models

Multiple class queueing models arise in situations where some flexibility is sought through pooling of demands for different services. Earlier research has shown that most of the benefits of flexibility can be obtained with only a small proportion of cross-trained operators. Predicting the performance of a system with different types of demands and operator pools with different skills is very difficult. We present an approximation method that is based on equivalent loss systems. We successively develop approximations for the waiting probability, The average waiting time and the service level. Our approximations are validated using a series of simulations. Along the way we present some interesting insights into some similarities between queueing systems and equivalent loss systems that have to our knowledge never been reported in the literature.