Out of Equilibrium Solutions in the XYXY-Hamiltonian Mean Field model

Out of equilibrium magnetised solutions of the $XY$-Hamiltonian Mean Field ($XY$-HMF) model are build using an ensemble of integrable uncoupled pendula. Using these solutions we display an out-of equilibrium phase transition using a specific reduced set of the magnetised solutions

Large deviations for ideal quantum systems

We consider a general d-dimensional quantum system of non-interacting particles, with suitable statistics, in a very large (formally infinite) container. We prove that, in equilibrium, the fluctuations in the density of particles in a subdomain of the container are described by a large deviation function related to the pressure of the system. That is, untypical densities occur with a probability exponentially small in the volume of the subdomain, with the coefficient in the exponent given by the appropriate thermodynamic potential. Furthermore, small fluctuations satisfy the central limit theorem.Comment: 28 pages, LaTeX 2

Pump-probe scheme for electron-photon dynamics in hybrid conductor-cavity systems

Recent experiments on nanoscale conductors coupled to microwave cavities put in prospect transport investigations of electron-photon interplay in the deep quantum regime. Here we propose a pump-probe scheme to investigate the transient dynamics of individual electron-photon excitations in a double quantum dot-cavity system. Excitations pumped into the system decay via charge tunneling at the double dot, probed in real time. We investigate theoretically the short-time charge transfer statistics at the dot, for periodic pumping, and show that this gives access to vacuum Rabi oscillations as well as excitation dynamics in the presence of double dot dephasing and relaxation.Comment: 5 Pages, 5 figure

Cross-species extrapolation of chemical sensitivity

Ecosystems are usually populated by many species. Each of these species carries the potential to show a different sensitivity towards all of the numerous chemical compounds that can be present in their environment. Since experimentally testing all possible species-chemical combinations is impossible, the ecological risk assessment of chemicals largely depends on cross-species extrapolation approaches. This review overviews currently existing cross-species extrapolation methodologies, and discusses i) how species sensitivity could be described, ii) which predictors might be useful for explaining differences in species sensitivity, and iii) which statistical considerations are important. We argue that risk assessment can benefit most from modelling approaches when sensitivity is described based on ecologically relevant and robust effects. Additionally, specific attention should be paid to heterogeneity of the training data (e.g. exposure duration, pH, temperature), since this strongly influences the reliability of the resulting models. Regarding which predictors are useful for explaining differences in species sensitivity, we review interspecies-correlation, relatedness-based, traits-based, and genomic-based extrapolation methods, describing the amount of mechanistic information the predictors contain, the amount of input data the models require, and the extent to which the different methods provide protection for ecological entities. We develop a conceptual framework, incorporating the strengths of each of the methods described. Finally, the discussion of statistical considerations reveals that regardless of the method used, statistically significant models can be found, although the usefulness, applicability, and understanding of these models varies considerably. We therefore recommend publication of scientific code along with scientific studies to simultaneously clarify modelling choices and enable elaboration on existing work. In general, this review specifies the data requirements of different cross-species extrapolation methods, aiming to make regulators and publishers more aware that access to raw- and meta-data needs to be improved to make future cross-species extrapolation efforts successful, enabling their integration into the regulatory environment

On the minimization of Dirichlet eigenvalues of the Laplace operator

We study the variational problem \inf \{\lambda_k(\Omega): \Omega\ \textup{open in}\ \R^m,\ |\Omega| < \infty, \ \h(\partial \Omega) \le 1 \}, where $\lambda_k(\Omega)$ is the $k$'th eigenvalue of the Dirichlet Laplacian acting in $L^2(\Omega)$, \h(\partial \Omega) is the $(m-1)$- dimensional Hausdorff measure of the boundary of $\Omega$, and $|\Omega|$ is the Lebesgue measure of $\Omega$. If $m=2$, and $k=2,3, \cdots$, then there exists a convex minimiser $\Omega_{2,k}$. If $m \ge 2$, and if $\Omega_{m,k}$ is a minimiser, then $\Omega_{m,k}^*:= \textup{int}(\overline{\Omega_{m,k}})$ is also a minimiser, and $\R^m\setminus \Omega_{m,k}^*$ is connected. Upper bounds are obtained for the number of components of $\Omega_{m,k}$. It is shown that if $m\ge 3$, and $k\le m+1$ then $\Omega_{m,k}$ has at most $4$ components. Furthermore $\Omega_{m,k}$ is connected in the following cases : (i) $m\ge 2, k=2,$ (ii) $m=3,4,5,$ and $k=3,4,$ (iii) $m=4,5,$ and $k=5,$ (iv) $m=5$ and $k=6$. Finally, upper bounds on the number of components are obtained for minimisers for other constraints such as the Lebesgue measure and the torsional rigidity.Comment: 16 page

Application-level performance of cross-layer scheduling for social VR in 5G

Social VR aims at enabling people located at different places to communicate and interact with each other in a natural way. It poses extremely strong throughput and latency requirements on the underlying communication networks. This paper investigates the potential of using cross-layer design approaches for radio access scheduling in order to realize these challenging requirements in (beyond) 5G networks. In particular, we provide an in-depth simulation study of the performance/capacity gains that can be achieved by exploiting the end-to-end latency budget and/or video frame type as cross-layer information in the scheduling decisions, and show how the benefits depend on the actual social VR scenario. This study further reveals the importance of using application-level metrics such as PSNR or SSIM rather than traditional network-level metrics like the packet drop rate in the performance assessment.</p

Volkov-Pankratov states in topological graphene nanoribbons

In topological systems, a modulation in the gap onset near interfaces can lead to the appearance of massive edge states, as were first described by Volkov and Pankratov. In this work, we study graphene nanoribbons in the presence of intrinsic spin-orbit coupling smoothly modulated near the system edges. We show that this space modulation leads to the appearance of Volkov-Pankratov states, in addition to the topologically protected ones. We obtain this result by means of two complementary methods, one based on the effective low-energy Dirac equation description and the other on a fully numerical tight-binding approach, finding excellent agreement between the two. We then show how transport measurements might reveal the presence of Volkov-Pankratov states, and discuss possible graphenelike structures in which such states might be observed