Sensitivity of Helioseismic Measurements of Normal-mode Coupling to Flows and Sound-speed Perturbations

In this article, we derive and compute the sensitivity of measurements of coupling between normal modes of oscillation in the Sun to underlying flows. The theory is based on first-Born perturbation theory, and the analysis is carried out using the formalism described by \citet{lavely92}. Albeit tedious, we detail the derivation and compute the sensitivity of specific pairs of coupled normal modes to anomalies in the interior. Indeed, these kernels are critical for the accurate inference of convective flow amplitudes and large-scale circulations in the solar interior. We resolve some inconsistencies in the derivation of \citet{lavely92} and reformulate the fluid-continuity condition. We also derive and compute sound-speed kernels, paving the way for inverting for thermal anomalies alongside flows.Comment: 24 pages, 8 Figures; MNRA

Directed transport of Brownian particles in a double symmetric potential

We investigate the dynamics of Brownian particles in internal state- dependent symmetric and periodic potentials. Although no space or time symmetry of the Hamiltonian is broken, we show that directed transport can appear. We demonstrate that the directed motion is induced by breaking the symmetry of the transition rates between the potentials when these are spatially shifted. Finally, we discuss the possibility of realizing our model in a system of cold particles trapped in optical lattices.Comment: to appear in Physical Review

Dynamical Encoding by Networks of Competing Neuron Groups: Winnerless Competition

Following studies of olfactory processing in insects and fish, we investigate neural networks whose dynamics in phase space is represented by orbits near the heteroclinic connections between saddle regions (fixed points or limit cycles). These networks encode input information as trajectories along the heteroclinic connections. If there are N neurons in the network, the capacity is approximately e(N-1)!, i.e., much larger than that of most traditional network structures. We show that a small winnerless competition network composed of FitzHugh-Nagumo spiking neurons efficiently transforms input information into a spatiotemporal output

On the linear extension complexity of stable set polytopes for perfect graphs

We study the linear extension complexity of stable set polytopes of perfect graphs. We make use of known structural results permitting to decompose perfect graphs into basic perfect graphs by means of two graph operations: 2-join and skew partitions. Exploiting the link between extension complexity and the nonnegative rank of an associated slack matrix, we investigate the behaviour of the extension complexity under these graph operations. We show bounds for the extension complexity of the stable set polytope of a perfect graph G depending linearly on the size of G and involving the depth of a decomposition tree of G in terms of basic perfect graphs

On the linear extension complexity of stable set polytopes for perfect graphs

We study the linear extension complexity of stable set polytopes of perfect graphs. We make use of known structural results permitting to decompose perfect graphs into basic perfect graphs by means of two graph operations: 2-joins and skew partitions. Exploiting the link between extension complexity and the nonnegative rank of an associated slack matrix, we investigate the behavior of the extension complexity under these graph operations. We show bounds for the extension complexity of the stable set polytope of a perfect graph G depending linearly on the size of G and involving the depth of a decomposition tree of G in terms of basic perfect graphs

A Study of the Formation of Single- and Double-Walled Carbon Nanotubes by a CVD Method

The reduction in H2/CH4 atmosphere of aluminum-iron oxides produces metal particles small enough to catalyze the formation of single-walled carbon nanotubes. Several experiments have been made using the same temperature profile and changing only the maximum temperature (800-1070 °C). Characterizations of the catalyst materials are performed using notably 57Fe Mo¨ssbauer spectroscopy. Electron microscopy and a macroscopical method are used to characterize the nanotubes. The nature of the iron species (Fe3+, R-Fe, ç-Fe-C, Fe3C) is correlated to their location in the material. The nature of the particles responsible for the high-temperature formation of the nanotubes is probably an Fe-C alloy which is, however, found as Fe3C by postreaction analysis. Increasing the reduction temperature increases the reduction yield and thus favors the formation of surface-metal particles, thus producing more nanotubes. The obtained carbon nanotubes are mostly single-walled and double-walled with an average diameter close to 2.5 nm. Several formation mechanisms are thought to be active. In particular, it is shown that the second wall can grow inside the first one but that subsequent ones are formed outside. It is also possible that under given experimental conditions, the smallest (<2 nm) catalyst particles preferentially produce double-walled rather than single-walled carbon nanotubes

Biphonons in the Klein-Gordon lattice

A numerical approach is proposed for studying the quantum optical modes in the Klein-Gordon lattices where the energy contribution of the atomic displacements is non-quadratic. The features of the biphonon excitations are investigated in detail for different non-quadratic contributions to the Hamiltonian. The results are extended to multi-phonon bound states.Comment: Comments and suggestions are welcom