Topological Hochschild homology of twisted group algebras

We show the topological Hochschild homology spectrum of a twisted group algebra \THH(A^{\tau}[G]) is the Thom spectrum associated to a parametrized orthogonal spectrum $E(A,G)$. We then analyze the structure of the parametrized orthogonal spectrum $E(A,G)$ and show that it is locally trivial

Multilayer primitive equations model with velocity shear and stratification

The purpose of this paper is to present a multilayer primitive equations model for ocean dynamics in which the velocity and buoyancy fields within each layer are not only allowed to vary arbitrarily with horizontal position and time, but also with depth--linearly at most. The model is a generalization of Ripa's inhomogeneous one-layer model to an arbitrary number of layers. Unlike models with homogeneous layers, the present model is able to represent thermodynamics processes. Unlike models with slab layers, i.e. those in which the layer velocity and buoyancy fields are depth-independent, the present model can represent explicitly the thermal-wind balance within each layer which dominates at low frequency. In the absence of external forcing and dissipation, energy, volume, mass, and buoyancy variance constrain the dynamics; conservation of total zonal momentum requires in addition the usual zonal symmetry of the topography and horizontal domain. The model further possesses a singular Hamiltonian structure. Unlike the single-layer counterpart, however, no steady solution has been possible to prove formally (or Arnold) stable using the above invariants. It is shown here that a model with only two layers provides an excellent representation of the exact gravest baroclinic mode phase speed. This suggests that configurations with only a small number of layers will be needed to tackle a large variety of problems with enough realism

Nonlinear interaction of spin and charge currents in graphene

We describe a nonlinear interaction between charge currents and spin currents which arises from the energy dependence of the conductivity. This allows nonmagnetic contacts to be used for measuring and controlling spin signals. We choose graphene as a model system to study these effects and predict its magnitudes in nonlocal spin valve devices. The ambipolar behavior of graphene is used to demonstrate amplification of spin accumulation in p-n junctions by applying a charge current through nonmagnetic contacts.Comment: minor changes, 4 pages, 3 figure

Nonfractional Memory: Filtering, Antipersistence, and Forecasting

The fractional difference operator remains to be the most popular mechanism to generate long memory due to the existence of efficient algorithms for their simulation and forecasting. Nonetheless, there is no theoretical argument linking the fractional difference operator with the presence of long memory in real data. In this regard, one of the most predominant theoretical explanations for the presence of long memory is cross-sectional aggregation of persistent micro units. Yet, the type of processes obtained by cross-sectional aggregation differs from the one due to fractional differencing. Thus, this paper develops fast algorithms to generate and forecast long memory by cross-sectional aggregation. Moreover, it is shown that the antipersistent phenomenon that arises for negative degrees of memory in the fractional difference literature is not present for cross-sectionally aggregated processes. Pointedly, while the autocorrelations for the fractional difference operator are negative for negative degrees of memory by construction, this restriction does not apply to the cross-sectional aggregated scheme. We show that this has implications for long memory tests in the frequency domain, which will be misspecified for cross-sectionally aggregated processes with negative degrees of memory. Finally, we assess the forecast performance of high-order $AR$ and $ARFIMA$ models when the long memory series are generated by cross-sectional aggregation. Our results are of interest to practitioners developing forecasts of long memory variables like inflation, volatility, and climate data, where aggregation may be the source of long memory

Non-linear spin Seebeck effect due to spin-charge interaction in graphene

The abilities to inject and detect spin carriers are fundamental for research on transport and manipulation of spin information. Pure electronic spin currents have been recently studied in nanoscale electronic devices using a non-local lateral geometry, both in metallic systems and in semiconductors. To unlock the full potential of spintronics we must understand the interactions of spin with other degrees of freedom, going beyond the prototypical electrical spin injection and detection using magnetic contacts. Such interactions have been explored recently, for example, by using spin Hall or spin thermoelectric effects. Here we present the detection of non-local spin signals using non-magnetic detectors, via an as yet unexplored non-linear interaction between spin and charge. In analogy to the Seebeck effect, where a heat current generates a charge potential, we demonstrate that a spin current in a paramagnet leads to a charge potential, if the conductivity is energy dependent. We use graphene as a model system to study this effect, as recently proposed. The physical concept demonstrated here is generally valid, opening new possibilities for spintronics

Linking adult second language learning and diachronic change:a cautionary note

It has been suggested that the morphological complexity of a language is negatively correlated with the size of its population of speakers. This relationship may be driven by the proportion of non-native speakers, among other things, and reflects adaptations to learning constraints imposed by adult language learners. Here we sound a note of caution with respect to these claims by arguing that (a) morphological complexity is defined in somewhat contradictory ways and hence not straightforward to measure, and (b) there is insufficient evidence to suggest that children’s cognitive limitations support mechanisms beneficial for learning of complex morphology relative to adults. We suggest that considering the informational value of morphological cues may be a better way to capture learnability of morphology. To settle the issue of how age related constraints on learning might impact language change, more cross-linguistic studies comparing learning trajectories of different second languages and laboratory experiments examining language transmission in children and adults are needed