Spin-pumping and inelastic electron tunneling spectroscopy in topological insulators

We demonstrate that a quantum spin Hall current, spontaneously generated at the edge of a two-dimensional topological insulator, acts as a source of spin-pumping for a magnetic impurity with uniaxial anisotropy. One can then manipulate the impurity spin direction by means of an electrical current without using either magnetic electrodes or an external magnetic field. Furthermore we show that the unique properties of the quantum spin Hall topological state have profound effects on the inelastic electron tunneling spectrum of the impurity. For low current densities inelastic spin-flip events do not contribute to the conductance. As a consequence the conductance steps, normally appearing at voltages corresponding to the spin excitations, are completely suppressed. In contrast an intense current leads to spin pumping and generates a transverse component of the impurity spin. This breaks the topological phase yielding to the conductance steps.Comment: Updated text, added figure, published versio

Spin-flip inelastic electron tunneling spectroscopy in atomic chains

We present a theoretical study of the spin transport properties of mono-atomic magnetic chains with a focus on the spectroscopical features of the I-V curve associated to spin-flip processes. Our calculations are based on the s-d model for magnetism with the electron transport treated at the level of the non-equilibrium Green's function formalism. Inelastic spin-flip scattering processes are introduced perturbatively via the first Born approximation and an expression for the associated self-energy is derived. The computational method is then applied to describe the I-V characteristics and its derivatives of one dimensional chains of Mn atoms and the results are then compared to available experimental data. We find a qualitative and quantitative agreement between the calculated and the experimental conductance spectra. Significantly we are able to describe the relative intensities of the spin excitation features in the I-V curve, by means of a careful analysis of the spin transition selection rules associated to the atomic chains

Bias asymmetry in the conductance profile of magnetic ions on surfaces probed by scanning tunneling microscopy

The conductance profiles of magnetic transition metal atoms, such as Fe, Co and Mn, deposited on surfaces and probed by a scanning tunneling microscope (STM), provide detailed information on the magnetic excitations of such nano-magnets. In general the profiles are symmetric with respect to the applied bias. However a set of recent experiments has shown evidence for inherent asymmetries when either a normal or a spin-polarized STM tip is used. In order to explain such asymmetries here we expand our previously developed perturbative approach to electron-spin scattering to the spin- polarized case and to the inclusion of out of equilibrium spin populations. In the case of a magnetic STM tip we demonstrate that the asymmetries are driven by the non-equilibrium occupation of the various atomic spin-levels, an effect that reminds closely that electron spin-transfer. In contrast when the tip is not spin-polarized such non-equilibrium population cannot be build up. In this circumstance we propose that the asymmetry simply originates from the transition metal ion density of state, which is included here as a non-vanishing real component to the spin-scattering self-energy

Stretching the Safety Net to Serve Undocumented Immigrants: Community Responses to Health Needs

Examines the ability of communities to provide health care for both legal and undocumented immigrant patients. Looks at community diversity, political climate, and advocacy groups. Based on site visits to twelve nationally representative communities

Detecting highly overlapping community structure by greedy clique expansion

In complex networks it is common for each node to belong to several communities, implying a highly overlapping community structure. Recent advances in benchmarking indicate that existing community assignment algorithms that are capable of detecting overlapping communities perform well only when the extent of community overlap is kept to modest levels. To overcome this limitation, we introduce a new community assignment algorithm called Greedy Clique Expansion (GCE). The algorithm identifies distinct cliques as seeds and expands these seeds by greedily optimizing a local fitness function. We perform extensive benchmarks on synthetic data to demonstrate that GCE's good performance is robust across diverse graph topologies. Significantly, GCE is the only algorithm to perform well on these synthetic graphs, in which every node belongs to multiple communities. Furthermore, when put to the task of identifying functional modules in protein interaction data, and college dorm assignments in Facebook friendship data, we find that GCE performs competitively.Comment: 10 pages, 7 Figures. Implementation source and binaries available at http://sites.google.com/site/greedycliqueexpansion