The Bispectrum of IRAS Galaxies

We compute the bispectrum for the galaxy distribution in the IRAS QDOT, 2Jy, and 1.2Jy redshift catalogs for wavenumbers 0.05<k<0.2 h/Mpc and compare the results with predictions from gravitational instability in perturbation theory. Taking into account redshift space distortions, nonlinear evolution, the survey selection function, and discreteness and finite volume effects, all three catalogs show evidence for the dependence of the bispectrum on configuration shape predicted by gravitational instability. Assuming Gaussian initial conditions and local biasing parametrized by linear and non-linear bias parameters b_1 and b_2, a likelihood analysis yields 1/b_1 = 1.32^{+0.36}_{-0.58}, 1.15^{+0.39}_{-0.39} and b_2/b_1^2=-0.57^{+0.45}_{-0.30}, -0.50^{+0.31}_{-0.51}, for the for the 2Jy and 1.2Jy samples, respectively. This implies that IRAS galaxies trace dark matter increasingly weakly as the density contrast increases, consistent with their being under-represented in clusters. In a model with chi^2 non-Gaussian initial conditions, the bispectrum displays an amplitude and scale dependence different than that found in the Gaussian case; if IRAS galaxies do not have bias b_1> 1 at large scales, \chi^2 non-Gaussian initial conditions are ruled out at the 95% confidence level. The IRAS data do not distinguish between Lagrangian or Eulerian local bias.Comment: 30 pages, 11 figure

Gravity and Large-Scale Non-local Bias

The relationship between galaxy and matter overdensities, bias, is most often assumed to be local. This is however unstable under time evolution, we provide proofs under several sets of assumptions. In the simplest model galaxies are created locally and linearly biased at a single time, and subsequently move with the matter (no velocity bias) conserving their comoving number density (no merging). We show that, after this formation time, the bias becomes unavoidably non-local and non-linear at large scales. We identify the non-local gravitationally induced fields in which the galaxy overdensity can be expanded, showing that they can be constructed out of the invariants of the deformation tensor (Galileons). In addition, we show that this result persists if we include an arbitrary evolution of the comoving number density of tracers. We then include velocity bias, and show that new contributions appear, a dipole field being the signature at second order. We test these predictions by studying the dependence of halo overdensities in cells of fixed matter density: measurements in simulations show that departures from the mean bias relation are strongly correlated with the non-local gravitationally induced fields identified by our formalism. The effects on non-local bias seen in the simulations are most important for the most biased halos, as expected from our predictions. The non-locality seen in the simulations is not fully captured by assuming local bias in Lagrangian space. Accounting for these effects when modeling galaxy bias is essential for correctly describing the dependence on triangle shape of the galaxy bispectrum, and hence constraining cosmological parameters and primordial non-Gaussianity. We show that using our formalism we remove an important systematic in the determination of bias parameters from the galaxy bispectrum, particularly for luminous galaxies. (abridged)Comment: 26 pages, 9 figures. v2: improved appendix

Atomic structure of Ge quantum dots on the Si(001) surface

In situ morphological investigation of the {105} faceted Ge islands on the Si(001) surface (hut clusters) have been carried out using an ultra high vacuum instrument integrating a high resolution scanning tunnelling microscope and a molecular beam epitaxy vessel. Both species of hut clusters--pyramids and wedges--were found to have the same structure of the {105} facets which was visualized. Structures of vertexes of the pyramidal clusters and ridges of the wedge-shaped clusters were revealed as well and found to be different. This allowed us to propose a crystallographic model of the {105} facets as well as models of the atomic structure of both species of the hut clusters. An inference is made that transitions between the cluster shapes are impossible.Comment: 6 pages, 6 figures. Accepted to JETP Letters (publication date 2010-03-25

An open and parallel multiresolution framework using block-based adaptive grids

A numerical approach for solving evolutionary partial differential equations in two and three space dimensions on block-based adaptive grids is presented. The numerical discretization is based on high-order, central finite-differences and explicit time integration. Grid refinement and coarsening are triggered by multiresolution analysis, i.e. thresholding of wavelet coefficients, which allow controlling the precision of the adaptive approximation of the solution with respect to uniform grid computations. The implementation of the scheme is fully parallel using MPI with a hybrid data structure. Load balancing relies on space filling curves techniques. Validation tests for 2D advection equations allow to assess the precision and performance of the developed code. Computations of the compressible Navier-Stokes equations for a temporally developing 2D mixing layer illustrate the properties of the code for nonlinear multi-scale problems. The code is open source

A sticky situation: CCN1 promotes both proliferation and apoptosis of cancer cells

Members of the CCN family of matricellular signaling regulators promote cell adhesion through integrins and heparan sulfate-containing proteoglycans. A paradox of the CCN field is that, depending on the set of circumstances examined, individual CCN molecules can have quite different, and often opposing, effects. In a recent report, Franzen and colleagues (Mol Cancer Res. 7:1045–1055, 2009) show using siRNA knockdown that CCN1 (cyr61) is essential for the proliferation of prostate cancer cells. Intriguingly, on the other hand, CCN1 also enhances TRAIL-induced apoptosis. Thus the utility of anti-CCN1 therapy in cancer needs to be carefully considered in light of these divergent results. The significance of this paper is discussed

Creation and control of a two-dimensional electron liquid at the bare SrTiO3 surface

Many-body interactions in transition-metal oxides give rise to a wide range of functional properties, such as high-temperature superconductivity, colossal magnetoresistance, or multiferroicity. The seminal recent discovery of a two-dimensional electron gas (2DEG) at the interface of the insulating oxides LaAlO3 and SrTiO3 represents an important milestone towards exploiting such properties in all-oxide devices. This conducting interface shows a number of appealing properties, including a high electron mobility, superconductivity, and large magnetoresistance and can be patterned on the few-nanometer length scale. However, the microscopic origin of the interface 2DEG is poorly understood. Here, we show that a similar 2DEG, with an electron density as large as 8x10^13 cm^-2, can be formed at the bare SrTiO3 surface. Furthermore, we find that the 2DEG density can be controlled through exposure of the surface to intense ultraviolet (UV) light. Subsequent angle-resolved photoemission spectroscopy (ARPES) measurements reveal an unusual coexistence of a light quasiparticle mass and signatures of strong many-body interactions.Comment: 14 pages, 4 figures, supplementary information (see other files

Data taking strategy for the phase study in ψ′→K+K−\psi^{\prime} \to K^+K^-

The study of the relative phase between strong and electromagnetic amplitudes is of great importance for understanding the dynamics of charmonium decays. The information of the phase can be obtained model-independently by fitting the scan data of some special decay channels, one of which is $\psi^{\prime} \to K^{+}K^{-}$. To find out the optimal data taking strategy for a scan experiment in the measurement of the phase in $\psi^{\prime} \to K^{+} K^{-}$, the minimization process is analyzed from a theoretical point of view. The result indicates that for one parameter fit, only one data taking point in the vicinity of a resonance peak is sufficient to acquire the optimal precision. Numerical results are obtained by fitting simulated scan data. Besides the results related to the relative phase between strong and electromagnetic amplitudes, the method is extended to analyze the fits of other resonant parameters, such as the mass and the total decay width of $\psi^{\prime}$.Comment: 13 pages, 7 figure

A Microscopic View on the Mott transition in Chromium-doped V2O3

V2O3 is the prototype system for the Mott transition, one of the most fundamental phenomena of electronic correlation. Temperature, doping or pressure induce a metal to insulator transition (MIT) between a paramagnetic metal (PM) and a paramagnetic insulator (PI). This or related MITs have a high technological potential, among others for intelligent windows and field effect transistors. However the spatial scale on which such transitions develop is not known in spite of their importance for research and applications. Here we unveil for the first time the MIT in Cr-doped V2O3 with submicron lateral resolution: with decreasing temperature, microscopic domains become metallic and coexist with an insulating background. This explains why the associated PM phase is actually a poor metal. The phase separation can be associated with a thermodynamic instability near the transition. This instability is reduced by pressure which drives a genuine Mott transition to an eventually homogeneous metallic state.Comment: Paper plus supplementary materia

PPFL: privacy-preserving federated learning with trusted execution environments

We propose and implement a Privacy-preserving Federated Learning (PPFL) framework for mobile systems to limit privacy leakages in federated learning. Leveraging the widespread presence of Trusted Execution Environments (TEEs) in high-end and mobile devices, we utilize TEEs on clients for local training, and on servers for secure aggregation, so that model/gradient updates are hidden from adversaries. Challenged by the limited memory size of current TEEs, we leverage greedy layer-wise training to train each model's layer inside the trusted area until its convergence. The performance evaluation of our implementation shows that PPFL can significantly improve privacy while incurring small system overheads at the client-side. In particular, PPFL can successfully defend the trained model against data reconstruction, property inference, and membership inference attacks. Furthermore, it can achieve comparable model utility with fewer communication rounds (0.54x) and a similar amount of network traffic (1.002x) compared to the standard federated learning of a complete model. This is achieved while only introducing up to ~15% CPU time, ~18% memory usage, and ~21% energy consumption overhead in PPFL's client-side

Multicomponent fractional quantum Hall effect in graphene

We report observation of the fractional quantum Hall effect (FQHE) in high mobility multi-terminal graphene devices, fabricated on a single crystal boron nitride substrate. We observe an unexpected hierarchy in the emergent FQHE states that may be explained by strongly interacting composite Fermions with full SU(4) symmetric underlying degrees of freedom. The FQHE gaps are measured from temperature dependent transport to be up 10 times larger than in any other semiconductor system. The remarkable strength and unusual hierarcy of the FQHE described here provides a unique opportunity to probe correlated behavior in the presence of expanded quantum degrees of freedom.Comment: 5 pages, 3 figure