Methods for detection and characterization of signals in noisy data with the Hilbert-Huang Transform

The Hilbert-Huang Transform is a novel, adaptive approach to time series analysis that does not make assumptions about the data form. Its adaptive, local character allows the decomposition of non-stationary signals with hightime-frequency resolution but also renders it susceptible to degradation from noise. We show that complementing the HHT with techniques such as zero-phase filtering, kernel density estimation and Fourier analysis allows it to be used effectively to detect and characterize signals with low signal to noise ratio.Comment: submitted to PRD, 10 pages, 9 figures in colo

4π4\pi periodic Andreev bound states in a Dirac semimetal

Electrons in a Dirac semimetals possess linear dispersion in all three spatial dimensions, and form part of a developing platform of novel quantum materials. Bi$_{1-x}$Sb$_x$ supports a three-dimensional Dirac cone at the Sb-induced band inversion point. Nanoscale phase-sensitive junction technology is used to induce superconductivity in this Dirac semimetal. Radio frequency irradiation experiments reveal a significant contribution of 4$\pi$-periodic Andreev bound states to the supercurrent in Nb-Bi$_{0.97}$Sb$_{0.03}$-Nb Josephson junctions. The conditions for a substantial $4\pi$ contribution to the supercurrent are favourable because of the Dirac cone's topological protection against backscattering, providing very broad transmission resonances. The large g-factor of the Zeeman effect from a magnetic field applied in the plane of the junction, allows tuning of the Josephson junctions from 0 to $\pi$ regimes.Comment: Supplementary information is include

Low temperature dynamics of kinks on Ising interfaces

The anisotropic motion of an interface driven by its intrinsic curvature or by an external field is investigated in the context of the kinetic Ising model in both two and three dimensions. We derive in two dimensions (2d) a continuum evolution equation for the density of kinks by a time-dependent and nonlocal mapping to the asymmetric exclusion process. Whereas kinks execute random walks biased by the external field and pile up vertically on the physical 2d lattice, then execute hard-core biased random walks on a transformed 1d lattice. Their density obeys a nonlinear diffusion equation which can be transformed into the standard expression for the interface velocity v = M[(gamma + gamma'')kappa + H]$, where M, gamma + gamma'', and kappa are the interface mobility, stiffness, and curvature, respectively. In 3d, we obtain the velocity of a curved interface near the orientation from an analysis of the self-similar evolution of 2d shrinking terraces. We show that this velocity is consistent with the one predicted from the 3d tensorial generalization of the law for anisotropic curvature-driven motion. In this generalization, both the interface stiffness tensor and the curvature tensor are singular at the orientation. However, their product, which determines the interface velocity, is smooth. In addition, we illustrate how this kink-based kinetic description provides a useful framework for studying more complex situations by modeling the effect of immobile dilute impurities.Comment: 11 pages, 10 figure

Non-local signatures of the chiral magnetic effect in Dirac semimetal Bi0.97_{0.97}Sb0.03_{0.03}

The field of topological materials science has recently been focussing on three-dimensional Dirac semimetals, which exhibit robust Dirac phases in the bulk. However, the absence of characteristic surface states in accidental Dirac semimetals (DSM) makes it difficult to experimentally verify claims about the topological nature using commonly used surface-sensitive techniques. The chiral magnetic effect (CME), which originates from the Weyl nodes, causes an $\textbf{E}\cdot\textbf{B}$-dependent chiral charge polarization, which manifests itself as negative magnetoresistance. We exploit the extended lifetime of the chirally polarized charge and study the CME through both local and non-local measurements in Hall bar structures fabricated from single crystalline flakes of the DSM Bi$_{0.97}$Sb$_{0.03}$. From the non-local measurement results we find a chiral charge relaxation time which is over one order of magnitude larger than the Drude transport lifetime, underlining the topological nature of Bi$_{0.97}$Sb$_{0.03}$.Comment: 6 pages, 6 figures + 7 pages of supplemental materia

Sparsity based sub-wavelength imaging with partially incoherent light via quadratic compressed sensing

We demonstrate that sub-wavelength optical images borne on partially-spatially-incoherent light can be recovered, from their far-field or from the blurred image, given the prior knowledge that the image is sparse, and only that. The reconstruction method relies on the recently demonstrated sparsity-based sub-wavelength imaging. However, for partially-spatially-incoherent light, the relation between the measurements and the image is quadratic, yielding non-convex measurement equations that do not conform to previously used techniques. Consequently, we demonstrate new algorithmic methodology, referred to as quadratic compressed sensing, which can be applied to a range of other problems involving information recovery from partial correlation measurements, including when the correlation function has local dependencies. Specifically for microscopy, this method can be readily extended to white light microscopes with the additional knowledge of the light source spectrum.Comment: 16 page

Induced superconductivity in the two-dimensional topological insulator phase of cadmium arsenide

Hybrid structures between conventional, s-wave superconductors and two-dimensional topological insulators (2D TIs) are a promising route to topological superconductivity. Here, we investigate planar Josephson junctions fabricated from hybrid structures that use thin films of cadmium arsenide (Cd3As2) as the 2D TI material. Measurements of superconducting interference patterns in a perpendicular magnetic field are used to extract information about the spatial distribution of the supercurrent. We show that the interference patterns are distinctly different in junctions with and without mesa-isolation, respectively. In mesa-defined junctions, the bulk of the 2D TI appears to be almost completely shunted by supercurrent flowing along the edges, while the supercurrent is much more uniform across the junction when the Cd3As2 film extends beyond the device. We discuss the possible origins of the observed behaviors.Comment: Accepted for publication in APL Material

OmOm Diagnostic for Dilaton Dark Energy

$Om$ diagnostic can differentiate between different models of dark energy without the accurate current value of matter density. We apply this geometric diagnostic to dilaton dark energy(DDE) model and differentiate DDE model from LCDM. We also investigate the influence of coupled parameter $\alpha$ on the evolutive behavior of $Om$ with respect to redshift $z$. According to the numerical result of $Om$, we get the current value of equation of state $\omega_{\sigma0}$=-0.952 which fits the WMAP5+BAO+SN very well.Comment: 6 pages and 6 figures

Integrity, Confidentiality, and Equity: Using Inquiry-Based Labs to help students understand AI and Cybersecurity

Recent advances in Artificial Intelligence (AI) have brought society closer to the long-held dream of creating machines to help with both common and complex tasks and functions. From recommending movies to detecting disease in its earliest stages, AI has become an aspect of daily life many people accept without scrutiny. Despite its functionality and promise, AI has inherent security risks that users should understand and programmers must be trained to address. The ICE (integrity, confidentiality, and equity) cybersecurity labs developed by a team of cybersecurity researchers addresses these vulnerabilities to AI models through a series of hands-on, inquiry-based labs. Through experimenting with and manipulating data models, students can experience firsthand how adversarial samples and bias can degrade the integrity, confidentiality, and equity of deep learning neural networks, as well as implement security measures to mitigate these vulnerabilities. This article addresses the pedagogical approach underpinning the ICE labs, and discusses both sample activities and technological considerations for teachers who want to implement these labs with their students