Controlling Metamaterial Resonances with Light

We investigate the use of coherent optical fields as a means of dynamically controlling the resonant behaviour of a variety of composite metamaterials, wherein the metamaterial structures are embedded in a dispersive dielectric medium. Control and switching is implemented by coherently driving the resonant permittivity of the embedding medium by applied optical radiation. The effect of embedding Split ring resonators (SRR) in a frequency- dispersive medium with Lorentz-like dispersion or with dispersion engineered by electromagnetic induced transparency (EIT), is manifested in the splitting of the negative permeability band, the modified (frequency-dependent) filling fractions and dissipation factors. The modified material parameters are strongly linked to the resonant frequencies of the medium, while for an embedding medium exhibiting EIT, also to the strength and detuning of the control field. The robustness of control against the deleterious influence of dissipation associated with the metallic structures as well as the inhomogeneous broadening due to structural imperfections is demonstrated. Studies on plasmonic metamaterials that consist of metallic nanorods arranged in loops and exhibit a collective magnetic response at optical frequencies are presented. Control and switching in this class of plasmonic nanorod metamaterials is shown to be possible, for example, by embedding these arrays in a Raman active liquid like CS$_2$ and utilizing the Inverse Raman Effect.Comment: 9 pages, 9 figure

Frequency Domain Simulations of Charge-Density-Wave Strains: Comparison with Electro-Optic Measurements

We have studied changes in charge-density-wave strain under application of square-wave currents of variable amplitude and frequency by numerically solving the phase-slip augmented diffusion model introduced by Adelman et al (Phys. Rev. B 53, 1833 (1996)). The frequency dependence of the strain, at each position and amplitude, was fit to a modified harmonic oscillator expression, and the position and current dependence of the fitting parameters determined. In particular, the delay time (1/resonant frequency) vanishes adjacent to the contact and grows with distance from the contact, and both the delay time and relaxation time decrease rapidly with increasing current (and phase-slip rate), as experimentally observed in the electro-optic response of blue bronze. We have also found that pinning the phase at the contacts causes more rapid changes in strain between the contacts than allowing the phase to flow outside the contacts.Comment: 12 pages, 4 figures, submitted to Phys. Rev.

Exploiting temporal information for 3D pose estimation

In this work, we address the problem of 3D human pose estimation from a sequence of 2D human poses. Although the recent success of deep networks has led many state-of-the-art methods for 3D pose estimation to train deep networks end-to-end to predict from images directly, the top-performing approaches have shown the effectiveness of dividing the task of 3D pose estimation into two steps: using a state-of-the-art 2D pose estimator to estimate the 2D pose from images and then mapping them into 3D space. They also showed that a low-dimensional representation like 2D locations of a set of joints can be discriminative enough to estimate 3D pose with high accuracy. However, estimation of 3D pose for individual frames leads to temporally incoherent estimates due to independent error in each frame causing jitter. Therefore, in this work we utilize the temporal information across a sequence of 2D joint locations to estimate a sequence of 3D poses. We designed a sequence-to-sequence network composed of layer-normalized LSTM units with shortcut connections connecting the input to the output on the decoder side and imposed temporal smoothness constraint during training. We found that the knowledge of temporal consistency improves the best reported result on Human3.6M dataset by approximately $12.2\%$ and helps our network to recover temporally consistent 3D poses over a sequence of images even when the 2D pose detector fails

On the Exponentials of Some Structured Matrices

In this note explicit algorithms for calculating the exponentials of important structured 4 x 4 matrices are provided. These lead to closed form formulae for these exponentials. The techniques rely on one particular Clifford Algebra isomorphism and basic Lie theory. When used in conjunction with structure preserving similarities, such as Givens rotations, these techniques extend to dimensions bigger than four.Comment: 19 page

Plasmon polaritons in photonic superlattices containing a left-handed material

We analyze one-dimensional photonic superlattices which alternate layers of air and a left-handed material. We assume Drude-type dispersive responses for the dielectric permittivity and magnetic permeability of the left-handed material. Maxwell's equations and the transfer-matrix technique are used to derive the dispersion relation for the propagation of obliquely incident optical fields. The photonic dispersion indicates that the growth-direction component of the electric (or magnetic) field leads to the propagation of electric (or magnetic) plasmon polaritons, for either TE or TM configurations. Furthermore, we show that if the plasma frequency is chosen within the photonic $=0$ zeroth-order bandgap, the coupling of light with plasmons weakens considerably. As light propagation is forbidden in that particular frequency region, the plasmon-polariton mode reduces to a pure plasmon mode.Comment: 4 pages, 4 figure

GeoNEX: A Cloud Gateway for Near Real-time Processing of Geostationary Satellite Products

The emergence of a new generation of geostationary satellite sensors provides land andatmosphere monitoring capabilities similar to MODIS and VIIRS with far greater temporal resolution (5-15 minutes). However, processing such large volume, highly dynamic datasets requires computing capabilities that (1) better support data access and knowledge discovery for scientists; (2) provide resources to enable real-time processing for emergency response (wildfire, smoke, dust, etc.); and (3) provide reliable and scalable services for the broader user community. This paper presents an implementation of GeoNEX (Geostationary NASA-NOAA Earth Exchange) services that integrate scientific algorithms with Amazon Web Services (AWS) to provide near realtime monitoring (~5 minute latency) capability in a hybrid cloud-computing environment. It offers a user-friendly, manageable and extendable interface and benefits from the scalability provided by Amazon Web Services. Four use cases are presented to illustrate how to (1) search and access geostationary data; (2) configure computing infrastructure to enable near real-time processing; (3) disseminate and utilize research results, visualizations, and animations to concurrent users; and (4) use a Jupyter Notebook-like interface for data exploration and rapid prototyping. As an example of (3), the Wildfire Automated Biomass Burning Algorithm (WF_ABBA) was implemented on GOES-16 and -17 data to produce an active fire map every 5 minutes over the conterminous US. Details of the implementation strategies, architectures, and challenges of the use cases are discussed

Estimation and Testing in Type I Generalized Half Logistic Distribution

A generalization of the half logistic distribution is developed through exponentiation of its cumulative distribution function and termed the Type I Generalized Half Logistic Distribution (GHLD). GHLD’s distributional characteristics and parameter estimation using maximum likelihood and modified maximum likelihood methods are presented with comparisons. Comparison of Type I GHLD and the exponential distribution is conducted via likelihood ratio criterion