Diverse Temporal Properties of GRB Afterglow

The detection of delayed X-ray, optical and radio emission, "afterglow", associated with $\gamma$-ray bursts (GRBs) is consistent with fireball models, where the emission are produced by relativistic expanding blast wave, driven by expanding fireball at cosmogical distances. The emission mechanisms of GRB afterglow have been discussed by many authors and synchrotron radiation is believed to be the main mechanism. The observations show that the optical light curves of two observed gamma-ray bursts, GRB970228 and GRB GRB970508, can be described by a simple power law, which seems to support the synchrotron radiation explanation. However, here we shall show that under some circumstances, the inverse Compton scattering (ICS) may play an important role in emission spectrum and this may influence the temporal properties of GRB afterglow. We expect that the light curves of GRB afterglow may consist of multi-components, which depends on the fireball parameters.Comment: Latex, no figures, minor correctio

Adjusted Empirical Likelihood for Long-memory Time Series Models

Empirical likelihood method has been applied to short-memory time series models by Monti (1997) through the Whittle's estimation method. Yau (2012) extended this idea to long-memory time series models. Asymptotic distributions of the empirical likelihood ratio statistic for short and long-memory time series have been derived to construct confidence regions for the corresponding model parameters. However, computing profile empirical likelihood function involving constrained maximization does not always have a solution which leads to several drawbacks. In this paper, we propose an adjusted empirical likelihood procedure to modify the one proposed by Yau (2012) for autoregressive fractionally integrated moving average (ARFIMA) model. It guarantees the existence of a solution to the required maximization problem as well as maintains same asymptotic properties obtained by Yau (2012). Simulations have been carried out to illustrate that the adjusted empirical likelihood method for different long-time series models provides better confidence regions and coverage probabilities than the unadjusted ones, especially for small sample sizes

Towards Identification of Relevant Variables in the observed Aerosol Optical Depth Bias between MODIS and AERONET observations

Measurements made by satellite remote sensing, Moderate Resolution Imaging Spectroradiometer (MODIS), and globally distributed Aerosol Robotic Network (AERONET) are compared. Comparison of the two datasets measurements for aerosol optical depth values show that there are biases between the two data products. In this paper, we present a general framework towards identifying relevant set of variables responsible for the observed bias. We present a general framework to identify the possible factors influencing the bias, which might be associated with the measurement conditions such as the solar and sensor zenith angles, the solar and sensor azimuth, scattering angles, and surface reflectivity at the various measured wavelengths, etc. Specifically, we performed analysis for remote sensing Aqua-Land data set, and used machine learning technique, neural network in this case, to perform multivariate regression between the ground-truth and the training data sets. Finally, we used mutual information between the observed and the predicted values as the measure of similarity to identify the most relevant set of variables. The search is brute force method as we have to consider all possible combinations. The computations involves a huge number crunching exercise, and we implemented it by writing a job-parallel program

Is GRO J1744-28 a Strange Star?

The unusal hard x-ray burster GRO J1744-28 recently discovered by the Compton Gamma-ray Observatory (GRO) can be modeled as a strange star with a dipolar magnetic field $\le 10^{11}$Gauss. When the accreted mass of the star exceeds some critical mass, its crust may break, resulting in conversion of the accreted matter into strange matter and release of energy. Subsequently, a fireball may form and expand relativistically outward. The expanding fireball may interact with the surrounding interstellar medium, causing its kinetic energy to be radiated in shock waves, producing a burst of x-ray radiation. The burst energy, duration, interval and spectrum derived from such a model are consistent with the observations of GRO J1744-28.Comment: Latex, has been published in SCIENCE, Vol. 280, 40

Crossing of the Phantom Divided Barrier with Lorentz Invariance Violating Fields

We study possible crossing of the phantom divided barrier in a Lorentz invariance violating dark energy model. Lorentz invariance violation which is achieved by introducing a vector field in the action, incorporates directly in the dynamics of the scalar field and equation of state. This interesting feature allows us to study phantom divided barrier crossing in the context of Lorentz invariance violation. We show that for suitable choice of parameter space, equation of state can cross phantom divided barrier just by one scalar field and Lorentz violating vector field controls this crossing.Comment: 14 pages, 4 figures, Revised and References added, Accepted for Publication in Europhysics Letter

Modelling Electron Spin Accumulation in a Metallic Nanoparticle

A model describing spin-polarized current via discrete energy levels of a metallic nanoparticle, which has strongly asymmetric tunnel contacts to two ferromagnetic leads, is presented. In absence of spin-relaxation, the model leads to a spin-accumulation in the nanoparticle, a difference ($\Delta\mu$) between the chemical potentials of spin-up and spin-down electrons, proportional to the current and the Julliere's tunnel magnetoresistance. Taking into account an energy dependent spin-relaxation rate $\Omega (\omega)$, $\Delta\mu$ as a function of bias voltage ($V$) exhibits a crossover from linear to a much weaker dependence, when $|e|\Omega (\Delta\mu)$ equals the spin-polarized current through the nanoparticle. Assuming that the spin-relaxation takes place via electron-phonon emission and Elliot-Yafet mechanism, the model leads to a crossover from linear to $V^{1/5}$ dependence. The crossover explains recent measurements of the saturation of the spin-polarized current with $V$ in Aluminum nanoparticles, and leads to the spin-relaxation rate of $\approx 1.6 MHz$ in an Aluminum nanoparticle of diameter $6nm$, for a transition with an energy difference of one level spacing.Comment: 37 pages, 7 figure

VA-index: Quantifying assortativity patterns in networks with multidimensional nodal attributes

Network connections have been shown to be correlated with structural or external attributes of the network vertices in a variety of cases. Given the prevalence of this phenomenon network scientists have developed metrics to quantify its extent. In particular, the assortativity coefficient is used to capture the level of correlation between a single-dimensional attribute (categorical or scalar) of the network nodes and the observed connections, i.e., the edges. Nevertheless, in many cases a multi-dimensional, i.e., vector feature of the nodes is of interest. Similar attributes can describe complex behavioral patterns (e.g., mobility) of the network entities. To date little attention has been given to this setting and there has not been a general and formal treatment of this problem. In this study we develop a metric, the vector assortativity index (VA-index for short), based on network randomization and (empirical) statistical hypothesis testing that is able to quantify the assortativity patterns of a network with respect to a vector attribute. Our extensive experimental results on synthetic network data show that the VA-index outperforms a baseline extension of the assortativity coefficient, which has been used in the literature to cope with similar cases. Furthermore, the VAindex can be calibrated (in terms of parameters) fairly easy, while its benefits increase with the (co-)variance of the vector elements, where the baseline systematically over(under)estimate the true mixing patterns of the network

Temperature dependent electrical resistivity of a single strand of ferromagnetic single crystalline nanowire

We have measured the electrical resistivity of a single strand of a ferromagnetic Ni nanowire of diameter 55 nm using a 4-probe method in the temperature range 3 K-300 K. The wire used is chemically pure and is a high quality oriented single crystalline sample in which the temperature independent residual resistivity is determined predominantly by surface scattering. Precise evaluation of the temperature dependent resistivity ($\rho$) allowed us to identify quantitatively the electron-phonon contribution (characterized by a Debye temperature $\theta_R$) as well as the spin-wave contribution which is significantly suppressed upon size reduction

Oscillatory Spin Polarization and Magneto-Optic Kerr Effect in Fe3O4 Thin Films on GaAs(001)

The spin dependent properties of epitaxial Fe3O4 thin films on GaAs(001) are studied by the ferromagnetic proximity polarization (FPP) effect and magneto-optic Kerr effect (MOKE). Both FPP and MOKE show oscillations with respect to Fe3O4 film thickness, and the oscillations are large enough to induce repeated sign reversals. We attribute the oscillatory behavior to spin-polarized quantum well states forming in the Fe3O4 film. Quantum confinement of the t2g states near the Fermi level provides an explanation for the similar thickness dependences of the FPP and MOKE oscillations.Comment: to appear in Phys. Rev. Let