Fast simulation of phase-change processes in chalcogenide alloys using a Gillespie-type cellular automata approach

Copyright © 2008 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. The following article appeared in Journal of Applied Physics 104 (2008) and may be found at http://link.aip.org/link/?JAPIAU/104/084901/1A stochastic cellular automata simulator capable of spatiotemporal modeling of the crystallization and amorphization behavior of phase-change materials during the complex annealing cycles used in optical and electrical memory applications is presented. This is based on consideration of bulk and surface energies to generate rates of growth and decay of crystallites built up from “monomers” that may themselves be quite complex molecules. The approach uses a stochastic Gillespie-type time-stepping algorithm to deal with events that may occur on a very wide range of time scales. The simulations are performed at molecular length scale and using an approximation of local free energy changes that depend only on immediate neighbors. The approach is potentially capable of spanning the length scales between ab initio atomistic modeling methods, such as density functional theory, and bulk-scale methods, such the Johnshon–Mehl–Avrami–Kolmogorov formalism. As an example the model is used to predict the crystallization behavior in the chalcogenide Ge2Sb2Te5 alloy commonly used in phase-change memory devices. The simulations include annealing cycles with nontrivial spatial and temporal variations in temperature, with good agreement to experimental incubation times at low temperatures while modeling nontrivial crystal size distributions and melting dynamics at higher temperatures

A determination of H_0 with the CLASS gravitational lens B1608+656: II. Mass models and the Hubble constant from lensing

EDITED FROM PAPER: We present mass models of the four-image gravitational lens system B1608+656. A mass model for the lens galaxies has been determined that reproduces the image positions, two out of three flux-density ratios and the model time delays. Using the time delays determined by Fassnacht et al. (1999a), we find that the best isothermal mass model gives H_0=59^{+7}_{-6} km/s/Mpc for Omega_m=1 and Omega_l=0.0, or H_0=(65-63)^{+7}_{-6} km/s/Mpc for Omega_m=0.3 and Omega_l = 0.0-0.7 (95.4% statistical confidence). A systematic error of +/-15 km/s/Mpc is estimated. This cosmological determination of H_0 agrees well with determinations from three other gravitational lens systems (i.e. B0218+357, Q0957+561 and PKS1830-211), SNe Ia, the S-Z effect and local determinations. The current agreement on H_0 from four out of five gravitational lens systems (i) emphasizes the reliability of its determination from isolated gravitational lens systems and (ii) suggests that a close-to-isothermal mass profile can describe disk galaxies, ellipticals and central cluster ellipticals. The average of H_0 from B0218+357, Q0957+561, B1608+656 and PKS1830-211, gives H_0(GL)=69 +/-7 km/s/Mpc for a flat universe with Omega_m=1 or H_0(GL)=74 +/-8 km/s/Mpc for Omega_m=0.3 and Omega_l=0.0-0.7. When including PG1115+080, these values decrease to 64 +/-11 km/s/Mpc and 68 +/-13 km/s/Mpc (2-sigma errors), respectively.Comment: Accepted for publication in ApJ. 34 pages, 4 figure

PDS ‘To Go’? ‘Portability’ of Rights through Real-time Monitoring: the Centralised Online Real-time Electronic PDS in Chhattisgarh, India

Information and communications technology (ICT)-based reforms are increasingly being used to improve the delivery of public services. These reforms have taken the form of crowd-sourcing information (election monitoring), using ICTs to increase efficiency (e.g. computerised land registry systems), and connecting users to providers (e.g. mobile phone-based health services). These different approaches attempt to improve delivery through either (a) improving the quality of information, (b) reducing corruption or (c) making access more convenient and simple. The main question which the research reported here addressed was: through what processes, and under what conditions, do real-time monitoring technology-based reforms strengthen accountability and affect the delivery of public services? This was done by examining the Centralised Online Real-time Electronic (CORE) Public Distribution System (PDS) reforms introduced by the State Government of Chhattisgarh, India.UK Department for International Developmen

Growth and Characterization of MnBi2Te4 Magnetic Topological Insulator

We report successful growth of magnetic topological insulator (MTI) MnBi(2)Te(4)singlecrystalby solid state reaction route via self flux method. The phase formation of MnBi(2)Te(4)singlecrystalis strongly dependent on the heat treatment. MnBi(2)Te(4)is grown in various phases i. e., MnBi4Te7, MnBi6Te10 and MnTe as seen in powder X-ray diffraction (PXRD) of crushed resultant crystal. The Rietveld analysis shows some impurity lines along with the main phase MnBi2Te4. Low temperature (10K) magneto-resistance (MR) in applied magnetic field of up to 6 Tesla exhibited - ve MR below 0.5 Tesla and +ve for higher fields. The studied MnBi2Te4, MTI crystal could be a possible candidate for Quantum Anomalous Hall (QAH) effect. Here we are reporting a newly discovered magnetic topological insulator MnBi(2)Te(4)having non-trivial symmetry as well as strong Spin-Orbit Coupling forQAH effect

Further Investigation of the Time Delay, Magnification Ratios, and Variability in the Gravitational Lens 0218+357

High precision VLA flux density measurements for the lensed images of 0218+357 yield a time delay of 10.1(+1.5-1.6)days (95% confidence). This is consistent with independent measurements carried out at the same epoch (Biggs et al. 1999), lending confidence in the robustness of the time delay measurement. However, since both measurements make use of the same features in the light curves, it is possible that the effects of unmodelled processes, such as scintillation or microlensing, are biasing both time delay measurements in the same way. Our time delay estimates result in confidence intervals that are somewhat larger than those of Biggs et al., probably because we adopt a more general model of the source variability, allowing for constant and variable components. When considered in relation to the lens mass model of Biggs et al., our best-fit time delay implies a Hubble constant of H_o = 71(+17-23) km/s-Mpc for Omega_o=1 and lambda_o=0 (95% confidence; filled beam). This confidence interval for H_o does not reflect systematic error, which may be substantial, due to uncertainty in the position of the lens galaxy. We also measure the flux ratio of the variable components of 0218+357, a measurement of a small region that should more closely represent the true lens magnification ratio. We find ratios of 3.2(+0.3-0.4) (95% confidence; 8 GHz) and 4.3(+0.5-0.8) (15 GHz). Unlike the reported flux ratios on scales of 0.1", these ratios are not strongly significantly different. We investigate the significance of apparent differences in the variability properties of the two images of the background active galactic nucleus. We conclude that the differences are not significant, and that time series much longer than our 100-day time series will be required to investigate propagation effects in this way.Comment: 33 pages, 9 figures. Accepted for publication in ApJ. Light curve data may be found at http://space.mit.edu/RADIO/papers.htm

Effects of Dust on Gravitational Lensing by Spiral Galaxies

Gravitational lensing of an optical QSO by a spiral galaxy is often counteracted by dust obscuration, since the line-of-sight to the QSO passes close to the center of the galactic disk. The dust in the lens is likely to be correlated with neutral hydrogen, which in turn should leave a Lyman-alpha absorption signature on the QSO spectrum. We use the estimated dust-to-gas ratio of the Milky-Way galaxy as a mean and allow a spread in its values to calculate the effects of dust on lensing by low redshift spiral galaxies. Using a no-evolution model for spirals at z<1 we find (in Lambda=0 cosmologies) that the magnification bias due to lensing is stronger than dust obscuration for QSO samples with a magnitude limit B<16. The density parameter of neutral hydrogen, Omega_HI, is overestimated in such samples and is underestimated for fainter QSOs.Comment: 18 pages, 4 figures, ApJ, in pres

Slow Light Propagation in a Thin Optical Fiber via Electromagnetically Induced Transparency

We propose a novel configuration that utilizes electromagnetically induced transparency (EIT) to tailor a fiber mode propagating inside a thin optical fiber and coherently control its dispersion properties to drastically reduce the group velocity of the fiber mode. The key to this proposal is: the evanescent-like field of the thin fiber strongly couples with the surrounding active medium, so that the EIT condition is met by the medium. We show how the properties of the fiber mode is modified due to the EIT medium, both numerically and analytically. We demonstrate that the group velocity of the new modified fiber mode can be drastically reduced (approximately 44 m/sec) using the coherently prepared orthohydrogen doped in a matrix of parahydrogen crystal as the EIT medium.Comment: 10 pages in two column RevTex4, 6 Figure

Deep Learning Based Forecasting of Indian Summer Monsoon Rainfall

Accurate short range weather forecasting has significant implications for various sectors. Machine learning based approaches, e.g., deep learning, have gained popularity in this domain where the existing numerical weather prediction (NWP) models still have modest skill after a few days. Here we use a ConvLSTM network to develop a deep learning model for precipitation forecasting. The crux of the idea is to develop a forecasting model which involves convolution based feature selection and uses long term memory in the meteorological fields in conjunction with gradient based learning algorithm. Prior to using the input data, we explore various techniques to overcome dataset difficulties. We follow a strategic approach to deal with missing values and discuss the models fidelity to capture realistic precipitation. The model resolution used is (25 km). A comparison between 5 years of predicted data and corresponding observational records for 2 days lead time forecast show correlation coefficients of 0.67 and 0.42 for lead day 1 and 2 respectively. The patterns indicate higher correlation over the Western Ghats and Monsoon trough region (0.8 and 0.6 for lead day 1 and 2 respectively). Further, the model performance is evaluated based on skill scores, Mean Square Error, correlation coefficient and ROC curves. This study demonstrates that the adopted deep learning approach based only on a single precipitation variable, has a reasonable skill in the short range. Incorporating multivariable based deep learning has the potential to match or even better the short range precipitation forecasts based on the state of the art NWP models.Comment: 14 pages, 14 figures. The manuscript is under review with journal 'Transactions on Geoscience and Remote Sensing