A Laboratory Plasma Experiment for Studying Magnetic Dynamics of Accretion Discs and Jets

This work describes a laboratory plasma experiment and initial results which should give insight into the magnetic dynamics of accretion discs and jets. A high-speed multiple-frame CCD camera reveals images of the formation and helical instability of a collimated plasma, similar to MHD models of disc jets, and also plasma detachment associated with spheromak formation, which may have relevance to disc winds and flares. The plasmas are produced by a planar magnetized coaxial gun. The resulting magnetic topology is dependent on the details of magnetic helicity injection, namely the force-free state eigenvalue alpha_gun imposed by the coaxial gun.Comment: accepted for publication in MNRA

Study of magnetic helicity injection via plasma imaging using a high-speed digital camera

The evolution of a plasma generated by a novel planar coaxial gun is photographed using a state-of-the-art digital camera, which captures eight time-resolved images per discharge. This experiment is designed to study the fundamental physics of magnetic helicity injection, which is an important issue in fusion plasma confinement, as well as solar and astrophysical phenomena such as coronal mass ejections and accretion disk dynamics. The images presented in this paper are not only beautiful but provide a powerful way to understand the global dynamics of the plasma

White holes and eternal black holes

We investigate isolated white holes surrounded by vacuum, which correspond to the time reversal of eternal black holes that do not evaporate. We show that isolated white holes produce quasi- thermal Hawking radiation. The time reversal of this radiation, incident on a black hole precursor, constitutes a special preparation that will cause the black hole to become eternal.Comment: 5 pages, 2 figures, revtex; revised version to appear in Classical and Quantum Gravit

Assessment of assimilating SMOS soil moisture information into a distributed hydrologic model

The role that soil moisture plays in terms of modulating hydrologic processes including infiltration and runoff generation makes it an essential component to capture for hydrologic modeling. This work aims to leverage information gained from SMOS to improve surface soil moisture simulations in the Russian River Basin (California, U.S.A). The basin's complex terrain offers a rigorous testing ground for SMOS soil moisture products. Data from seven in situ observation sites are used to assess model performance after assimilating SMOS-based soil saturation ratios. For a comparison of "best case" scenarios, the in situ observations themselves are assimilated. Results show that SMOS assimilated simulations shows modest improvement at most in situ locations. Despite the observed decrease in model performance at some locations, overall performance of simulations assimilated with SMOS-based saturation ratios remains high. Findings suggest that even in a complex environment, useful information may be extracted from SMOS estimates for hydrologic modeling

Volume Stabilization and the Origin of the Inflaton Shift Symmetry in String Theory

The main problem of inflation in string theory is finding the models with a flat potential, consistent with stabilization of the volume of the compactified space. This can be achieved in the theories where the potential has (an approximate) shift symmetry in the inflaton direction. We will identify a class of models where the shift symmetry uniquely follows from the underlying mathematical structure of the theory. It is related to the symmetry properties of the corresponding coset space and the period matrix of special geometry, which shows how the gauge coupling depends on the volume and the position of the branes. In particular, for type IIB string theory on K3xT^2/Z with D3 or D7 moduli belonging to vector multiplets, the shift symmetry is a part of SO(2,2+n) symmetry of the coset space [SU(1,1)/ U(1)]x[SO(2,2+n)/(SO(2)x SO(2+n)]. The absence of a prepotential, specific for the stringy version of supergravity, plays a prominent role in this construction, which may provide a viable mechanism for the accelerated expansion and inflation in the early universe.Comment: 12 page

Coal desulfurization process

A method for chlorinolysis of coal is an organic solvent at a moderate temperautre and atmospheric pressure has been proven to be effective in removing sulfur, particularly the organic sulfur, from coal. Chlorine gas is bubbled through a slurry of moist coal in chlorinated solvent. The chlorinated coal is separated, hydrolyzed and the dechlorinated. Preliminary results of treating a high sulfutr (4.77%S) bituminous coal show that up to 70% organic sulfur, 90% hyritic sulfur and 76% total sulfur can be removed. The treated coal is dechlorinated by heating at 500 C. The presence of moisture helps to remove organic sulfur

Deep Neural Network Cloud-Type Classification (DeepCTC) model and its application in evaluating PERSIANN-CCS

Satellite remote sensing plays a pivotal role in characterizing hydrometeorological components including cloud types and their associated precipitation. The Cloud Profiling Radar (CPR) on the Polar Orbiting CloudSat satellite has provided a unique dataset to characterize cloud types. However, data from this nadir-looking radar offers limited capability for estimating precipitation because of the narrow satellite swath coverage and low temporal frequency. We use these high-quality observations to build a Deep Neural Network Cloud-Type Classification (DeepCTC) model to estimate cloud types from multispectral data from the Advanced Baseline Imager (ABI) onboard the GOES-16 platform. The DeepCTC model is trained and tested using coincident data from both CloudSat and ABI over the CONUS region. Evaluations of DeepCTC indicate that the model performs well for a variety of cloud types including Altostratus, Altocumulus, Cumulus, Nimbostratus, Deep Convective and High clouds. However, capturing low-level clouds remains a challenge for the model. Results from simulated GOES-16 ABI imageries of the Hurricane Harvey event show a large-scale perspective of the rapid and consistent cloud-type monitoring is possible using the DeepCTC model. Additionally, assessments using half-hourly Multi-Radar/Multi-Sensor (MRMS) precipitation rate data (for Hurricane Harvey as a case study) show the ability of DeepCTC in identifying rainy clouds, including Deep Convective and Nimbostratus and their precipitation potential. We also use DeepCTC to evaluate the performance of the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) product over different cloud types with respect to MRMS referenced at a half-hourly time scale for July 2018. Our analysis suggests that DeepCTC provides supplementary insights into the variability of cloud types to diagnose the weakness and strength of near real-time GEO-based precipitation retrievals. With additional training and testing, we believe DeepCTC has the potential to augment the widely used PERSIANN-CCS algorithm for estimating precipitation

Structure of bottle-brush brushes under good solvent conditions. A molecular dynamics study

We report a simulation study for bottle-brush polymers grafted on a rigid backbone. Using a standard coarse-grained bead-spring model extensive molecular dynamics simulations for such macromolecules under good solvent conditions are performed. We consider a broad range of parameters and present numerical results for the monomer density profile, density of the untethered ends of the grafted flexible backbones and the correlation function describing the range that neighboring grafted bottle-brushes are affected by the presence of the others due to the excluded volume interactions. The end beads of the flexible backbones of the grafted bottle-brushes do not access the region close to the rigid backbone due to the presence of the side chains of the grafted bottle-brush polymers, which stretch further the chains in the radial directions. Although a number of different correlation lengths exist as a result of the complex structure of these macromolecules, their properties can be tuned with high accuracy in good solvents. Moreover, qualitative differences with "typical" bottle-brushes are discussed. Our results provide a first approach to characterizing such complex macromolecules with a standard bead spring model.Comment: To appear in Journal of Physics Condensed Matter (2011