394 research outputs found
Particle simulations in magnetospheric plasmas
In view of the recent remarkable advancement of computer technology and simulation software, simulation studies are one of the most powerful academic tools for establishment of quantitative space physics and modelling of our space environment. The complex nature encountered in space plasma physics has motivated considerable development in computer simulations, which have played an essential role in the development of space plasma theory. This report describes research undertaken to understand physical processes involved in plasma waves observed in the magnetospheric plasmas, and associated nonlinear phenomena such as heating, diffusion, and acceleration of particles due to excited waves. The research explains and clarifies the observational data both qualitatively and quantitatively
GRMHD/RMHD Simulations and Stability of Magnetized Spine-Sheath Relativistic Jets
A new general relativistic magnetohydrodynamics (GRMHD) code ``RAISHIN'' used
to simulate jet generation by rotating and non-rotating black holes with a
geometrically thin Keplarian accretion disk finds that the jet develops a
spine-sheath structure in the rotating black hole case. Spine-sheath structure
and strong magnetic fields significantly modify the Kelvin-Helmholtz (KH)
velocity shear driven instability. The RAISHIN code has been used in its
relativistic magnetohydrodynamic (RMHD) configuration to study the effects of
strong magnetic fields and weakly relativistic sheath motion, c/2, on the KH
instability associated with a relativistic, Lorentz factor equal 2.5, jet
spine-sheath interaction. In the simulations sound speeds up to c/1.7 and
Alfven wave speeds up to 0.56 c are considered. Numerical simulation results
are compared to theoretical predictions from a new normal mode analysis of the
RMHD equations. Increased stability of a weakly magnetized system resulting
from c/2 sheath speeds and stabilization of a strongly magnetized system
resulting from c/2 sheath speeds is found.Comment: 5 pages, 5 figures, accepted for publication in Astrophysics and
Space Scienc
Two-point correlation function of density perturbations in a large void universe
We study the two-point correlation function of density perturbations in a
spherically symmetric void universe model which does not employ the Copernican
principle. First we solve perturbation equations in the inhomogeneous universe
model and obtain density fluctuations by using a method of non-linear
perturbation theory which was adopted in our previous paper. From the obtained
solutions, we calculate the two-point correlation function and show that it has
a local anisotropy at the off-center position differently from those in
homogeneous and isotropic universes. This anisotropy is caused by the tidal
force in the off-center region of the spherical void. Since no tidal force
exists in homogeneous and isotropic universes, we may test the inhomogeneous
universe by observing statistical distortion of the two-point galaxy
correlation function.Comment: 16 pages, 3 figure
Non-relativistic perpendicular shocks modeling young supernova remnants: nonstationary dynamics and particle acceleration at forward and reverse shocks
For parameters that are applicable to the conditions at young supernova
remnants, we present results of 2D3V particle-in-cell simulations of a
non-relativistic plasma shock with a large-scale perpendicular magnetic field
inclined at 45-deg angle to the simulation plane to approximate 3D physics. We
developed an improved clean setup that uses the collision of two plasma slabs
with different density and velocity, leading to the development of two
distinctive shocks and a contact discontinuity. The shock formation is mediated
by Weibel-type filamentation instabilities that generate magnetic turbulence.
Cyclic reformation is observed in both shocks with similar period, for which we
note global variations on account of shock rippling and local variations
arising from turbulent current filaments. The shock rippling occurs on spatial
and temporal scales given by gyro-motions of shock-reflected ions. The drift
motion of electrons and ions is not a gradient drift, but commensurates with E
x B drift. We observe a stable suprathermal tail in the ion spectra, but no
electron acceleration because the amplitude of Buneman modes in the shock foot
is insufficient for trapping relativistic electrons. We see no evidence of
turbulent reconnection. A comparison with other 2D simulation results suggests
that the plasma beta and the ion-to-electron mass ratio are not decisive for
efficient electron acceleration, but pre-acceleration efficacy might be reduced
with respect to the 2D results once three-dimensional effects are fully
accounted for. Other microphysical factors may also be at play to limit the
amplitude of Buneman waves or prevent return of electrons to the foot region.Comment: Astrophysical Journal, in press, some figures with low resolutio
CRNPRED: highly accurate prediction of one-dimensional protein structures by large-scale critical random networks
BACKGROUND: One-dimensional protein structures such as secondary structures or contact numbers are useful for three-dimensional structure prediction and helpful for intuitive understanding of the sequence-structure relationship. Accurate prediction methods will serve as a basis for these and other purposes. RESULTS: We implemented a program CRNPRED which predicts secondary structures, contact numbers and residue-wise contact orders. This program is based on a novel machine learning scheme called critical random networks. Unlike most conventional one-dimensional structure prediction methods which are based on local windows of an amino acid sequence, CRNPRED takes into account the whole sequence. CRNPRED achieves, on average per chain, Q(3 )= 81% for secondary structure prediction, and correlation coefficients of 0.75 and 0.61 for contact number and residue-wise contact order predictions, respectively. CONCLUSION: CRNPRED will be a useful tool for computational as well as experimental biologists who need accurate one-dimensional protein structure predictions
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