32,365 research outputs found
A Morphological Approach to the Pulsed Emission from Soft Gamma Repeaters
We present a geometrical methodology to interpret the periodical light curves
of Soft Gamma Repeaters based on the magnetar model and the numerical
arithmetic of the three-dimensional magnetosphere model for the young pulsars.
The hot plasma released by the star quake is trapped in the magnetosphere and
photons are emitted tangent to the local magnetic field lines. The variety of
radiation morphologies in the burst tails and the persistent stages could be
well explained by the trapped fireballs on different sites inside the closed
field lines. Furthermore, our numerical results suggests that the pulse profile
evolution of SGR 1806-20 during the 27 December 2004 giant flare is due to a
lateral drift of the emitting region in the magnetosphere.Comment: 7 figures, accepted by Ap
BDGS: A Scalable Big Data Generator Suite in Big Data Benchmarking
Data generation is a key issue in big data benchmarking that aims to generate
application-specific data sets to meet the 4V requirements of big data.
Specifically, big data generators need to generate scalable data (Volume) of
different types (Variety) under controllable generation rates (Velocity) while
keeping the important characteristics of raw data (Veracity). This gives rise
to various new challenges about how we design generators efficiently and
successfully. To date, most existing techniques can only generate limited types
of data and support specific big data systems such as Hadoop. Hence we develop
a tool, called Big Data Generator Suite (BDGS), to efficiently generate
scalable big data while employing data models derived from real data to
preserve data veracity. The effectiveness of BDGS is demonstrated by developing
six data generators covering three representative data types (structured,
semi-structured and unstructured) and three data sources (text, graph, and
table data)
Interface Width and Bulk Stability: requirements for the simulation of Deeply Quenched Liquid-Gas Systems
Simulations of liquid-gas systems with extended interfaces are observed to
fail to give accurate results for two reasons: the interface can get ``stuck''
on the lattice or a density overshoot develops around the interface. In the
first case the bulk densities can take a range of values, dependent on the
initial conditions. In the second case inaccurate bulk densities are found. In
this communication we derive the minimum interface width required for the
accurate simulation of liquid gas systems with a diffuse interface. We
demonstrate this criterion for lattice Boltzmann simulations of a van der Waals
gas. When combining this criterion with predictions for the bulk stability we
can predict the parameter range that leads to stable and accurate simulation
results. This allows us to identify parameter ranges leading to high density
ratios of over 1000. This is despite the fact that lattice Boltzmann
simulations of liquid-gas systems were believed to be restricted to modest
density ratios of less than 20.Comment: 5 pages, 3 figure
Fast Monte Carlo Simulation for Patient-specific CT/CBCT Imaging Dose Calculation
Recently, X-ray imaging dose from computed tomography (CT) or cone beam CT
(CBCT) scans has become a serious concern. Patient-specific imaging dose
calculation has been proposed for the purpose of dose management. While Monte
Carlo (MC) dose calculation can be quite accurate for this purpose, it suffers
from low computational efficiency. In response to this problem, we have
successfully developed a MC dose calculation package, gCTD, on GPU architecture
under the NVIDIA CUDA platform for fast and accurate estimation of the x-ray
imaging dose received by a patient during a CT or CBCT scan. Techniques have
been developed particularly for the GPU architecture to achieve high
computational efficiency. Dose calculations using CBCT scanning geometry in a
homogeneous water phantom and a heterogeneous Zubal head phantom have shown
good agreement between gCTD and EGSnrc, indicating the accuracy of our code. In
terms of improved efficiency, it is found that gCTD attains a speed-up of ~400
times in the homogeneous water phantom and ~76.6 times in the Zubal phantom
compared to EGSnrc. As for absolute computation time, imaging dose calculation
for the Zubal phantom can be accomplished in ~17 sec with the average relative
standard deviation of 0.4%. Though our gCTD code has been developed and tested
in the context of CBCT scans, with simple modification of geometry it can be
used for assessing imaging dose in CT scans as well.Comment: 18 pages, 7 figures, and 1 tabl
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