25,748 research outputs found
A new class of -d topological superconductor with topological classification
The classification of topological states of matter depends on spatial
dimension and symmetry class. For non-interacting topological insulators and
superconductors the topological classification is obtained systematically and
nontrivial topological insulators are classified by either integer or .
The classification of interacting topological states of matter is much more
complicated and only special cases are understood. In this paper we study a new
class of topological superconductors in dimensions which has
time-reversal symmetry and a spin conservation symmetry. We
demonstrate that the superconductors in this class is classified by
when electron interaction is considered, while the
classification is without interaction.Comment: 5 pages main text and 3 pages appendix. 1 figur
A GPU-based finite-size pencil beam algorithm with 3D-density correction for radiotherapy dose calculation
Targeting at the development of an accurate and efficient dose calculation
engine for online adaptive radiotherapy, we have implemented a finite size
pencil beam (FSPB) algorithm with a 3D-density correction method on GPU. This
new GPU-based dose engine is built on our previously published ultrafast FSPB
computational framework [Gu et al. Phys. Med. Biol. 54 6287-97, 2009].
Dosimetric evaluations against Monte Carlo dose calculations are conducted on
10 IMRT treatment plans (5 head-and-neck cases and 5 lung cases). For all
cases, there is improvement with the 3D-density correction over the
conventional FSPB algorithm and for most cases the improvement is significant.
Regarding the efficiency, because of the appropriate arrangement of memory
access and the usage of GPU intrinsic functions, the dose calculation for an
IMRT plan can be accomplished well within 1 second (except for one case) with
this new GPU-based FSPB algorithm. Compared to the previous GPU-based FSPB
algorithm without 3D-density correction, this new algorithm, though slightly
sacrificing the computational efficiency (~5-15% lower), has significantly
improved the dose calculation accuracy, making it more suitable for online IMRT
replanning
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
Bipartite graph partitioning and data clustering
Many data types arising from data mining applications can be modeled as
bipartite graphs, examples include terms and documents in a text corpus,
customers and purchasing items in market basket analysis and reviewers and
movies in a movie recommender system. In this paper, we propose a new data
clustering method based on partitioning the underlying bipartite graph. The
partition is constructed by minimizing a normalized sum of edge weights between
unmatched pairs of vertices of the bipartite graph. We show that an approximate
solution to the minimization problem can be obtained by computing a partial
singular value decomposition (SVD) of the associated edge weight matrix of the
bipartite graph. We point out the connection of our clustering algorithm to
correspondence analysis used in multivariate analysis. We also briefly discuss
the issue of assigning data objects to multiple clusters. In the experimental
results, we apply our clustering algorithm to the problem of document
clustering to illustrate its effectiveness and efficiency.Comment: Proceedings of ACM CIKM 2001, the Tenth International Conference on
Information and Knowledge Management, 200
Delay-dependent robust stability of stochastic delay systems with Markovian switching
In recent years, stability of hybrid stochastic delay systems, one of the important issues in the study of stochastic systems, has received considerable attention. However, the existing results do not deal with the structure of the diffusion but estimate its upper bound, which induces conservatism. This paper studies delay-dependent robust stability of hybrid stochastic delay systems. A delay-dependent criterion for robust exponential stability of hybrid stochastic delay systems is presented in terms of linear matrix inequalities (LMIs), which exploits the structure of the diffusion. Numerical examples are given to verify the effectiveness and less conservativeness of the proposed method
Parallel field magnetoresistance in topological insulator thin films
We report that the finite thickness of three-dimensional topological
insulator (TI) thin films produces an observable magnetoresistance (MR) in
phase coherent transport in parallel magnetic fields. The MR data of Bi2Se3 and
(Bi,Sb)2Te3 thin films are compared with existing theoretical models of
parallel field magnetotransport. We conclude that the TI thin films bring
parallel field transport into a unique regime in which the coupling of surface
states to bulk and to opposite surfaces is indispensable for understanding the
observed MR. The {\beta} parameter extracted from parallel field MR can in
principle provide a figure of merit for searching TI compounds with more
insulating bulk than existing materials.Comment: 6 pages, 4 figure
Chemical dynamics of triacetylene formation and implications to the synthesis of polyynes in Titan's atmosphere
For the last four decades, the role of polyynes such as diacetylene (HCCCCH) and triacetylene (HCCCCCCH) in the chemical evolution of the atmosphere of Saturn's moon Titan has been a subject of vigorous research. These polyacetylenes are thought to serve as an UV radiation shield in planetary environments; thus, acting as prebiotic ozone, and are considered as important constituents of the visible haze layers on Titan. However, the underlying chemical processes that initiate the formation and control the growth of polyynes have been the least understood to date. Here, we present a combined experimental, theoretical, and modeling study on the synthesis of the polyyne triacetylene (HCCCCCCH) via the bimolecular gas phase reaction of the ethynyl radical (CCH) with diacetylene (HCCCCH). This elementary reaction is rapid, has no entrance barrier, and yields the triacetylene molecule via indirect scattering dynamics through complex formation in a single collision event. Photochemical models of Titan's atmosphere imply that triacetylene may serve as a building block to synthesize even more complex polyynes such as tetraacetylene (HCCCCCCCCH)
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