35,707 research outputs found
Scattering in and Symmetric Multimode Waveguides: Generalized Conservation Laws and Spontaneous Symmetry Breaking beyond One Dimension
We extend the generalize conservation law of light propagating in a
one-dimensional -symmetric system, i.e., for the
transmittance and the reflectance from the left and right, to a
multimode waveguide with either or symmetry, in which
higher dimensional investigations are necessary. These conservation laws exist
not only in a matrix form for the transmission and reflection matrices; they
also exist in a scalar form for real-valued quantities by defining generalized
transmittance and reflectance. We then discuss, for the first time, how a
multimode -symmetric waveguide can be used to observe spontaneous
symmetry breaking of the scattering matrix, which typically requires tuning the
non-hermiticity of the system (i.e. the strength of gain and loss). Here the
advantage of using a multimode waveguide is the elimination of tuning any
system parameters: the transverse mode order plays the role of the symmetry
breaking parameter, and one observes the symmetry breaking by simply performing
scattering experiment in each waveguide channel at a single frequency and fixed
strength of gain and loss.Comment: 8 pages, 6 figure
Coherent transport on Apollonian networks and continuous-time quantum walks
We study the coherent exciton transport on Apollonian networks generated by
simple iterative rules. The coherent exciton dynamics is modeled by
continuous-time quantum walks and we calculate the transition probabilities
between two nodes of the networks. We find that the transport depends on the
initial nodes of the excitation. For networks less than the second generation
the coherent transport shows perfect revivals when the initial excitation
starts at the central node. For networks of higher generation, the transport
only shows partial revivals. Moreover, we find that the excitation is most
likely to be found at the initial nodes while the coherent transport to other
nodes has a very low probability. In the long time limit, the transition
probabilities show characteristic patterns with identical values of limiting
probabilities. Finally, the dynamics of quantum transport are compared with the
classical transport modeled by continuous-time random walks.Comment: 5 pages, 6 figues. Submitted to Phys. ReV.
SOS-convex Semi-algebraic Programs and its Applications to Robust Optimization: A Tractable Class of Nonsmooth Convex Optimization
In this paper, we introduce a new class of nonsmooth convex functions called
SOS-convex semialgebraic functions extending the recently proposed notion of
SOS-convex polynomials. This class of nonsmooth convex functions covers many
common nonsmooth functions arising in the applications such as the Euclidean
norm, the maximum eigenvalue function and the least squares functions with
-regularization or elastic net regularization used in statistics and
compressed sensing. We show that, under commonly used strict feasibility
conditions, the optimal value and an optimal solution of SOS-convex
semi-algebraic programs can be found by solving a single semi-definite
programming problem (SDP). We achieve the results by using tools from
semi-algebraic geometry, convex-concave minimax theorem and a recently
established Jensen inequality type result for SOS-convex polynomials. As an
application, we outline how the derived results can be applied to show that
robust SOS-convex optimization problems under restricted spectrahedron data
uncertainty enjoy exact SDP relaxations. This extends the existing exact SDP
relaxation result for restricted ellipsoidal data uncertainty and answers the
open questions left in [Optimization Letters 9, 1-18(2015)] on how to recover a
robust solution from the semi-definite programming relaxation in this broader
setting
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Effect factors of part-load performance for various Organic Rankine cycles using in engine waste heat recovery
The Organic Rankine Cycle (ORC) is regarded as one of the most promising waste heat recovery technologies for electricity generation engines. Since the engine usually operates under different working conditions, it is important to research the part-load performance of the ORC. In order to reveal the effect factors of part-load performance, four different forms of ORCs are compared in the study with dynamic math models established in SIMULINK. They are the ORC applying low temperature working fluid R245fa with a medium heat transfer cycle, the ORCs with high temperature working fluid toluene heated directly by exhaust condensing at low pressure and high pressure, and the double-stage ORC. It is regarded that the more slowly the system output power decreases, the better part-load performance it has. Based on a comparison among the four systems, the effects of evaporating pressure, condensing condition, working fluid, and system structure on part-load performance are revealed in the work. Further, it is found that the system which best matches with the heat source not only performs well under the design conditions, but also has excellent part-load performance
Global behavior of cosmological dynamics with interacting Veneziano ghost
In this paper, we shall study the dynamical behavior of the universe
accelerated by the so called Veneziano ghost dark energy component locally and
globally by using the linearization and nullcline method developed in this
paper. The energy density is generalized to be proportional to the Hawking
temperature defined on the trapping horizon instead of Hubble horizon of the
Friedmann-Robertson-Walker (FRW) universe. We also give a prediction of the
fate of the universe and present the bifurcation phenomenon of the dynamical
system of the universe. It seems that the universe could be dominated by dark
energy at present in some region of the parameter space.Comment: 8 pages, 7 figures, accepted for publication in JHE
Insulator-metal transition shift related to magnetic polarons in La0.67-xYxCa0.33MnO3
The magnetic transport properties have been measured for La0.67-xYxCa0.33MnO3
(0 <= x <= 0.14) system. It was found that the transition temperature Tp almost
linearly moves to higher temperature as H increases. Electron spin resonance
confirms that above Tp, there exist ferromagnetic clusters. From the magnetic
polaron point of view, the shift of Tp vs. H was understood, and it was
estimated that the size of the magnetic polaron is of 9.7~15.4 angstrom which
is consistent with the magnetic correlation length revealed by the small-angle
neutron-scattering technique. The transport properties at temperatures higher
than Tp conform to the variable-range hopping mechanism.Comment: 22 pages, 6 figures, pdf, to be published in Euro. Phys. J.
The Casimir force of Quantum Spring in the (D+1)-dimensional spacetime
The Casimir effect for a massless scalar field on the helix boundary
condition which is named as quantum spring is studied in our recent
paper\cite{Feng}. In this paper, the Casimir effect of the quantum spring is
investigated in -dimensional spacetime for the massless and massive
scalar fields by using the zeta function techniques. We obtain the exact
results of the Casimir energy and Casimir force for any , which indicate a
symmetry of the two space dimensions. The Casimir energy and Casimir
force have different expressions for odd and even dimensional space in the
massless case but in both cases the force is attractive. In the case of
odd-dimensional space, the Casimir energy density can be expressed by the
Bernoulli numbers, while in the even case it can be expressed by the
-function. And we also show that the Casimir force has a maximum value
which depends on the spacetime dimensions. In particular, for a massive scalar
field, we found that the Casimir force varies as the mass of the field changes.Comment: 9 pages, 5 figures, v2, massive case added, refs. adde
Brain MRI Super Resolution Using 3D Deep Densely Connected Neural Networks
Magnetic resonance image (MRI) in high spatial resolution provides detailed
anatomical information and is often necessary for accurate quantitative
analysis. However, high spatial resolution typically comes at the expense of
longer scan time, less spatial coverage, and lower signal to noise ratio (SNR).
Single Image Super-Resolution (SISR), a technique aimed to restore
high-resolution (HR) details from one single low-resolution (LR) input image,
has been improved dramatically by recent breakthroughs in deep learning. In
this paper, we introduce a new neural network architecture, 3D Densely
Connected Super-Resolution Networks (DCSRN) to restore HR features of
structural brain MR images. Through experiments on a dataset with 1,113
subjects, we demonstrate that our network outperforms bicubic interpolation as
well as other deep learning methods in restoring 4x resolution-reduced images.Comment: Accepted by ISBI'1
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