72,847 research outputs found
A simulation method for determining the optical response of highly complex photonic structures of biological origin
We present a method based on a time domain simulation of wave propagation
that allows studying the optical response of a broad range of dielectric
photonic structures. This method is particularly suitable for dealing with
complex biological structures. One of the main features of the proposed
approach is the simple and intuitive way of defining the setup and the photonic
structure to be simulated, which can be done by feeding the simulation with a
digital image of the structure. We also develop a set of techniques to process
the behavior of the evolving waves within the simulation. These techniques
include a direction filter, that permits decoupling of waves travelling
simultaneously in different directions, a dynamic differential absorber, to
cancel the waves reflected at the edges of the simulation space, a
multi-frequency excitation scheme based on a filter that allows decoupling
waves of different wavelengths travelling simultaneously, and a
near-to-far-field approach to evaluate the resulting wavefield outside the
simulation domain. We validate the code and, as an example, apply it to the
complex structure found in a microorganism called Diachea leucopoda, which
exhibits a multicolor iridescent appearance.Comment: 43 pages, 19 figure
A Novel Design Approach to X-Band Minkowski Reflectarray Antennas using the Full-Wave EM Simulation-based Complete Neural Model with a Hybrid GA-NM Algorithm
In this work, a novel multi-objective design optimization procedure is presented for the Minkowski Reflectarray RAs using a complete 3-D CST Microwave Studio MWS-based Multilayer Perceptron Neural Network MLP NN model including the substrate constant Δr with a hybrid Genetic GA and Nelder-Mead NM algorithm. The MLP NN model provides an accurate and fast model and establishes the reflection phase of a unit Minkowski RA element as a continuous function within the input domain including the substrate 1 †Δr †6; 0.5mm †h †3mm in the frequency between 8GHz †f †12GHz. This design procedure enables a designer to obtain not only the most optimum Minkowski RA design all throughout the X- band, at the same time the optimum Minkowski RAs on the selected substrates. Moreover a design of a fully optimized X-band 15Ă15 Minkowski RA antenna is given as a worked example with together the tolerance analysis and its performance is also compared with those of the optimized RAs on the selected traditional substrates. Finally it may be concluded that the presented robust and systematic multi-objective design procedure is conveniently applied to the Microstrip Reflectarray RAs constructed from the advanced patches
On the Inversion of High Energy Proton
Inversion of the K-fold stochastic autoconvolution integral equation is an
elementary nonlinear problem, yet there are no de facto methods to solve it
with finite statistics. To fix this problem, we introduce a novel inverse
algorithm based on a combination of minimization of relative entropy, the Fast
Fourier Transform and a recursive version of Efron's bootstrap. This gives us
power to obtain new perspectives on non-perturbative high energy QCD, such as
probing the ab initio principles underlying the approximately negative binomial
distributions of observed charged particle final state multiplicities, related
to multiparton interactions, the fluctuating structure and profile of proton
and diffraction. As a proof-of-concept, we apply the algorithm to ALICE
proton-proton charged particle multiplicity measurements done at different
center-of-mass energies and fiducial pseudorapidity intervals at the LHC,
available on HEPData. A strong double peak structure emerges from the
inversion, barely visible without it.Comment: 29 pages, 10 figures, v2: extended analysis (re-projection ratios,
2D
Robust equalization of multichannel acoustic systems
In most real-world acoustical scenarios, speech signals captured by distant microphones from a source are reverberated due to multipath propagation, and the reverberation may impair speech intelligibility. Speech dereverberation can be achieved
by equalizing the channels from the source to microphones. Equalization systems can
be computed using estimates of multichannel acoustic impulse responses. However,
the estimates obtained from system identification always include errors; the fact that
an equalization system is able to equalize the estimated multichannel acoustic system does not mean that it is able to equalize the true system. The objective of this
thesis is to propose and investigate robust equalization methods for multichannel
acoustic systems in the presence of system identification errors.
Equalization systems can be computed using the multiple-input/output inverse theorem or multichannel least-squares method. However, equalization systems
obtained from these methods are very sensitive to system identification errors. A
study of the multichannel least-squares method with respect to two classes of characteristic channel zeros is conducted. Accordingly, a relaxed multichannel least-
squares method is proposed. Channel shortening in connection with the multiple-
input/output inverse theorem and the relaxed multichannel least-squares method is
discussed.
Two algorithms taking into account the system identification errors are developed. Firstly, an optimally-stopped weighted conjugate gradient algorithm is
proposed. A conjugate gradient iterative method is employed to compute the equalization system. The iteration process is stopped optimally with respect to system identification errors. Secondly, a system-identification-error-robust equalization
method exploring the use of error models is presented, which incorporates system
identification error models in the weighted multichannel least-squares formulation
An efficient algorithm for two-dimensional radiative transfer in axisymmetric circumstellar envelopes and disks
We present an algorithm for two-dimensional radiative transfer in
axisymmetric, circumstellar media. The formal integration of the transfer
equation is performed by a generalization of the short characteristics (SC)
method to spherical coordinates. Accelerated Lambda Iteration (ALI) and Ng's
algorithm are used to converge towards a solution. By taking a logarithmically
spaced radial coordinate grid, the method has the natural capability of
treating problems that span several decades in radius, in the most extreme case
from the stellar radius up to parsec scale. Flux conservation is guaranteed in
spherical coordinates by a particular choice of discrete photon directions and
a special treatment of nearly-radially outward propagating radiation. The
algorithm works well from zero up to very high optical depth, and can be used
for a wide variety of transfer problems, including non-LTE line formation, dust
continuum transfer and high temperature processes such as compton scattering.
In this paper we focus on multiple scattering off dust grains and on non-LTE
transfer in molecular and atomic lines. Line transfer is treated according to
an ALI scheme for multi-level atoms/molecules, and includes both random and
systematic velocity fields. The algorithms are implemented in a multi-purpose
user-friendly radiative transfer program named RADICAL. We present two example
computations: one of dust scattering in the Egg Nebula, and one of non-LTE line
formation in rotational transitions of HCO in a flattened protostellar
collapsing cloud.Comment: 18 pages, 32 figure
A spectral deferred correction strategy for low Mach number reacting flows subject to electric fields
We propose an algorithm for low Mach number reacting flows subjected to
electric field that includes the chemical production and transport of charged
species. This work is an extension of a multi-implicit spectral deferred
correction (MISDC) algorithm designed to advance the conservation equations in
time at scales associated with advective transport. The fast and nontrivial
interactions of electrons with the electric field are treated implicitly using
a Jacobian-Free Newton Krylov approach for which a preconditioning strategy is
developed. Within the MISDC framework, this enables a close and stable coupling
of diffusion, reactions and dielectric relaxation terms with advective
transport and is shown to exhibit second-order convergence in space and time.
The algorithm is then applied to a series of steady and unsteady problems to
demonstrate its capability and stability. Although developed in a
one-dimensional case, the algorithmic ingredients are carefully designed to be
amenable to multidimensional applications
SamACO: variable sampling ant colony optimization algorithm for continuous optimization
An ant colony optimization (ACO) algorithm offers
algorithmic techniques for optimization by simulating the foraging behavior of a group of ants to perform incremental solution
constructions and to realize a pheromone laying-and-following
mechanism. Although ACO is first designed for solving discrete
(combinatorial) optimization problems, the ACO procedure is
also applicable to continuous optimization. This paper presents
a new way of extending ACO to solving continuous optimization
problems by focusing on continuous variable sampling as a key
to transforming ACO from discrete optimization to continuous
optimization. The proposed SamACO algorithm consists of three
major steps, i.e., the generation of candidate variable values for
selection, the antsâ solution construction, and the pheromone
update process. The distinct characteristics of SamACO are the
cooperation of a novel sampling method for discretizing the
continuous search space and an efficient incremental solution
construction method based on the sampled values. The performance
of SamACO is tested using continuous numerical functions
with unimodal and multimodal features. Compared with some
state-of-the-art algorithms, including traditional ant-based algorithms
and representative computational intelligence algorithms
for continuous optimization, the performance of SamACO is seen
competitive and promising
Basis Pursuit Receiver Function
Receiver functions (RFs) are derived by deconvolution of the horizontal (radial or transverse) component of ground motion from the vertical component, which segregates the PS phases. Many methods have been proposed to employ deconvolution in frequency as well as in time domain. These methods vary in their approaches to impose regularization that addresses the stability problem. Here, we present application of a new time-domain deconvolution technique called basis pursuit deconvolution (BPD) that has recently been applied to seismic exploration data. Unlike conventional deconvolution methods, the BPD uses an L1 norm constraint on model reflectivity to impose sparsity. In addition, it uses an overcomplete wedge dictionary based on a dipole reflectivity series to define model constraints, which can achieve higher resolution than that obtained by the traditional methods. We demonstrate successful application of BPD based RF estimation from synthetic data for a crustal model with a near-surface thin layer of thickness 5, 7, 10, and 15 km. The BPD can resolve these thin layers better with much improved signal-to-noise ratio than the conventional methods. Finally, we demonstrate application of the BPD receiver function (BPRF) method to a field dataset from Kutch, India, where near-surface sedimentary layers are known to be present. The BPRFs are able to resolve reflections from these layers very well.Jackson Chair funds at the Jackson School of Geosciences, University of Texas, AustinCouncil of Scientific and Industrial Research twelfth five year plan project at the Council of Scientific and Industrial Research National Geophysical Research Institute (CSIR-NGRI), HyderabadInstitute for Geophysic
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