922 research outputs found
Enhanced statistical stability in coherent interferometric imaging
http://iopscience.iop.org/0266-5611/International audienc
Detection and imaging in strongly backscattering randomly layered media
Abstract. Echoes from small reflectors buried in heavy clutter are weak and difficult to distinguish from the medium backscatter. Detection and imaging with sensor arrays in such media requires filtering out the unwanted backscatter and enhancing the echoes from the reflectors that we wish to locate. We consider a filtering and detection approach based on the singular value decomposition of the local cosine transform of the array response matrix. The algorithm is general and can be used for detection and imaging in heavy clutter, but its analysis depends on the model of the cluttered medium. This paper is concerned with the analysis of the algorithm in finely layered random media. We obtain a detailed characterization of the singular values of the transformed array response matrix and justify the systematic approach of the filtering algorithm for detecting and refining the time windows that contain the echoes that are useful in imaging
Higher dimensional Calabi-Yau manifolds of Kummer type
Based on Cynk-Hulek method we construct complex Calabi-Yau varieties of
arbitrary dimensions using elliptic curves with automorphism of order 6. Also
we give formulas for Hodge numbers of varieties obtained from that
construction. We shall generalize result of Katsura and Sch\"utt to obtain
arbitrarily dimensional Calabi-Yau manifolds which are Zariski in any
characteristic Comment: 13 pages, 2 figure
Adaptive time-frequency detection and filtering for imaging in heavy clutter
Abstract. We introduce an adaptive approach for the detection of a reflector in a strongly scattering medium using a timefrequency representation of the array response matrix followed by a Singular Value Decomposition (SVD). We use the Local Cosine Transform (LCT) for the time-frequency representation and introduce a detection criterion that identifies anomalies in the top singular values, across frequencies and in different time windows, that are due to the reflector. The detection is adaptive because the time windows that contain the primary echoes from the reflector are not determined in advance. Their location and width is identified by searching through the time-frequency binary tree of the LCT. After detecting the presence of the reflector we filter the array response matrix to retain information only in the time windows that have been selected. We also project the filtered array response matrix to the subspace associated with the top singular value and then image using travel time migration. We show with extensive numerical simulations that this approach to detection and imaging works well in heavy clutter that is calibrated using random matrix theory so as to simulate regimes close to the experiments in [3]. While the detection and filtering algorithm presented here works well in general clutter it has been analyzed theoretically only for the case of randomly layered media [1]
Generalized Borcea-Voisin Construction
C. Voisin and C. Borcea have constructed mirror pairs of families of
Calabi-Yau threefolds by taking the quotient of the product of an elliptic
curve with a K3 surface endowed with a non-symplectic involution. In this
paper, we generalize the construction of Borcea and Voisin to any prime order
and build three and four dimensional Calabi-Yau orbifolds. We classify the
topological types that are obtained and show that, in dimension 4, orbifolds
built with an involution admit a crepant resolution and come in topological
mirror pairs. We show that for odd primes, there are generically no minimal
resolutions and the mirror pairing is lost.Comment: 15 pages, 2 figures. v2: typos corrected & references adde
Filtering Deterministic Layer Effects in Imaging
Sensor array imaging arises in applications such as nondestructive evaluation of materials
with ultrasonic waves, seismic exploration, and radar. The sensors probe a medium with
signals and record the resulting echoes, which are then processed to determine the location
and reflectivity of remote reflectors. These could be defects in materials such as voids,
fault lines or salt bodies in the earth, and cars, buildings, or aircraft in radar applications.
Imaging is relatively well understood when the medium through which the signals
propagate is smooth, and therefore nonscattering. But in many problems the medium is
heterogeneous, with numerous small inhomogeneities that scatter the waves. We refer to
the collection of inhomogeneities as clutter, which introduces an uncertainty in imaging
because it is unknown and impossible to estimate in detail. We model the clutter as a
random process. The array data is measured in one realization of the random medium,
and the challenge is to mitigate cumulative clutter scattering so as to obtain robust images
that are statistically stable with respect to different realizations of the inhomogeneities.
Scatterers that are not buried too deep in clutter can be imaged reliably with the coherent
interferometric (CINT) approach. But in heavy clutter the signal-to-noise ratio (SNR)
is low and CINT alone does not work. The “signal,” the echoes from the scatterers to be
imaged, is overwhelmed by the “noise,” the strong clutter reverberations. There are two
existing approaches for imaging at low SNR: The first operates under the premise that data
are incoherent so that only the intensity of the scattered field can be used. The unknown
coherent scatterers that we want to image are modeled as changes in the coefficients of
diffusion or radiative transport equations satisfied by the intensities, and the problem becomes
one of parameter estimation. Because the estimation is severely ill-posed, the results
have poor resolution, unless very good prior information is available and large arrays are
used. The second approach recognizes that if there is some residual coherence in the data,
that is, some reliable phase information is available, it is worth trying to extract it and
use it with well-posed coherent imaging methods to obtain images with better resolution.
This paper takes the latter approach and presents a first attempt at enhancing the SNR
of the array data by suppressing medium reverberations. It introduces filters, or annihilators of layer backscatter, that are designed to remove primary echoes from strong, isolated
layers in a medium with additional random layering at small, subwavelength scales. These
strong layers are called deterministic because they can be imaged from the data. However,
our goal is not to image the layers, but to suppress them and thus enhance the echoes
from compact scatterers buried deep in the medium. Surprisingly, the layer annihilators
work better than intended, in the sense that they suppress not only the echoes from the
deterministic layers, but also multiply scattered ones in the randomly layered structure.
Following the layer annihilators presented here, other filters of general, nonlayered
heavy clutter have been developed. We review these more recent developments and the
challenges of imaging in heavy clutter in the introduction in order to place the research
presented here in context. We then present in detail the layer annihilators and show with
analysis and numerical simulations how they work
Unveiling the intruder deformed 0 state in Si
The 0 state in Si has been populated at the {\sc Ganil/Lise3}
facility through the -decay of a newly discovered 1 isomer in
Al of 26(1) ms half-life. The simultaneous detection of pairs
allowed the determination of the excitation energy E(0)=2719(3) keV and
the half-life T=19.4(7) ns, from which an electric monopole strength of
(E0)=13.0(0.9) was deduced. The 2 state is
observed to decay both to the 0 ground state and to the newly observed
0 state (via a 607(2) keV transition) with a ratio
R(2)=1380(717). Gathering all
information, a weak mixing with the 0 and a large deformation parameter
of =0.29(4) are found for the 0 state, in good agreement with
shell model calculations using a new {\sc sdpf-u-mix} interaction allowing
\textit{np-nh} excitations across the N=20 shell gap.Comment: 5 pages, 3 figures, accepted for publication in Physical Review
Letter
Spectroscopy of P using the one-proton knockout reaction
The structure of P was studied with a one-proton knockout reaction
at88~MeV/u from a S projectile beam at NSCL. The rays from
thedepopulation of excited states in P were detected with GRETINA,
whilethe P nuclei were identified event-by-event in the focal plane of
theS800 spectrograph. The level scheme of P was deduced up to 7.5 MeV
using coincidences. The observed levels were attributed to
protonremovals from the -shell and also from the deeply-bound
orbital.The orbital angular momentum of each state was derived from the
comparisonbetween experimental and calculated shapes of individual
(-gated)parallel momentum distributions. Despite the use of different
reactions andtheir associate models, spectroscopic factors, , derived
from theS knockout reaction agree with those obtained earlier
fromS(,\nuc{3}{He}) transfer, if a reduction factor , as
deducedfrom inclusive one-nucleon removal cross sections, is applied to the
knockout transitions.In addition to the expected proton-hole configurations,
other states were observedwith individual cross sections of the order of
0.5~mb. Based on their shiftedparallel momentum distributions, their decay
modes to negative parity states,their high excitation energy (around 4.7~MeV)
and the fact that they were notobserved in the (,\nuc{3}{He}) reaction, we
propose that they may resultfrom a two-step mechanism or a nucleon-exchange
reaction with subsequent neutronevaporation. Regardless of the mechanism, that
could not yet be clarified, thesestates likely correspond to neutron core
excitations in \nuc{35}{P}. Thisnewly-identified pathway, although weak, offers
the possibility to selectivelypopulate certain intruder configurations that are
otherwise hard to produceand identify.Comment: 5 figures, 1 table, accepted for publication in Physical Review
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