7,387 research outputs found
High-contrast imaging in the Hyades with snapshot LOCI
To image faint substellar companions obscured by the stellar halo and
speckles, scattered light from the bright primary star must be removed in
hardware or software. We apply the "locally-optimized combination of images"
(LOCI) algorithm to 1-minute Keck Observatory snapshots of GKM dwarfs in the
Hyades using source diversity to determine the most likely PSF. We obtain a
mean contrast of 10^{-2} at 0.01", 10^{-4} at <1", and 10^{-5} at 5". New brown
dwarf and low-mass stellar companions to Hyades primaries are found in a third
of the 84 targeted systems. This campaign shows the efficacy of LOCI on
snapshot imaging as well as on bright wide binaries with off-axis LOCI,
reaching contrasts sufficient for imaging 625-Myr late-L/early-T dwarfs purely
in post-processing.Comment: 12 pages, 12 figures, to appear in SPIE Astronomy 2012, paper
8447-16
MCMC methods for functions modifying old algorithms to make\ud them faster
Many problems arising in applications result in the need\ud
to probe a probability distribution for functions. Examples include Bayesian nonparametric statistics and conditioned diffusion processes. Standard MCMC algorithms typically become arbitrarily slow under the mesh refinement dictated by nonparametric description of the unknown function. We describe an approach to modifying a whole range of MCMC methods which ensures that their speed of convergence is robust under mesh refinement. In the applications of interest the data is often sparse and the prior specification is an essential part of the overall modeling strategy. The algorithmic approach that we describe is applicable whenever the desired probability measure has density with respect to a Gaussian process or Gaussian random field prior, and to some useful non-Gaussian priors constructed through random truncation. Applications are shown in density estimation, data assimilation in fluid mechanics, subsurface geophysics and image registration. The key design principle is to formulate the MCMC method for functions. This leads to algorithms which can be implemented via minor modification of existing algorithms, yet which show enormous speed-up on a wide range of applied problems
Fluctuation characteristics of the TCV snowflake divertor measured with high speed visible imaging
Tangentially viewing fast camera footage of the low-field side snowflake
minus divertor in TCV is analysed across a four point scan in which the
proximity of the two X-points is varied systematically. The motion of
structures observed in the post- processed movie shows two distinct regions of
the camera frame exhibiting differing patterns. One type of motion in the outer
scrape-off layer remains present throughout the scan whilst the other, apparent
in the inner scrape-off layer between the two nulls, becomes increasingly
significant as the X-points contract towards one another. The spatial structure
of the fluctuations in both regions is shown to conform to the equilibrium
magnetic field. When the X-point gap is wide the fluctuations measured in the
region between the X-points show a similar structure to the fluctuations
observed above the null region, remaining coherent for multiple toroidal turns
of the magnetic field and indicating a physical connectivity of the
fluctuations between the upstream and downstream regions. When the X-point gap
is small the fluctuations in the inner scrape-off layer between the nulls are
decorrelated from fluctuations upstream, indicating local production of
filamentary structures. The motion of filaments in the inter-null region
differs, with filaments showing a dominantly poloidal motion along magnetic
flux surfaces when the X-point gap is large, compared to a dominantly radial
motion across flux-surfaces when the gap is small. This demonstrates an
enhancement to cross-field tranport between the nulls of the TCV low-field-side
snowflake minus when the gap between the nulls is small.Comment: Accepted for publication in Plasma Physics and Controlled Fusio
LANDSAT-D investigations in snow hydrology
Work undertaken during the contract and its results are described. Many of the results from this investigation are available in journal or conference proceedings literature - published, accepted for publication, or submitted for publication. For these the reference and the abstract are given. Those results that have not yet been submitted separately for publication are described in detail. Accomplishments during the contract period are summarized as follows: (1) analysis of the snow reflectance characteristics of the LANDSAT Thematic Mapper, including spectral suitability, dynamic range, and spectral resolution; (2) development of a variety of atmospheric models for use with LANDSAT Thematic Mapper data. These include a simple but fast two-stream approximation for inhomogeneous atmospheres over irregular surfaces, and a doubling model for calculation of the angular distribution of spectral radiance at any level in an plane-parallel atmosphere; (3) incorporation of digital elevation data into the atmospheric models and into the analysis of the satellite data; and (4) textural analysis of the spatial distribution of snow cover
Enhancing retinal images by nonlinear registration
Being able to image the human retina in high resolution opens a new era in
many important fields, such as pharmacological research for retinal diseases,
researches in human cognition, nervous system, metabolism and blood stream, to
name a few. In this paper, we propose to share the knowledge acquired in the
fields of optics and imaging in solar astrophysics in order to improve the
retinal imaging at very high spatial resolution in the perspective to perform a
medical diagnosis. The main purpose would be to assist health care
practitioners by enhancing retinal images and detect abnormal features. We
apply a nonlinear registration method using local correlation tracking to
increase the field of view and follow structure evolutions using correlation
techniques borrowed from solar astronomy technique expertise. Another purpose
is to define the tracer of movements after analyzing local correlations to
follow the proper motions of an image from one moment to another, such as
changes in optical flows that would be of high interest in a medical diagnosis.Comment: 21 pages, 7 figures, submitted to Optics Communication
Seismic Ray Impedance Inversion
This thesis investigates a prestack seismic inversion scheme implemented in the ray
parameter domain. Conventionally, most prestack seismic inversion methods are
performed in the incidence angle domain. However, inversion using the concept of
ray impedance, as it honours ray path variation following the elastic parameter
variation according to Snell’s law, shows the capacity to discriminate different
lithologies if compared to conventional elastic impedance inversion.
The procedure starts with data transformation into the ray-parameter domain and then
implements the ray impedance inversion along constant ray-parameter profiles. With
different constant-ray-parameter profiles, mixed-phase wavelets are initially estimated
based on the high-order statistics of the data and further refined after a proper well-to-seismic
tie. With the estimated wavelets ready, a Cauchy inversion method is used to
invert for seismic reflectivity sequences, aiming at recovering seismic reflectivity
sequences for blocky impedance inversion. The impedance inversion from reflectivity
sequences adopts a standard generalised linear inversion scheme, whose results are
utilised to identify rock properties and facilitate quantitative interpretation. It has also
been demonstrated that we can further invert elastic parameters from ray impedance
values, without eliminating an extra density term or introducing a Gardner’s relation
to absorb this term.
Ray impedance inversion is extended to P-S converted waves by introducing the
definition of converted-wave ray impedance. This quantity shows some advantages in
connecting prestack converted wave data with well logs, if compared with the shearwave
elastic impedance derived from the Aki and Richards approximation to the
Zoeppritz equations. An analysis of P-P and P-S wave data under the framework of
ray impedance is conducted through a real multicomponent dataset, which can reduce
the uncertainty in lithology identification.Inversion is the key method in generating those examples throughout the entire thesis
as we believe it can render robust solutions to geophysical problems. Apart from the
reflectivity sequence, ray impedance and elastic parameter inversion mentioned above,
inversion methods are also adopted in transforming the prestack data from the offset
domain to the ray-parameter domain, mixed-phase wavelet estimation, as well as the
registration of P-P and P-S waves for the joint analysis.
The ray impedance inversion methods are successfully applied to different types of
datasets. In each individual step to achieving the ray impedance inversion, advantages,
disadvantages as well as limitations of the algorithms adopted are detailed. As a
conclusion, the ray impedance related analyses demonstrated in this thesis are highly
competent compared with the classical elastic impedance methods and the author
would like to recommend it for a wider application
Analytic Properties and Covariance Functions of a New Class of Generalized Gibbs Random Fields
Spartan Spatial Random Fields (SSRFs) are generalized Gibbs random fields,
equipped with a coarse-graining kernel that acts as a low-pass filter for the
fluctuations. SSRFs are defined by means of physically motivated spatial
interactions and a small set of free parameters (interaction couplings). This
paper focuses on the FGC-SSRF model, which is defined on the Euclidean space
by means of interactions proportional to the squares of the
field realizations, as well as their gradient and curvature. The permissibility
criteria of FGC-SSRFs are extended by considering the impact of a
finite-bandwidth kernel. It is proved that the FGC-SSRFs are almost surely
differentiable in the case of finite bandwidth. Asymptotic explicit expressions
for the Spartan covariance function are derived for and ; both known
and new covariance functions are obtained depending on the value of the
FGC-SSRF shape parameter. Nonlinear dependence of the covariance integral scale
on the FGC-SSRF characteristic length is established, and it is shown that the
relation becomes linear asymptotically. The results presented in this paper are
useful in random field parameter inference, as well as in spatial interpolation
of irregularly-spaced samples.Comment: 24 pages; 4 figures Submitted for publication to IEEE Transactions on
Information Theor
- …