13,385 research outputs found
Selective Principal Component Extraction and Reconstruction: A Novel Method for Ground Based Exoplanet Spectroscopy
Context: Infrared spectroscopy of primary and secondary eclipse events probes
the composition of exoplanet atmospheres and, using space telescopes, has
detected H2O, CH4 and CO2 in three hot Jupiters. However, the available data
from space telescopes has limited spectral resolution and does not cover the
2.4 - 5.2 micron spectral region. While large ground based telescopes have the
potential to obtain molecular-abundance-grade spectra for many exoplanets,
realizing this potential requires retrieving the astrophysical signal in the
presence of large Earth-atmospheric and instrument systematic errors. Aims:
Here we report a wavelet-assisted, selective principal component extraction
method for ground based retrieval of the dayside spectrum of HD 189733b from
data containing systematic errors. Methods: The method uses singular value
decomposition and extracts those critical points of the Rayleigh quotient which
correspond to the planet induced signal. The method does not require prior
knowledge of the planet spectrum or the physical mechanisms causing systematic
errors. Results: The spectrum obtained with our method is in excellent
agreement with space based measurements made with HST and Spitzer (Swain et al.
2009b; Charbonneau et al. 2008) and confirms the recent ground based
measurements (Swain et al. 2010) including the strong 3.3 micron emission.Comment: 4 pages, 3 figures; excepted for publication by A&
Key Issues in the Analysis of Remote Sensing Data: A report on the workshop
The procedures of a workshop assessing the state of the art of machine analysis of remotely sensed data are summarized. Areas discussed were: data bases, image registration, image preprocessing operations, map oriented considerations, advanced digital systems, artificial intelligence methods, image classification, and improved classifier training. Recommendations of areas for further research are presented
Bayesian classification in a time-varying environment
The problem of classifying a pattern based on multiple observation made in a time-varying environment is analyzed. The identity of the pattern may itself change. A Bayesian solution is derived, after which the conditions of the physical situation are invoked to produce a cascade classifier model. Experimental results based on remote sensing data demonstrate the effectiveness of the classifier
Contact angles on heterogeneous surfaces; a new look at Cassie's and Wenzel's laws
We consider a three dimensional liquid drop sitting on a rough and chemically
heterogeneous substrate. Using a novel minimization technique on the free
energy of this system, a generalized Young's equation for the contact angle is
found. In certain limits, the Cassie and Wenzel laws, and a new equivalent
rule, applicable in general, are derived. We also propose an equation in the
same spirit as these results but valid on a more `microscopic' level.
Throughout we work under the presence of gravity and keep account of line
tension terms.Comment: 10 pages RevTeX, 2 EPS figures. A few minor corrections mad
Wetting between structured surfaces: Liquid bridges and induced forces
Wetting phenomena are theoretically studied for a slab geometry
consisting of a wetting phase confined between two chemically
patterned substrates. Each of these is decorated by an array of
stripes whose composition alternates between two different surface
phases. For a single pair of opposing stripes, the wetting phase may
either form a bridge spanning from one surface to the other or it may
break up into two separate channels. The bridge state induces an
effective interaction between the two substrates. This leads to the
bridge itself having a preferred contact angle and the substrates
having a preferred separation. In the case of many stripes, one has a
whole sequence of morphological transitions with the number of bridges
decreasing as the surface separation grows
The Influence of Substrate Structure on Membrane Adhesion
We consider a membrane both weakly and strongly adhering to a geometrically
structured substrate. The interaction potential is assumed to be local, via the
Deryagin approximation, and harmonic. Consequently, we can analytically
describe a variety of different geometries: as well as randomly rough
self-affine surfaces, smooth substrates interrupted by an isolated cylindrical
pit, a single elongated trench or a periodic array of trenches are
investigated. We present more general expressions for the adhesion energy and
membrane configuration in Fourier space and find that, compared to planar
surfaces, the adhesion energy decreases. We also highlight the possibility of
overshoots occurring in the membrane profile and look at its degree of
penetration into surface indentations.Comment: 41 pages LaTex, 12 EPS figure
Corrugation-Induced First-Order Wetting: An Effective Hamiltonian Study
We consider an effective Hamiltonian description of critical wetting
transitions in systems with short-range forces at a corrugated (periodic) wall.
We are able to recover the results obtained previously from a `microscopic'
density-functional approach in which the system wets in a discontinuous manner
when the amplitude of the corrugations reaches a critical size A*. Using the
functional renormalization group, we find that A* becomes dependent on the
wetting parameter \omega in such a way as to decrease the extent of the
first-order regime. Nevertheless, we still expect wetting in the Ising model to
proceed in a discontinuous manner for small deviations of the wall from the
plane.Comment: 9 pages RevTex with 2 EPS figures. To appear in Eur. Phys. J.
An exact solution for two dimensional wetting with a corrugated wall
An exact solution of a two dimensional RSOS model of wetting at a corrugated
(periodic) wall is found using transfer matrix techniques. In contrast to
mean-field analysis of the same problem the wetting transition remains
second-order and occurs at a lower temperature than that of the planar system.
Comparison with numerical studies and other analytical approaches is made.Comment: 11 pages LaTex with 1 eps figure. To appear in J.Phys.
Coupled Hamiltonians and Three Dimensional Short-Range Wetting Transitions
We address three problems faced by effective interfacial Hamiltonian models
of wetting based on a single collective coordinate \ell representing the
position of the unbinding fluid interface. Problems (P1) and (P2) refer to the
predictions of non-universality at the upper critical dimension d=3 at critical
and complete wetting respectively which are not borne out by Ising model
simulation studies. (P3) relates to mean-field correlation function structure
in the underlying continuum Landau model. We investigate the hypothesis that
these concerns arise due to the coupling of order parameter fluctuations near
the unbinding interface and wall. For quite general choices of collective
coordinates X_i we show that arbitrary two-field models H[X_1,X_2] can recover
the required anomalous structure of mean-field correlation functions (P3). To
go beyond mean-field theory we introduce a set of Hamiltonians based on proper
collective coordinates s near the wall which have both interfacial and
spin-like components. We argue that an optimum model H[s,\ell] in which the
degree of coupling is controlled by an angle-like variable, best describes the
non-universality of the Ising model and investigate its critical behaviour. For
critical wetting the appropriate Ginzburg criterion shows that the true
asymptotic critical regime for the local susceptibility \chi_1 is dramatically
reduced consistent with observations of mean-field behaviour in simulations
(P1). For complete wetting the model yields a precise expression for the
temperature dependence of the renormalized critical amplitude \theta in good
agreement with simulations (P2). We highlight the importance of a new wetting
parameter which describes the physics that emerges due to the coupling effects.Comment: 34 pages, RevTex, 8 eps figures. To appear in Physica
A method for classification of multisource data using interval-valued probabilities and its application to HIRIS data
A method of classifying multisource data in remote sensing is presented. The proposed method considers each data source as an information source providing a body of evidence, represents statistical evidence by interval-valued probabilities, and uses Dempster's rule to integrate information based on multiple data source. The method is applied to the problems of ground-cover classification of multispectral data combined with digital terrain data such as elevation, slope, and aspect. Then this method is applied to simulated 201-band High Resolution Imaging Spectrometer (HIRIS) data by dividing the dimensionally huge data source into smaller and more manageable pieces based on the global statistical correlation information. It produces higher classification accuracy than the Maximum Likelihood (ML) classification method when the Hughes phenomenon is apparent
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