971 resultados para Cross spectral properties


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In the present thesis a thourough multiwavelength analysis of a number of galaxy clusters known to be experiencing a merger event is presented. The bulk of the thesis consists in the analysis of deep radio observations of six merging clusters, which host extended radio emission on the cluster scale. A composite optical and X–ray analysis is performed in order to obtain a detailed and comprehensive picture of the cluster dynamics and possibly derive hints about the properties of the ongoing merger, such as the involved mass ratio, geometry and time scale. The combination of the high quality radio, optical and X–ray data allows us to investigate the implications of the ongoing merger for the cluster radio properties, focusing on the phenomenon of cluster scale diffuse radio sources, known as radio halos and relics. A total number of six merging clusters was selected for the present study: A3562, A697, A209, A521, RXCJ 1314.4–2515 and RXCJ 2003.5–2323. All of them were known, or suspected, to possess extended radio emission on the cluster scale, in the form of a radio halo and/or a relic. High sensitivity radio observations were carried out for all clusters using the Giant Metrewave Radio Telescope (GMRT) at low frequency (i.e. ≤ 610 MHz), in order to test the presence of a diffuse radio source and/or analyse in detail the properties of the hosted extended radio emission. For three clusters, the GMRT information was combined with higher frequency data from Very Large Array (VLA) observations. A re–analysis of the optical and X–ray data available in the public archives was carried out for all sources. Propriety deep XMM–Newton and Chandra observations were used to investigate the merger dynamics in A3562. Thanks to our multiwavelength analysis, we were able to confirm the existence of a radio halo and/or a relic in all clusters, and to connect their properties and origin to the reconstructed merging scenario for most of the investigated cases. • The existence of a small size and low power radio halo in A3562 was successfully explained in the theoretical framework of the particle re–acceleration model for the origin of radio halos, which invokes the re–acceleration of pre–existing relativistic electrons in the intracluster medium by merger–driven turbulence. • A giant radio halo was found in the massive galaxy cluster A209, which has likely undergone a past major merger and is currently experiencing a new merging process in a direction roughly orthogonal to the old merger axis. A giant radio halo was also detected in A697, whose optical and X–ray properties may be suggestive of a strong merger event along the line of sight. Given the cluster mass and the kind of merger, the existence of a giant radio halo in both clusters is expected in the framework of the re–acceleration scenario. • A radio relic was detected at the outskirts of A521, a highly dynamically disturbed cluster which is accreting a number of small mass concentrations. A possible explanation for its origin requires the presence of a merger–driven shock front at the location of the source. The spectral properties of the relic may support such interpretation and require a Mach number M < ∼ 3 for the shock. • The galaxy cluster RXCJ 1314.4–2515 is exceptional and unique in hosting two peripheral relic sources, extending on the Mpc scale, and a central small size radio halo. The existence of these sources requires the presence of an ongoing energetic merger. Our combined optical and X–ray investigation suggests that a strong merging process between two or more massive subclumps may be ongoing in this cluster. Thanks to forthcoming optical and X–ray observations, we will reconstruct in detail the merger dynamics and derive its energetics, to be related to the energy necessary for the particle re–acceleration in this cluster. • Finally, RXCJ 2003.5–2323 was found to possess a giant radio halo. This source is among the largest, most powerful and most distant (z=0.317) halos imaged so far. Unlike other radio halos, it shows a very peculiar morphology with bright clumps and filaments of emission, whose origin might be related to the relatively high redshift of the hosting cluster. Although very little optical and X–ray information is available about the cluster dynamical stage, the results of our optical analysis suggest the presence of two massive substructures which may be interacting with the cluster. Forthcoming observations in the optical and X–ray bands will allow us to confirm the expected high merging activity in this cluster. Throughout the present thesis a cosmology with H0 = 70 km s−1 Mpc−1, m=0.3 and =0.7 is assumed.

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The purpose of this Thesis is to develop a robust and powerful method to classify galaxies from large surveys, in order to establish and confirm the connections between the principal observational parameters of the galaxies (spectral features, colours, morphological indices), and help unveil the evolution of these parameters from $z \sim 1$ to the local Universe. Within the framework of zCOSMOS-bright survey, and making use of its large database of objects ($\sim 10\,000$ galaxies in the redshift range $0 < z \lesssim 1.2$) and its great reliability in redshift and spectral properties determinations, first we adopt and extend the \emph{classification cube method}, as developed by Mignoli et al. (2009), to exploit the bimodal properties of galaxies (spectral, photometric and morphologic) separately, and then combining together these three subclassifications. We use this classification method as a test for a newly devised statistical classification, based on Principal Component Analysis and Unsupervised Fuzzy Partition clustering method (PCA+UFP), which is able to define the galaxy population exploiting their natural global bimodality, considering simultaneously up to 8 different properties. The PCA+UFP analysis is a very powerful and robust tool to probe the nature and the evolution of galaxies in a survey. It allows to define with less uncertainties the classification of galaxies, adding the flexibility to be adapted to different parameters: being a fuzzy classification it avoids the problems due to a hard classification, such as the classification cube presented in the first part of the article. The PCA+UFP method can be easily applied to different datasets: it does not rely on the nature of the data and for this reason it can be successfully employed with others observables (magnitudes, colours) or derived properties (masses, luminosities, SFRs, etc.). The agreement between the two classification cluster definitions is very high. ``Early'' and ``late'' type galaxies are well defined by the spectral, photometric and morphological properties, both considering them in a separate way and then combining the classifications (classification cube) and treating them as a whole (PCA+UFP cluster analysis). Differences arise in the definition of outliers: the classification cube is much more sensitive to single measurement errors or misclassifications in one property than the PCA+UFP cluster analysis, in which errors are ``averaged out'' during the process. This method allowed us to behold the \emph{downsizing} effect taking place in the PC spaces: the migration between the blue cloud towards the red clump happens at higher redshifts for galaxies of larger mass. The determination of $M_{\mathrm{cross}}$ the transition mass is in significant agreement with others values in literature.

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Visual stress is a condition characterised by symptoms of eyestrain, headaches and distortions of visual perception when reading text. The symptoms are frequently alleviated with spectral filters and precision tinted ophthalmic lenses. Visual stress is thought to arise due to cortical hyperexcitability and is associated with a range of neurological conditions. Cortical hyperexcitability is known to occur following stroke. The case presented describes visual stress symptoms resulting from stroke, subsequently managed with spectral filters and precision tinted ophthalmic lenses. The case also highlights that the spectral properties of the tint may need to be modified if the disease course alters.

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Lasers with random distributed feedback (DFB) owing to Rayleigh scattering in optical fibers [1] have attracted a great interest: a number of papers demonstrating new laser schemes and applications have been proposed [2-7] recently. Moreover, the generation output power and, more generally, generation power distribution could be described both analytically and numerically within simple balance models [8-9]. However, spectral properties of random DFB fiber lasers are not studied except some attempt made in [10]. Generation spectrum of random DFB fiber laser is quite broad (more than 1 nm), and physical mechanisms of its formation and broadening are still unclear. There is no any practical solution up to date to minimize the generation spectrum width. Here we experimentally show the way to minimize the generation spectral width. © 2013 IEEE.

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The spectral properties of long-period gratings (LPGs) fabricated in photonic crystal fibers using femtosecond laser pulses by the point-by-point technique, without oil-immersion of the fiber, are investigated in detail. Postfabrication spectral monitoring at room temperature showed significant long-term instability of the gratings and stable spectra only after 600 h. The stabilized spectral properties of the gratings improved with increasing annealing temperature. The observed changes in resonant wavelength, optical strength, and grating birefringence were correlated to the laser inscription energy and were further used to study the mechanism of femtosecond inscription. Furthermore, the femtosecond-laser inscribed LPGs were compared to electric-arc fabricated LPGs. Comparison of experimental results with theoretical models of LPGs and laser propagation during inscription indicate that the major processes responsible for the index change are permanent compaction and thermally induced strain, the latter can be significantly changed through annealing. © 2011 Optical Society of America.

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Multi-output Gaussian processes provide a convenient framework for multi-task problems. An illustrative and motivating example of a multi-task problem is multi-region electrophysiological time-series data, where experimentalists are interested in both power and phase coherence between channels. Recently, the spectral mixture (SM) kernel was proposed to model the spectral density of a single task in a Gaussian process framework. This work develops a novel covariance kernel for multiple outputs, called the cross-spectral mixture (CSM) kernel. This new, flexible kernel represents both the power and phase relationship between multiple observation channels. The expressive capabilities of the CSM kernel are demonstrated through implementation of 1) a Bayesian hidden Markov model, where the emission distribution is a multi-output Gaussian process with a CSM covariance kernel, and 2) a Gaussian process factor analysis model, where factor scores represent the utilization of cross-spectral neural circuits. Results are presented for measured multi-region electrophysiological data.

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This dissertation investigates the connection between spectral analysis and frame theory. When considering the spectral properties of a frame, we present a few novel results relating to the spectral decomposition. We first show that scalable frames have the property that the inner product of the scaling coefficients and the eigenvectors must equal the inverse eigenvalues. From this, we prove a similar result when an approximate scaling is obtained. We then focus on the optimization problems inherent to the scalable frames by first showing that there is an equivalence between scaling a frame and optimization problems with a non-restrictive objective function. Various objective functions are considered, and an analysis of the solution type is presented. For linear objectives, we can encourage sparse scalings, and with barrier objective functions, we force dense solutions. We further consider frames in high dimensions, and derive various solution techniques. From here, we restrict ourselves to various frame classes, to add more specificity to the results. Using frames generated from distributions allows for the placement of probabilistic bounds on scalability. For discrete distributions (Bernoulli and Rademacher), we bound the probability of encountering an ONB, and for continuous symmetric distributions (Uniform and Gaussian), we show that symmetry is retained in the transformed domain. We also prove several hyperplane-separation results. With the theory developed, we discuss graph applications of the scalability framework. We make a connection with graph conditioning, and show the in-feasibility of the problem in the general case. After a modification, we show that any complete graph can be conditioned. We then present a modification of standard PCA (robust PCA) developed by Cand\`es, and give some background into Electron Energy-Loss Spectroscopy (EELS). We design a novel scheme for the processing of EELS through robust PCA and least-squares regression, and test this scheme on biological samples. Finally, we take the idea of robust PCA and apply the technique of kernel PCA to perform robust manifold learning. We derive the problem and present an algorithm for its solution. There is also discussion of the differences with RPCA that make theoretical guarantees difficult.

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The development of organic materials with 2PA has attracted intensive attention in the past two decades [1]. In two-photon bio-imaging applications the design of the chromophore requires to have a good cross-section (σ2PA) and good biological compatibility which depends on the molecular volume and polarity [2]. In this work, we present the design, synthesis and characterization of new indolium derivatives. These compounds are easy to achieve with good yields and good photophysical properties. In addition, time-dependent density functional theory (TDDFT) has been carried out to investigate the energy level of the ground and excited state. Their spectral properties and assays performed on cultured cells, demonstrate the potential of these compounds as fluorescent probes with application in two-photon bio-imaging.

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Near-infrared spectroscopy is a somewhat unutilised technique for the study of minerals. The technique has the ability to determine water content, hydroxyl groups and transition metals. In this paper we show the application of NIR spectroscopy to the study of selected minerals. The structure and spectral properties of two Cu-tellurite minerals graemite and teineite are compared with bismuth containing tellurite mineral smirnite by the application of NIR and IR spectroscopy. The position of Cu2+ bands and their splitting in the electronic spectra of tellurites are in conformity with octahedral geometry distortion. The spectral pattern of smirnite resembles graemite and the observed band at 10855 cm-1 with a weak shoulder at 7920 cm-1 is identified as due to Cu2+ ion. Any transition metal impurities may be identified by their bands in this spectral region. Three prominent bands observed in the region of 7200-6500 cm-1 are the overtones of water whilst the weak bands observed near 6200 cm-1in tellurites may be attributed to the hydrogen bonding between (TeO3)2- and H2O. The observation of a number of bands centred at around 7200 cm-1 confirms molecular water in tellurite minerals. A number of overlapping bands in the low wavenumbers 4500-4000 cm-1 is the result of combinational modes of (TeO3)2−ion. The appearance of the most intense peak at 5200 cm-1 with a pair of weak bands near 6000 cm-1 is a common feature in all the spectra and is related to the combinations of OH vibrations of water molecules, and bending vibrations ν2 (δ H2O). Bending vibrations δ H2O observed in the IR spectra shows a single band for smirnite at 1610 cm-1. The resolution of this band into number of components is evidenced for non-equivalent types of molecular water in graemite and teineite. (TeO3)2- stretching vibrations are characterized by three main absorptions at 1080, 780 and 695 cm-1.

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NIR and IR spectroscopy has been applied for detection of chemical species and the nature of hydrogen bonding in arsenate complexes. The structure and spectral properties of copper(II) arsenate minerals chalcophyllite and chenevixite are compared with copper(II) sulphate minerals devilline, chalcoalumite and caledonite. Split NIR bands in the electronic spectrum of two ranges 11700-8500 cm-1 and 8500-7200 cm-1 confirm distortion of octahedral symmetry for Cu(II) in the arsenate complexes. The observed bands with maxima at 9860 and 7750 cm-1 are assigned to Cu(II) transitions 2B1g ® 2B2g and 2B1g ® 2A1g. Overlapping bands in the NIR region 4500-4000 cm-1 is the effect of multi anions OH-, (AsO4)3- and (SO4)2-. The observation of broad and diffuse bands in the range 3700-2900 cm-1 confirms strong hydrogen bonding in chalcophyllite relative to chenevixite. The position of the water bending vibrations indicates the water is strongly hydrogen bonded in the mineral structure. The strong absorption feature centred at 1644 cm-1 in chalcophyllite indicates water is strongly hydrogen bonded in the mineral structure. The H2O-bending vibrations shift to low wavenumbers in chenevixite and an additional band observed at 1390 cm-1 is related to carbonate impurity. The characterisation of IR spectra by ν3 antisymmetric stretching vibrations of (SO4)2- and (AsO4)3 ions near 1100 and 800 cm-1 respectively is the result of isomorphic substitution for arsenate by sulphate in both the minerals of chalcophyllite and chenevixite.

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The recently discovered twist phase is studied in the context of the full ten-parameter family of partially coherent general anisotropic Gaussian Schell-model beams. It is shown that the nonnegativity requirement on the cross-spectral density of the beam demands that the strength of the twist phase be bounded from above by the inverse of the transverse coherence area of the beam. The twist phase as a two-point function is shown to have the structure of the generalized Huygens kernel or Green's function of a first-order system. The ray-transfer matrix of this system is exhibited. Wolf-type coherent-mode decomposition of the twist phase is carried out. Imposition of the twist phase on an otherwise untwisted beam is shown to result in a linear transformation in the ray phase space of the Wigner distribution. Though this transformation preserves the four-dimensional phase-space volume, it is not symplectic and hence it can, when impressed on a Wigner distribution, push it out of the convex set of all bona fide Wigner distributions unless the original Wigner distribution was sufficiently deep into the interior of the set.

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Communication within and across proteins is crucial for the biological functioning of proteins. Experiments such as mutational studies on proteins provide important information on the amino acids, which are crucial for their function. However, the protein structures are complex and it is unlikely that the entire responsibility of the function rests on only a few amino acids. A large fraction of the protein is expected to participate in its function at some level or other. Thus, it is relevant to consider the protein structures as a completely connected network and then deduce the properties, which are related to the global network features. In this direction, our laboratory has been engaged in representing the protein structure as a network of non-covalent connections and we have investigated a variety of problems in structural biology, such as the identification of functional and folding clusters, determinants of quaternary association and characterization of the network properties of protein structures. We have also addressed a few important issues related to protein dynamics, such as the process of oligomerization in multimers, mechanism on protein folding, and ligand induced communications (allosteric effect). In this review we highlight some of the investigations which we have carried out in the recent past. A review on protein structure graphs was presented earlier, in which the focus was on the graphs and graph spectral properties and their implementation in the study of protein structure graphs/networks (PSN). In this article, we briefly summarize the relevant parts of the methodology and the focus is on the advancement brought out in the understanding of protein structure-function relationships through structure networks. The investigations of structural/biological problems are divided into two parts, in which the first part deals with the analysis of PSNs based on static structures obtained from x-ray crystallography. The second part highlights the changes in the network, associated with biological functions, which are deduced from the network analysis on the structures obtained from molecular dynamics simulations.

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The recently introduced generalized pencil of Sudarshan which gives an exact ray picture of wave optics is analysed in some situations of interest to wave optics. A relationship between ray dispersion and statistical inhomogeneity of the field is obtained. A paraxial approximation which preserves the rectilinear propagation character of the generalized pencils is presented. Under this approximation the pencils can be computed directly from the field conditions on a plane, without the necessity to compute the cross-spectral density function in the entire space as an intermediate quantity. The paraxial results are illustrated with examples. The pencils are shown to exhibit an interesting scaling behaviour in the far-zone. This scaling leads to a natural generalization of the Fraunhofer range criterion and of the classical van Cittert-Zernike theorem to planar sources of arbitrary state of coherence. The recently derived results of radiometry with partially coherent sources are shown to be simple consequences of this scaling.

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This thesis examines the feasibility of a forest inventory method based on two-phase sampling in estimating forest attributes at the stand or substand levels for forest management purposes. The method is based on multi-source forest inventory combining auxiliary data consisting of remote sensing imagery or other geographic information and field measurements. Auxiliary data are utilized as first-phase data for covering all inventory units. Various methods were examined for improving the accuracy of the forest estimates. Pre-processing of auxiliary data in the form of correcting the spectral properties of aerial imagery was examined (I), as was the selection of aerial image features for estimating forest attributes (II). Various spatial units were compared for extracting image features in a remote sensing aided forest inventory utilizing very high resolution imagery (III). A number of data sources were combined and different weighting procedures were tested in estimating forest attributes (IV, V). Correction of the spectral properties of aerial images proved to be a straightforward and advantageous method for improving the correlation between the image features and the measured forest attributes. Testing different image features that can be extracted from aerial photographs (and other very high resolution images) showed that the images contain a wealth of relevant information that can be extracted only by utilizing the spatial organization of the image pixel values. Furthermore, careful selection of image features for the inventory task generally gives better results than inputting all extractable features to the estimation procedure. When the spatial units for extracting very high resolution image features were examined, an approach based on image segmentation generally showed advantages compared with a traditional sample plot-based approach. Combining several data sources resulted in more accurate estimates than any of the individual data sources alone. The best combined estimate can be derived by weighting the estimates produced by the individual data sources by the inverse values of their mean square errors. Despite the fact that the plot-level estimation accuracy in two-phase sampling inventory can be improved in many ways, the accuracy of forest estimates based mainly on single-view satellite and aerial imagery is a relatively poor basis for making stand-level management decisions.

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Special switching sequences can be employed in space-vector-based generation of pulsewidth-modulated (PWM) waveforms for voltage-source inverters. These sequences involve switching a phase twice, switching the second phase once, and clamping the third phase in a subcycle. Advanced bus-clamping PWM (ABCPWM) techniques have been proposed recently that employ such switching sequences. This letter studies the spectral properties of the waveforms produced by these PWM techniques. Further, analytical closed-form expressions are derived for the total rms harmonic distortion due to these techniques. It is shown that the ABCPWM techniques lead to lower distortion than conventional space vector PWM and discontinuous PWM at higher modulation indexes. The findings are validated on a 2.2-kW constant $V/f$ induction motor drive and also on a 100-kW motor drive.