916 resultados para Auto-correlation function
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The structure and dynamics of the ionic liquid 1-ethyl-3-methylimidazolium nitrate is studied by molecular dynamics simulations. We find long-range spatial correlations between the ions and a three-dimensional local structure that reflects the asymmetry of the cations. The main contribution to the configurational energy comes from the electrostatic interactions which leads to charge-ordering effects. Radial screening and threedimensional distribution of charge are also analyzed. The motion of a single ion is studied via velocity and reorientational correlation functions. It is found that ions "rattle" in a long-lived cage, while the orientational structure relaxes on a time scale longer than 200 ps. As in a supercooled liquid, the mean square displacements reveal a subdiffusive dynamics. In addition, the presence of dynamic heterogeneities can be detected by analyzing the non-Gaussian behavior of the van Hove correlation function and the spatial arrangement of the most mobile ions. The short-time collective dynamics is also studied through the electric current time correlation function.
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A force field model of the Keating type supplemented by rules to break, form, and interchange bonds is applied to investigate thermodynamic and structural properties of the amorphous SiO2 surface. A simulated quench from the liquid phase has been carried out for a silica sample made of 3888 silicon and 7776 oxygen atoms arranged on a slab similar to 40 angstrom thick, periodically repeated along two directions. The quench results into an amorphous sample, exposing two parallel square surfaces of similar to 42 nm(2) area each. Thermal averages computed during the quench allow us to determine the surface thermodynamic properties as a function of temperature. The surface tension turns out to be gamma=310 +/- 20 erg/cm(2) at room temperature and gamma=270 +/- 30 at T=2000 K, in fair agreement with available experimental estimates. The entropy contribution Ts-s to the surface tension is relatively low at all temperatures, representing at most similar to 20% of the surface energy. Almost without exceptions, Si atoms are fourfold coordinated and oxygen atoms are twofold coordinated. Twofold and threefold rings appear only at low concentration and are preferentially found in proximity of the surface. Above the glass temperature T-g=1660 +/- 50 K, the mobility of surface atoms is, as expected, slightly higher than that of bulk atoms. The computation of the height-height correlation function shows that the silica surface is rough in the equilibrium and undercooled liquid phase, becoming smooth below the glass temperature T-g.
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Ultracold polar molecules, in highly anisotropic traps and interacting via a repulsive dipolar potential, may form one-dimensional chains at high densities. According to classical theory, at low temperatures there exists a critical value of the density at which a second-order phase transition from a linear to a zigzag chain occurs. We study the effect of thermal and quantum fluctuations on these self-organized structures using classical and quantum Monte Carlo methods, by means of which we evaluate the pair correlation function and the static structure factor. Depending on the parameters, these functions exhibit properties typical of a crystalline or of a liquid system. We compare the thermal and the quantum results, identifying analogies and differences. Finally, we discuss experimental parameter regimes where the effects of quantum fluctuations on the linear-zigzag transition can be observed.
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We show that the statistical properties of a Coulomb crystal can be measured by means of a standard interferometric procedure performed on the spin of one ion in the chain. The ion spin, constituted by two internal levels of the ion, couples to the crystal modes via spatial displacement induced by photon absorption. The loss of contrast in the interferometric signal allows one to measure the autocorrelation function of the crystal observables. Close to the critical point, where the chain undergoes a second-order phase transition to a zigzag structure, the signal gives the behavior of the correlation function at the critical point.
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Tese de doutoramento, Ciências Geofísicas e da Geoinformação (Geofisíca), Universidade de Lisboa, Faculdade de Ciências, 2014
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Las características principales de las redes de cerco artesanales anchoveteras para CHD (PS 01.1.0 “ISSCFG”), utilizan tamaños de malla en el copo y cuerpo de ½” ~ 13 mm de material nylon Poliamida (PA). Se encontró una diferencia en las dimensiones, el material y diámetro del hilo del paño usado, entre las redes de las ANC-CHD tradicionales (Paita, Chimbote, Callao e Ilo) que utilizan paños anchoveteros de R310tex, R381tex R462tex, con longitud de relinga superior (LRS) de 183-366 m (100 a 200 bz), altura de paño estirado (AHE) de 27 a 64 m (15 a 35 bz); y las redes de cerco ANC-Pisco que utilizan paños anchoveteros de R155tex y R230tex, con LRS de 270 a 396 m (145 a 215 bz) y AHE de 30 m (16 bz). Del análisis regresional experimental, las principales características de la red (LRS, AHE), y la embarcación–capacidad de bodega-(CBOD) presentaron correlaciones significativas para la flota ANC-Tradicional (r = 0,86 y 0,91), mientras que en la flota ANC-Pisco las correlación de la función CBODLRS fue de 0,30 y la AHE fue constante (30 m) para todo el rango de LRS (270 - 396 m).
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Raman scattering in the region 20 to 100 cm -1 for fused quartz, "pyrex" boro-silicate glass, and soft soda-lime silicate glass was investigated. The Raman spectra for the fused quartz and the pyrex glass were obtained at room temperature using the 488 nm exciting line of a Coherent Radiation argon-ion laser at powers up to 550 mW. For the soft soda-lime glass the 514.5 nm exciting line at powers up to 660 mW was used because of a weak fluorescence which masked the Stokes Raman spectrum. In addition it is demonstrated that the low-frequency Raman coupling constant can be described by a model proposed by Martin and Brenig (MB). By fitting the predicted spectra based on the model with a Gaussian, Poisson, and Lorentzian forms of the correlation function, the structural correlation radius (SCR) was determined for each glass. It was found that to achieve the best possible fit· from each of the three correlation functions a value of the SCR between 0.80 and 0.90 nm was required for both quartz and pyrex glass but for the soft soda-lime silicate glass the required value of the SCR. was between 0.50 and 0.60 nm .. Our results support the claim of Malinovsky and Sokolov (1986) that the MB model based on a Poisson correlation function provides a universal fit to the experimental VH (vertical and horizontal polarizations) spectrum for any glass regardless of its chemical composition. The only deficiency of the MB model is its failure to fit the experimental depolarization spectra.
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The thesis has covered various aspects of modeling and analysis of finite mean time series with symmetric stable distributed innovations. Time series analysis based on Box and Jenkins methods are the most popular approaches where the models are linear and errors are Gaussian. We highlighted the limitations of classical time series analysis tools and explored some generalized tools and organized the approach parallel to the classical set up. In the present thesis we mainly studied the estimation and prediction of signal plus noise model. Here we assumed the signal and noise follow some models with symmetric stable innovations.We start the thesis with some motivating examples and application areas of alpha stable time series models. Classical time series analysis and corresponding theories based on finite variance models are extensively discussed in second chapter. We also surveyed the existing theories and methods correspond to infinite variance models in the same chapter. We present a linear filtering method for computing the filter weights assigned to the observation for estimating unobserved signal under general noisy environment in third chapter. Here we consider both the signal and the noise as stationary processes with infinite variance innovations. We derived semi infinite, double infinite and asymmetric signal extraction filters based on minimum dispersion criteria. Finite length filters based on Kalman-Levy filters are developed and identified the pattern of the filter weights. Simulation studies show that the proposed methods are competent enough in signal extraction for processes with infinite variance.Parameter estimation of autoregressive signals observed in a symmetric stable noise environment is discussed in fourth chapter. Here we used higher order Yule-Walker type estimation using auto-covariation function and exemplify the methods by simulation and application to Sea surface temperature data. We increased the number of Yule-Walker equations and proposed a ordinary least square estimate to the autoregressive parameters. Singularity problem of the auto-covariation matrix is addressed and derived a modified version of the Generalized Yule-Walker method using singular value decomposition.In fifth chapter of the thesis we introduced partial covariation function as a tool for stable time series analysis where covariance or partial covariance is ill defined. Asymptotic results of the partial auto-covariation is studied and its application in model identification of stable auto-regressive models are discussed. We generalize the Durbin-Levinson algorithm to include infinite variance models in terms of partial auto-covariation function and introduce a new information criteria for consistent order estimation of stable autoregressive model.In chapter six we explore the application of the techniques discussed in the previous chapter in signal processing. Frequency estimation of sinusoidal signal observed in symmetric stable noisy environment is discussed in this context. Here we introduced a parametric spectrum analysis and frequency estimate using power transfer function. Estimate of the power transfer function is obtained using the modified generalized Yule-Walker approach. Another important problem in statistical signal processing is to identify the number of sinusoidal components in an observed signal. We used a modified version of the proposed information criteria for this purpose.
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Using a scaling assumption, we propose a phenomenological model aimed to describe the joint probability distribution of two magnitudes A and T characterizing the spatial and temporal scales of a set of avalanches. The model also describes the correlation function of a sequence of such avalanches. As an example we study the joint distribution of amplitudes and durations of the acoustic emission signals observed in martensitic transformations [Vives et al., preceding paper, Phys. Rev. B 52, 12 644 (1995)].
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We derive a new representation for a function as a linear combination of local correlation kernels at optimal sparse locations and discuss its relation to PCA, regularization, sparsity principles and Support Vector Machines. We first review previous results for the approximation of a function from discrete data (Girosi, 1998) in the context of Vapnik"s feature space and dual representation (Vapnik, 1995). We apply them to show 1) that a standard regularization functional with a stabilizer defined in terms of the correlation function induces a regression function in the span of the feature space of classical Principal Components and 2) that there exist a dual representations of the regression function in terms of a regularization network with a kernel equal to a generalized correlation function. We then describe the main observation of the paper: the dual representation in terms of the correlation function can be sparsified using the Support Vector Machines (Vapnik, 1982) technique and this operation is equivalent to sparsify a large dictionary of basis functions adapted to the task, using a variation of Basis Pursuit De-Noising (Chen, Donoho and Saunders, 1995; see also related work by Donahue and Geiger, 1994; Olshausen and Field, 1995; Lewicki and Sejnowski, 1998). In addition to extending the close relations between regularization, Support Vector Machines and sparsity, our work also illuminates and formalizes the LFA concept of Penev and Atick (1996). We discuss the relation between our results, which are about regression, and the different problem of pattern classification.
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The structure of gold cyanide, AuCN, has been determined at 10 and 300 K using total neutron diffraction. The structure consists of infinite -Au-(CN)-Au-(CN)-Au-(CN)- linear chains, hexagonally packed, with the gold atoms in sheets. The Au-C and Au-N bond lengths are found to be identical, with d(Au-C/N) = 1.9703(5) Angstrom at 300 K. This work supersedes a previous study, by others, which used Rietveld analysis of neutron Bragg diffraction in isolation, and found these bonds to have significantly different lengths (Deltad = 0.24 Angstrom) at 300 K. The total correlation function, T(r), at 10 and 300 K, has been modeled using information derived from total diffraction. The broadening of inter- and intrachain correlations differs markedly due to random displacements of the chains in the direction of the chain axes. This is a consequence of the relatively weak bonding between the chains. An explanation for the negative thermal expansion in the c-direction, which occurs between 10 and 300 K, is presented.
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We present molecular dynamics (MD) and slip-springs model simulations of the chain segmental dynamics in entangled linear polymer melts. The time-dependent behavior of the segmental orientation autocorrelation functions and mean-square segmental displacements are analyzed for both flexible and semiflexible chains, with particular attention paid to the scaling relations among these dynamic quantities. Effective combination of the two simulation methods at different coarse-graining levels allows us to explore the chain dynamics for chain lengths ranging from Z ≈ 2 to 90 entanglements. For a given chain length of Z ≈ 15, the time scales accessed span for more than 10 decades, covering all of the interesting relaxation regimes. The obtained time dependence of the monomer mean square displacements, g1(t), is in good agreement with the tube theory predictions. Results on the first- and second-order segmental orientation autocorrelation functions, C1(t) and C2(t), demonstrate a clear power law relationship of C2(t) C1(t)m with m = 3, 2, and 1 in the initial, free Rouse, and entangled (constrained Rouse) regimes, respectively. The return-to-origin hypothesis, which leads to inverse proportionality between the segmental orientation autocorrelation functions and g1(t) in the entangled regime, is convincingly verified by the simulation result of C1(t) g1(t)−1 t–1/4 in the constrained Rouse regime, where for well-entangled chains both C1(t) and g1(t) are rather insensitive to the constraint release effects. However, the second-order correlation function, C2(t), shows much stronger sensitivity to the constraint release effects and experiences a protracted crossover from the free Rouse to entangled regime. This crossover region extends for at least one decade in time longer than that of C1(t). The predicted time scaling behavior of C2(t) t–1/4 is observed in slip-springs simulations only at chain length of 90 entanglements, whereas shorter chains show higher scaling exponents. The reported simulation work can be applied to understand the observations of the NMR experiments.
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Neutron diffraction at 11.4 and 295 K and solid-state 67Zn NMR are used to determine both the local and average structures in the disordered, negative thermal expansion (NTE) material, Zn(CN)2. Solid-state NMR not only confirms that there is head-to-tail disorder of the C≡N groups present in the solid, but yields information about the relative abundances of the different Zn(CN)4-n(NC)n tetrahedral species, which do not follow a simple binomial distribution. The Zn(CN)4 and Zn(NC)4 species occur with much lower probabilities than are predicted by binomial theory, supporting the conclusion that they are of higher energy than the other local arrangements. The lowest energy arrangement is Zn(CN)2(NC)2. The use of total neutron diffraction at 11.4 K, with analysis of both the Bragg diffraction and the derived total correlation function, yields the first experimental determination of the individual Zn−N and Zn−C bond lengths as 1.969(2) and 2.030(2) Å, respectively. The very small difference in bond lengths, of ~0.06 Å, means that it is impossible to obtain these bond lengths using Bragg diffraction in isolation. Total neutron diffraction also provides information on both the average and local atomic displacements responsible for NTE in Zn(CN)2. The principal motions giving rise to NTE are shown to be those in which the carbon and nitrogen atoms within individual Zn−C≡N−Zn linkages are displaced to the same side of the Zn···Zn axis. Displacements of the carbon and nitrogen atoms to opposite sides of the Zn···Zn axis, suggested previously in X-ray studies as being responsible for NTE behavior, in fact make negligible contribution at temperatures up to 295 K.
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In multiple-input multiple-output (MIMO) radar systems, the transmitters emit orthogonal waveforms to increase the spatial resolution. New frequency hopping (FH) codes based on chaotic sequences are proposed. The chaotic sequences have the characteristics of good encryption, anti-jamming properties and anti-intercept capabilities. The main idea of chaotic FH is based on queuing theory. According to the sensitivity to initial condition, these sequences can achieve good Hamming auto-correlation while also preserving good average correlation. Simulation results show that the proposed FH signals can achieve lower autocorrelation side lobe level and peak cross-correlation level with the increasing of iterations. Compared to the LFM signals, this sequence has higher range-doppler resolution.
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We present a detailed description of the Voronoi Tessellation (VT) cluster finder algorithm in 2+1 dimensions, which improves on past implementations of this technique. The need for cluster finder algorithms able to produce reliable cluster catalogs up to redshift 1 or beyond and down to 10(13.5) solar masses is paramount especially in light of upcoming surveys aiming at cosmological constraints from galaxy cluster number counts. We build the VT in photometric redshift shells and use the two-point correlation function of the galaxies in the field to both determine the density threshold for detection of cluster candidates and to establish their significance. This allows us to detect clusters in a self-consistent way without any assumptions about their astrophysical properties. We apply the VT to mock catalogs which extend to redshift 1.4 reproducing the ACDM cosmology and the clustering properties observed in the Sloan Digital Sky Survey data. An objective estimate of the cluster selection function in terms of the completeness and purity as a function of mass and redshift is as important as having a reliable cluster finder. We measure these quantities by matching the VT cluster catalog with the mock truth table. We show that the VT can produce a cluster catalog with completeness and purity > 80% for the redshift range up to similar to 1 and mass range down to similar to 10(13.5) solar masses.