972 resultados para Acoustic oscillation
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An acoustic plasmon is predicted to occur, in addition to the conventional two-dimensional (2D) plasmon, as the collective motion of a system of two types of electronic carriers coexisting in the same 2D band of extrinsic (doped or gated) graphene. The origin of this novel mode stems from the anisotropy present in the graphene band structure near the Dirac points K and K'. This anisotropy allows for the coexistence of carriers moving with two distinct Fermi velocities along the Gamma K and Gamma K' directions, which leads to two modes of collective oscillation: one mode in which the two types of carriers oscillate in phase with one another (this is the conventional 2D graphene plasmon, which at long wavelengths (q -> 0) has the same dispersion, q(1/2), as the conventional 2D plasmon of a 2D free electron gas), and the other mode found here corresponds to a low-frequency acoustic oscillation (whose energy exhibits at long-wavelengths a linear dependence on the 2D wavenumber q) in which the two types of carriers oscillate out of phase. This prediction represents a realization of acoustic
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We reconstruct the interaction rate between dark matter and the holographic dark energy with the parametrized equation of states and the future event horizon as the infrared cutoff length. It is shown that the observational constraints from the 192 type Ia Supernovae (SnIa) and baryon acoustic oscillation (BAO) measurement permit the negative interaction in the wide region. Moreover, the usual phenomenological descriptions cannot describe the reconstructed interaction well for many cases. The other possible interaction is also discussed.
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We probe the systematic uncertainties from the 113 Type Ia supernovae (SN Ia) in the Pan-STARRS1 (PS1) sample along with 197 SN Ia from a combination of low-redshift surveys. The companion paper by Rest et al. describes the photometric measurements and cosmological inferences from the PS1 sample. The largest systematic uncertainty stems from the photometric calibration of the PS1 and low-z samples. We increase the sample of observed Calspec standards from 7 to 10 used to define the PS1 calibration system. The PS1 and SDSS-II calibration systems are compared and discrepancies up to ∼0.02 mag are recovered. We find uncertainties in the proper way to treat intrinsic colors and reddening produce differences in the recovered value of w up to 3%. We estimate masses of host galaxies of PS1 supernovae and detect an insignificant difference in distance residuals of the full sample of 0.037 ± 0.031 mag for host galaxies with high and low masses. Assuming flatness and including systematic uncertainties in our analysis of only SNe measurements, we find w = -1.120+0.360-0.206(Stat)+0.269-0.291(Sys). With additional constraints from Baryon acoustic oscillation, cosmic microwave background (CMB) (Planck) and H0 measurements, we find w = -1.166+0.072-0.069 and Ωm = 0.280+0.013-0.012 (statistical and systematic errors added in quadrature). The significance of the inconsistency with w = -1 depends on whether we use Planck or Wilkinson Microwave Anisotropy Probe measurements of the CMB: wBAO+H0+SN+WMAP = -1.124+0.083-0.065.
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We present grizP1 light curves of 146 spectroscopically confirmed Type Ia supernovae (SNe Ia; 0.03 < z < 0.65) discovered during the first 1.5 yr of the Pan-STARRS1 Medium Deep Survey. The Pan-STARRS1 natural photometric system is determined by a combination of on-site measurements of the instrument response function and observations of spectrophotometric standard stars. We find that the systematic uncertainties in the photometric system are currently 1.2% without accounting for the uncertainty in the Hubble Space Telescope Calspec definition of the AB system. A Hubble diagram is constructed with a subset of 113 out of 146 SNe Ia that pass our light curve quality cuts. The cosmological fit to 310 SNe Ia (113 PS1 SNe Ia + 222 light curves from 197 low-z SNe Ia), using only supernovae (SNe) and assuming a constant dark energy equation of state and flatness, yields w = -1.120+0.360-0.206(Stat)+0.2690.291(Sys). When combined with BAO+CMB(Planck)+H0, the analysis yields ΩM = 0.280+0.0130.012 and w = -1.166+0.072-0.069 including all identified systematics. The value of w is inconsistent with the cosmological constant value of -1 at the 2.3σ level. Tension endures after removing either the baryon acoustic oscillation (BAO) or the H0 constraint, though it is strongest when including the H0 constraint. If we include WMAP9 cosmic microwave background (CMB) constraints instead of those from Planck, we find w = -1.124+0.083-0.065, which diminishes the discord to <2σ. We cannot conclude whether the tension with flat ΛCDM is a feature of dark energy, new physics, or a combination of chance and systematic errors. The full Pan-STARRS1 SN sample with ∼three times as many SNe should provide more conclusive results.
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Clusters of galaxies are the most impressive gravitationally-bound systems in the universe, and their abundance (the cluster mass function) is an important statistic to probe the matter density parameter (Omega(m)) and the amplitude of density fluctuations (sigma(8)). The cluster mass function is usually described in terms of the Press-Schecther (PS) formalism where the primordial density fluctuations are assumed to be a Gaussian random field. In previous works we have proposed a non-Gaussian analytical extension of the PS approach with basis on the q-power law distribution (PL) of the nonextensive kinetic theory. In this paper, by applying the PL distribution to fit the observational mass function data from X-ray highest flux-limited sample (HIFLUGCS), we find a strong degeneracy among the cosmic parameters, sigma(8), Omega(m) and the q parameter from the PL distribution. A joint analysis involving recent observations from baryon acoustic oscillation (BAO) peak and Cosmic Microwave Background (CMB) shift parameter is carried out in order to break these degeneracy and better constrain the physically relevant parameters. The present results suggest that the next generation of cluster surveys will be able to probe the quantities of cosmological interest (sigma(8), Omega(m)) and the underlying cluster physics quantified by the q-parameter.
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We examine different phenomenological interaction models for Dark Energy and Dark Matter by performing statistical joint analysis with observational data arising from the 182 Gold type la supernova samples, the shift parameter of the Cosmic Microwave Background given by the three-year Wilkinson Microwave Anisotropy Probe observations, the baryon acoustic oscillation measurement from the Sloan Digital Sky Survey and age estimates of 35 galaxies. Including the time-dependent observable, we add sensitivity of measurement and give complementary results for the fitting. The compatibility among three different data sets seem to imply that the coupling between dark energy and dark matter is a small positive value, which satisfies the requirement to solve the coincidence problem and the second law of thermodynamics, being compatible with previous estimates. (c) 2008 Elsevier B.V. All rights reserved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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We investigate theoretical and observational aspects of a time-dependent parameterization for the dark energy equation of state w(z), which is a well behaved function of the redshift z over the entire cosmological evolution, i.e., z is an element of [-1, infinity). By using a theoretical algorithm of constructing the quintes-sence potential directly from the w(z) function, we derive and discuss the general features of the resulting potential for the cases in which dark energy is separately conserved and when it is coupled to dark matter. Since the parameterization here discussed allows us to divide the parametric plane in defined regions associated to distinct classes of dark energy models, we use some of the most recent observations from type Ia supernovae, baryon acoustic oscillation peak and Cosmic Microwave Background shift parameter to check which class is observationally preferred. We show that the largest portion of the confidence contours lies into the region corresponding to a possible crossing of the so-called phantom divide line at some point of the cosmic evolution.
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Simplifying the Einstein field equation by assuming the cosmological principle yields a set of differential equations which governs the dynamics of the universe as described in the cosmological standard model. The cosmological principle assumes the space appears the same everywhere and in every direction and moreover, the principle has earned its position as a fundamental assumption in cosmology by being compatible with the observations of the 20th century. It was not until the current century when observations in cosmological scales showed significant deviation from isotropy and homogeneity implying the violation of the principle. Among these observations are the inconsistency between local and non-local Hubble parameter evaluations, baryon acoustic features of the Lyman-α forest and the anomalies of the cosmic microwave background radiation. As a consequence, cosmological models beyond the cosmological principle have been studied vastly; after all, the principle is a hypothesis and as such should frequently be tested as any other assumption in physics. In this thesis, the effects of inhomogeneity and anisotropy, arising as a consequence of discarding the cosmological principle, is investigated. The geometry and matter content of the universe becomes more cumbersome and the resulting effects on the Einstein field equation is introduced. The cosmological standard model and its issues, both fundamental and observational are presented. Particular interest is given to the local Hubble parameter, supernova explosion, baryon acoustic oscillation, and cosmic microwave background observations and the cosmological constant problems. Explored and proposed resolutions emerging by violating the cosmological principle are reviewed. This thesis is concluded by a summary and outlook of the included research papers.
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An introduction to a modified forced oscillation method, square-wave excitation technique, including fundamentals and methods, as used in respiratory function examination. On the basis of experimental results and theoretical predictions, we suggest that Respiratory Acoustic Impedance (RAI) measurement by spectral analysis can significantly improve estimation of contribution to RAI from different part of respiratory tract. The outcome is of considerable interest in the study of lung disease, such as COPD and asthma in young children.
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This technical report is concerned with one aspect of environmental monitoring—the detection and analysis of acoustic events in sound recordings of the environment. Sound recordings offer ecologists the advantage of cheaper and increased sampling but make available so much data that automated analysis becomes essential. The report describes a number of tools for automated analysis of recordings, including noise removal from spectrograms, acoustic event detection, event pattern recognition, spectral peak tracking, syntactic pattern recognition applied to call syllables, and oscillation detection. These algorithms are applied to a number of animal call recognition tasks, chosen because they illustrate quite different modes of analysis: (1) the detection of diffuse events caused by wind and rain, which are frequent contaminants of recordings of the terrestrial environment; (2) the detection of bird and calls; and (3) the preparation of acoustic maps for whole ecosystem analysis. This last task utilises the temporal distribution of events over a daily, monthly or yearly cycle.
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This paper presents a system to analyze long field recordings with low signal-to-noise ratio (SNR) for bio-acoustic monitoring. A method based on spectral peak track, Shannon entropy, harmonic structure and oscillation structure is proposed to automatically detect anuran (frog) calling activity. Gaussian mixture model (GMM) is introduced for modelling those features. Four anuran species widespread in Queensland, Australia, are selected to evaluate the proposed system. A visualization method based on extracted indices is employed for detection of anuran calling activity which achieves high accuracy.
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Acoustic classification of anurans (frogs) has received increasing attention for its promising application in biological and environment studies. In this study, a novel feature extraction method for frog call classification is presented based on the analysis of spectrograms. The frog calls are first automatically segmented into syllables. Then, spectral peak tracks are extracted to separate desired signal (frog calls) from background noise. The spectral peak tracks are used to extract various syllable features, including: syllable duration, dominant frequency, oscillation rate, frequency modulation, and energy modulation. Finally, a k-nearest neighbor classifier is used for classifying frog calls based on the results of principal component analysis. The experiment results show that syllable features can achieve an average classification accuracy of 90.5% which outperforms Mel-frequency cepstral coefficients features (79.0%).
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Frog protection has become increasingly essential due to the rapid decline of its biodiversity. Therefore, it is valuable to develop new methods for studying this biodiversity. In this paper, a novel feature extraction method is proposed based on perceptual wavelet packet decomposition for classifying frog calls in noisy environments. Pre-processing and syllable segmentation are first applied to the frog call. Then, a spectral peak track is extracted from each syllable if possible. Track duration, dominant frequency and oscillation rate are directly extracted from the track. With k-means clustering algorithm, the calculated dominant frequency of all frog species is clustered into k parts, which produce a frequency scale for wavelet packet decomposition. Based on the adaptive frequency scale, wavelet packet decomposition is applied to the frog calls. Using the wavelet packet decomposition coefficients, a new feature set named perceptual wavelet packet decomposition sub-band cepstral coefficients is extracted. Finally, a k-nearest neighbour (k-NN) classifier is used for the classification. The experiment results show that the proposed features can achieve an average classification accuracy of 97.45% which outperforms syllable features (86.87%) and Mel-frequency cepstral coefficients (MFCCs) feature (90.80%).