Deep multiredshift limits on Epoch of Reionization 21 cm power spectra from four seasons of Murchison Widefield Array observations

We compute the spherically averaged power spectrum from four seasons of data obtained for the Epoch of Reionization (EoR) project observed with the Murchison Widefield Array (MWA). We measure the EoR power spectrum over k = 0.07–3.0 h Mpc−1 at redshifts $z$ = 6.5–8.7. The largest aggregation of 110 h on EoR0 high band (3340 observations), yields a lowest measurement of (43 mK)2 = 1.8 × 103 mK2 at k = 0.14 h Mpc−1 and $z$ = 6.5 (2σ thermal noise plus sample variance). Using the Real-Time System to calibrate and the CHIPS pipeline to estimate power spectra, we select the best observations from the central five pointings within the 2013–2016 observing seasons, observing three independent fields and in two frequency bands. This yields 13 591 2-min snapshots (453 h), based on a quality assurance metric that measures ionospheric activity. We perform another cut to remove poorly calibrated data, based on power in the foreground-dominated and EoR-dominated regions of the two-dimensional power spectrum, reducing the set to 12 569 observations (419 h). These data are processed in groups of 20 observations, to retain the capacity to identify poor data, and used to analyse the evolution and structure of the data over field, frequency, and data quality. We subsequently choose the cleanest 8935 observations (298 h of data) to form integrated power spectra over the different fields, pointings, and redshift ranges.

Using Dynamic Light Scattering Experimental Setup and Neural Networks For Particle Sizing

Using a Lorentzian function fit as reference, a basic experiment was designed for processing Dynamic Light Scattering time series, allowing to estimate the average particle size of a suspension. For fitting the averaged power spectrum of the time series, several neural network configurations were tested in order to compare the results with the reference. The results of this comparison revealed a good match, serving as a proof of concept for using neural networks as an alternative for DLS time series processing.

Emplacement of Lamproites in and around Ramadugu, Nalgonda District- ground Magnetic evidence

<p>The total magnetic intensity data has been collected in and around Ramadugu Village in Eastern DharwarCraton to understand the magnetic evidence over the known Lamproites zones in conjunction with geology and geomorphology. Based on the magnetic, geological and geomorphological signatures observed from the known lamproites potential zones, new probable locations are identified in the study area. Nine magnetic lows and fourteen magnetic highs are traced, lows are representing the presence of Lamproites within the granite gneiss, and highs are observed over the presence of banded iron formations. The generated analytical (Horizontal, Vertical, Tilt, Analytical signal) maps from the total magnetic anomaly show the trends of the magnetic lineaments and trending in NW-SE, NE-SW &amp;E-W direction. The coefficient of variation (CV) of the magnetic data clearly identified four tectonic disturbed (A.B,C,D) zones, various faults and other lineaments/dykes and the intersection of lineaments, geological, morpho structural, tectonic aspects of reported occurrence of lamproites near Ramadugu and Vattikodu areas were found to be localized at surrounding of the domal peripherals. Using this criterion eight potential lamproites zones were delineated(2,3,4,5,8,9,10,11 and 13) in the study region. The long normalized radial averaged power spectrum of the study area indicated that the depth to the granite gneiss basement is around 2 Km.The dyke configurations in the region was obtained via the inversion of magnetic profiles.</p>

Evolutionary Spectral Analyses of a Powerful Typhoon at the Sutong Bridge Site Based on the HHT

To investigate the nonstationary characteristics of strong typhoons, this paper considers the evolutionary spectral characteristics of strong typhoons based on the Hilbert-Huang transform (HHT). Discrete expressions are determined for the evolutionary spectral analysis based on the HHT. The study indicates that the classic empirical mode decomposition (EMD) method fails to extract all of the high-frequency fluctuations from wind velocity data, and the time-averaged power spectrum obtained directly using the HHT cannot provide the true wind velocity spectrum. The degrees of nonstationarity of different-order IMF components are analysed and a synthesized method of analysing the evolutionary spectrum and time-averaged power spectrum of a strong typhoon is proposed. To avoid the energy leakage problem that exists in HHT spectral analyses, the Gram-Schmidt method is used to orthogonalize the intrinsic mode function (IMF) components. The study indicates that when the orthogonalization is implemented in accordance with the sequence from high-order IMF components to low-order ones, the orthogonalized components retain the same good Hilbert property as that of the IMFs. The synthesized method proposed yields a time-averaged power spectrum that is consistent with the Fourier spectrum in value and can produce the energy distributions of a typhoon in the time and frequency domains simultaneously.

High-Efficiency Carrier Frequency Estimation Algorithm for Real-Time Multi-Domain Communication Signal Analysis

Based on real-time multi-domain communication signal analysis architecture, a high-efficiency blind carrier frequency estimation algorithm using the power spectrum symmetry of the measured modulated signal is presented. The proposed algorithm, which utilizes the moving averaged power spectrum achieved by the realtime spectrum analysis, iteratively identifies the carrier frequency in according to the power difference between the upper sideband and lower sideband, which is defined and revised by the estimated carrier frequency in each iteration. When the power difference of the two sidebands converges to the preset threshold, the carrier frequency can be obtained. For the modulation analysis, the measured signal can be coarsely compensated by the estimated result, and the residual carrier frequency error is eliminated by a following carrier synchronization loop. Compared with previous works, owing to the moving averaged power spectrum normalization and the smart iterative step variation mechanism for the two sidebands definition, the carrier frequency estimation accuracy and speed can be significantly improved without increasing the computational effort. Experimental results are included to demonstrate the outstanding performance of the proposed algorithm.

Damping Coefficient Induces Stochastic Multiresonance in Bistable System with Asymmetric Dichotomous Noise

Stochastic resonance (SR) and stochastic multiresonance (SMR) phenomena as a function of the underdamping and overdamping coefficients in bistable system with asymmetric dichotomous noise are investigated numerically. By the efficient numerical simulation of the asymmetric dichotomous noise and the fourth-order Runge-Kutta algorithm, we calculate the system responses, the averaged power spectrum, and the signal-noise-ratio (SNR) that can be a measure of the existence of SR and SMR phenomenon. And the effects of damping coefficients on the three characteristics are analyzed. Firstly, it is found that the periodic asymmetric distribution of the particle’s hopping between two potential wells in the system response is gradually weakened as underdamping coefficient is increased to overdamping coefficient. And it also displays the periodic asymmetric distribution under the circumstance of overdamping coefficient. Then the averaged power spectrum exhibits multiple sharp peaks, and the highest peak increases and decreases for underdamping coefficient which is added to overdamping coefficient. Finally, SNR versus the damping coefficient for the system parameters and the noise parameters are acquired and they show multiple peaks and valleys, which illustrates the obvious SMR phenomena in bistable system with asymmetric dichotomous noise.

An Approach To Discrete Spectrum Correction Based on Energy Centroid

This paper proves that the energy centre of symmetric window function is the coordinate origin in discrete spectrum analysis. The correction formula of frequency, amplitude and phase can be obtained using this character. Simulation demonstrates that this method can correct averaged power spectrum directly with simple algorithm and fast processing speed, and the interference of negative or narrow interval frequencies has little influence on correction precision. This method is suitable for all kinds of symmetric window. But it is not suited with dense frequencies signal or continuous spectrum.