Academic literature on the topic 'Power Specturm'

ABSTRACT We analyse the 1D spatial power spectra of dust surface density and mid to far-infrared emission at $24\!-\!500\, \mu$m in the LMC, SMC, M31, and M33. By forward-modelling the point spread function (PSF) on the power spectrum, we find that nearly all power spectra have a single power-law and point source component. A broken power-law model is only favoured for the LMC 24 μm MIPS power spectrum and is due to intense dust heating in 30 Doradus. We also test for local power spectrum variations by splitting the LMC and SMC maps into 820 pc boxes. We find significant variations in the power-law index with no strong evidence for breaks. The lack of a ubiquitous break suggests that the spatial power spectrum does not constrain the disc scale height. This contradicts claims of a break where the turbulent motion changes from 3D to 2D. The power spectrum indices in the LMC, SMC, and M31 are similar (2.0–2.5). M33 has a flatter power spectrum (1.3), similar to more distant spiral galaxies with a centrally-concentrated H2 distribution. We compare the power spectra of H i, CO, and dust in M31 and M33, and find that H i power spectra are consistently flatter than CO power spectra. These results cast doubt on the idea that the spatial power spectrum traces large scale turbulent motion in nearby galaxies. Instead, we find that the spatial power spectrum is influenced by (1) the PSF on scales below ∼3 times the FWHM, (2) bright compact regions (30 Doradus), and (3) the global morphology of the tracer (an exponential CO disc).

In this paper, a method for estimating atmospheric refractivity from sea and land clutters is proposed. To estimate the atmospheric refractivity, clutter power spectrums based on an artificial tri-linear model are calculated using an Advanced Refractive Prediction System (AREPS) simulator. Then, the clutter power spectrums are again obtained based on the measured atmospheric refractivity data using the AREPS simulator. In actual operation, this spectrum from measured reflectivity can be replaced with real-time clutter spectrums collected from radars. A cost function for the genetic algorithm (GA) is then defined based on the difference between the two clutter power spectrums to predict the atmospheric refractivity using the artificial tri-linear model. The optimum variables of the tri-linear model are determined at a minimum cost in the GA process. The results demonstrate that atmospheric refractivity can be predicted using the proposed method from the clutter powers.

Since its introduction a few years ago the use of the power/response spectrum transformation has gained considerable interest and acceptance, and a number of new applications of the transformation have been developed in the equipment qualification area. A brief review of the power/response spectrum transformation is given with a discussion of the input/output relationships for linear systems required for elevated power spectrum generation. Frequency content of earthquakelike signals is discussed with emphasis on the resolution given by the PSD. The problem of excessive ZPA due to inconsistent spectra enveloping and mechanical nonlinearities is also discussed. The PSD/RS transformation is applied to the problems of combining various dynamic load events, developing bounding spectra, and developing damping consistent test spectra. Development of elevated component spectra corrected for base overtest and generation from in-situ measurements is reviewed.

ABSTRACT We use a suite of N-body simulations to study intrinsic alignments (IA) of halo shapes with the surrounding large-scale structure in the ΛCDM model. For this purpose, we develop a novel method to measure multipole moments of the three-dimensional power spectrum of the E-mode field of halo shapes with the matter/halo distribution, $P_{\delta E}^{(\ell)}(k)$ (or $P^{(\ell)}_{{\rm h}E}$), and those of the auto-power spectrum of the E-mode, $P^{(\ell)}_{EE}(k)$, based on the E/B-mode decomposition. The IA power spectra have non-vanishing amplitudes over the linear to non-linear scales, and the large-scale amplitudes at k ≲ 0.1 h−1 Mpc are related to the matter power spectrum via a constant coefficient (AIA), similar to the linear bias parameter of galaxy or halo density field. We find that the cross- and auto-power spectra PδE and PEE at non-linear scales, k ≳ 0.1 h−1 Mpc, show different k-dependences relative to the matter power spectrum, suggesting a violation of the non-linear alignment model commonly used to model contaminations of cosmic shear signals. The IA power spectra exhibit baryon acoustic oscillations, and vary with halo samples of different masses, redshifts, and cosmological parameters (Ωm, S8). The cumulative signal-to-noise ratio for the IA power spectra is about 60 per cent of that for the halo density power spectrum, where the super-sample covariance is found to give a significant contribution to the total covariance. Thus our results demonstrate that the IA power spectra of galaxy shapes, measured from imaging and spectroscopic surveys for an overlapping area of the sky, can be used to probe the underlying matter power spectrum, the primordial curvature perturbations, and cosmological parameters, in addition to the standard galaxy density power spectrum.