Power Spectrum Of Variability Research Articles

Emulation of f(R) modified gravity from ΛCDM using conditional GANs

Abstract A major aim of cosmological surveys is to test deviations from the standard ΛCDM model, but the full scientific value of these surveys will only be realised through efficient simulation methods that keep up with the increasing volume and precision of observational data. N-body simulations of modified gravity (MG) theories are computationally expensive since highly non-linear equations must be solved. This represents a significant bottleneck in the path to reach the data volume and resolution attained by equivalent ΛCDM simulations. We develop a field-level neural network-based emulator that generates density and velocity divergence fields under the f(R) gravity MG model from the corresponding ΛCDM simulated fields. Using attention mechanisms and a complementary frequency-based loss function, our model is able to learn this intricate mapping. We use the idea of latent space extrapolation to generalise our emulator to f(R) models with differing field strengths. The predictions of our emulator agree with the f(R) simulations to within 5% for matter density and to within 10% for velocity divergence power spectra up to k ∼ 2 h Mpc−1. But for a few select cases, higher-order statistics are reproduced with ≲10% agreement. Latent extrapolation allows our emulator to generalise to different parameterisations of the f(R) model without explicitly training on those variants. Given a ΛCDM simulation, the GPU-based emulator can reproduce the equivalent f(R) realisation ∼600 times faster than full N-body simulations. This lays the foundations for a valuable tool for realistic yet rapid mock field generation and robust cosmological analyses.

Evolution mapping II: describing statistics of the non-linear cosmic velocity field.

Abstract We extend the evolution mapping approach, introduced in the first paper of this series to describe non-linear matter density fluctuations, to statistics of the cosmic velocity field. This framework classifies cosmological parameters into shape parameters, which determine the shape of the linear matter power spectrum, PL(k, z), and evolution parameters, which control its amplitude at any redshift. Evolution mapping leverages the fact that density fluctuations in cosmologies with identical shape parameters but different evolution parameters exhibit similar non-linear evolutions when expressed as a function of clustering amplitude. We analyse a suite of N-body simulations sharing identical shape parameters but spanning a wide range of evolution parameters. Using a method for estimating the volume-weighted velocity field based on the Voronoi tesselation of simulation particles, we study the non-linear evolution of the velocity divergence power spectrum, Pθθ(k), and its cross-power spectrum with the density field, Pδθ(k). We demonstrate that the evolution mapping relation applies accurately to Pθθ(k) and Pδθ(k). While this breaks down in the strongly non-linear regime, deviations can be modelled in terms of differences in the suppression factor, g(a) = D(a)/a, similar to those for the density field. Such modelling describes the differences in Pθθ(k) between models with the same linear clustering amplitude to better than 1percnt accuracy at all scales and redshifts considered. Evolution mapping simplifies the description of the cosmological dependence of non-linear density and velocity statistics, streamlining the sampling of large cosmological parameter spaces for cosmological analysis.

Comparative analysis of electroencephalogram (EEG) data gathered from the frontal region with other brain regions affected by attention deficit hyperactivity disorder (ADHD) through multiresolution analysis and machine learning techniques

Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by repeated patterns of hyperactivity, impulsivity, and inattention that limit daily functioning and development. Electroencephalography (EEG) anomalies correspond to changes in brain connection and activity. The authors propose utilizing empirical mode decomposition (EMD) and discrete wavelet transform (DWT) for feature extraction and machine learning (ML) algorithms to categorize ADHD and control subjects. For this study, the authors considered freely accessible ADHD data obtained from the IEEE data site. Studies have demonstrated a range of EEG anomalies in ADHD patients, such as variations in power spectra, coherence patterns, and event-related potentials (ERPs). Some of the studies claimed that the brain’s prefrontal cortex and frontal regions collaborate in intricate networks, and disorders in either of them exacerbate the symptoms of ADHD. , Based on the research that claimed the brain’s prefrontal cortex and frontal regions collaborate in intricate networks, and disorders in either of them exacerbate the symptoms of ADHD, the proposed study examines the optimal position of EEG electrode for identifying ADHD and in addition to monitoring accuracy on frontal/ prefrontal and other regions of brain our study also investigates the position groupings that have the highest effect on accurateness in identification of ADHD. The results demonstrate that the dataset classified with AdaBoost provided values for accuracy, precision, specificity, sensitivity, and F1-score as 1.00, 0.70, 0.70, 0.75, and 0.71, respectively, whereas using random forest (RF) it is 0.98, 0.64, 0.60, 0.81, and 0.71, respectively, in detecting ADHD. After detailed analysis, it is observed that the most accurate results included all electrodes. The authors believe the processes can detect various neurodevelopmental problems in children utilizing EEG signals.

Decomposition of the Horizontal Wind Divergence Associated With the Rossby, Mixed Rossby‐Gravity, Inertia‐Gravity, and Kelvin Waves on the Sphere

AbstractThe paper presents a new method for the decomposition of the horizontal wind divergence among linear waves on the sphere: inertia‐gravity (IG), mixed Rossby‐gravity (MRG), Kelvin and Rossby waves. The work is motivated by the need to quantify the vertical velocity and momentum fluxes in the tropics where the distinction between the Rossby and gravity regime, present in the extratropics, becomes obliterated. The method leads to divergence power spectra as a function of latitude and pressure. The spectra follow the same power laws as the vertical kinetic energy spectra for different wave types. The key novel aspect of the work is the coexistence of wave types at the same zonal wavenumbers. Applied to ERA5 data in August 2018, the new method reveals that the zonally‐integrated Kelvin wave divergence makes up about 19% of the upper‐troposphere divergence within 10°S–10°N. The MRG wave divergence has four times smaller magnitude. The relative roles of the two waves vary with scale. Overall small roles of the Kelvin and MRG waves in the tropical divergence is explained by decomposing their kinetic energies into rotational and divergent parts. The beta effects produces less then 5% of the tropospheric divergence associated with Rossby waves. The majority of divergence belongs to IG modes and is nearly equipartitioned between the eastward‐ and westward‐propagating IG modes in the upper troposphere, whereas stratospheric partitioning depends on the background flow.

The universal power spectrum of quasars in optical wavelengths

Context. The optical variability of quasars is one of the few windows through which we can explore the behaviour of accretion discs around supermassive black holes. Aims. We aim to establish the dependence of variability properties, such as characteristic timescales and the variability amplitude, on basic quasar parameters such as black hole mass and the accretion rate, controlling for the rest-frame wavelength of emission. Methods. Using large catalogues of quasars, we selected the g-band light curves for 4770 objects from the Zwicky Transient Facility archive. All the selected objects fall into a narrow redshift bin, 0.6 < z < 0.7, but cover a wide range of accretion rates in Eddington units (REdd) and black hole masses (M). We grouped these objects into 26 independent bins according to these parameters, calculated low-resolution g-band variability power spectra for each of these bins, and approximated the power spectra with a simple analytic model that features a break at a timescale, tb. Results. We find a clear dependence of the break timescale, tb, on REdd, on top of the known dependence of tb on the black hole mass, M. In our fits, tb ∝ M0.65 − 0.55REdd0.35−0.3, where the ranges in the exponents correspond to the best-fitting parameters of different power spectrum models. This mass dependence is slightly steeper than that found in other studies. Scaling tb to the orbital timescale of the innermost stable circular orbit (ISCO), tISCO, results approximately in tb/tISCO ∝ (REdd/M)0.35. In the standard thin disc model, (REdd/M) ∝ Tmax4, where Tmax is the maximum disc temperature, so that tb/tISCO appears to scale approximately with the maximum temperature of the disc to a small power. The observed values of tb are ∼10 longer than the orbital timescale at the light-weighted average radius of the disc region emitting in the (observer frame) g-band. The different scaling of the break frequency with M and REdd shows that the shape of the variability power spectrum cannot be solely a function of the quasar luminosity, even for a single rest-frame wavelength. Finally, the best-fitting models have slopes above the break in the range between −2.5 and −3. A slope of −2, as in the damped random walk models, fits the data significantly worse.

Research on the Auto-Exposure Method of an Aerial TDI Camera Based on Scene Prediction

Aerial TDI cameras can obtain images with a high sensitivity, high resolution, and wide dynamic range under low-illumination conditions. Under the condition of low illumination, exposure is an important parameter that affects the image quality of the camera. Auto-exposure aims to obtain the information of target scene in advance and uses it as the basis for determining exposure parameters, which can avoid the loss of image information caused by overexposure or underexposure. The auto-exposure of TDI CCD is usually difficult, as the shooting mode of TDI CCD is a push and sweep mode, which can only take one image of the target scene, and the output image is not repetitive, so it is difficult to obtain an image of the target scene in advance. At present, the common method is to add an additional sensor to collect the feature information of the target scene in advance; however, this increases the complexity of the system. Therefore, this paper proposes that the camera uses TDI CCD to collect the first N rows of data of the target scene in advance as the basis, and then adjusts and determines the exposure parameters with the median gray value as the target; thus, without adding additional sensors, the auto-exposure of TDI CCD can be realized. To evaluate the effect of auto-exposure, three methods of image power spectrum variance, image histogram, and image information entropy are used. The test results show that, after auto-exposure, the variance in the image power spectrum increased by 0.4362, the entropy of image information increased by 1.7064, and the distribution of the image histogram was more uniform than that before auto-exposure. This shows that the effect of auto-exposure is good, and it has better scene adaptation, allowing for it to meet the requirements of auto-exposure imaging under low-illumination conditions in aerial TDI cameras.

Optical variability in quasars: scalings with black hole mass and Eddington ratio depend on the observed time-scales

ABSTRACT Quasars emission is highly variable, and this variability gives us clues to understand the accretion process onto supermassive black holes. We can expect variability properties to correlate with the main physical properties of the accreting black hole, i.e. its mass and accretion rate. It has been established that the relative amplitude of variability anticorrelates with the accretion rate. The dependence of the variance on black hole mass has remained elusive, and contradicting results, including positive, negative, or no correlation, have been reported. In this work, we show that the key to these contradictions lies in the times-cales of variability studied (e.g. the length of the light curves available). By isolating the variance on different time-scales in well-defined mass and accretion rate bins we show that there is indeed a negative correlation between black hole mass and variance and that this anticorrelation is stronger for shorter time-scale fluctuations. The behaviour can be explained in terms of a universal variability power spectrum for all quasars, resembling a broken power law where the variance is constant at low temporal frequencies and then drops continuously for frequencies higher than a characteristic (break) frequency fb, where fb correlates with the black hole mass. Furthermore, to explain all the variance results presented here, not only the normalization of this power spectrum must anticorrelate with the accretion rate, but also the shape of the power spectra at short time-scales must depend on this parameter as well.

The universal shape of the X-ray variability power spectrum of AGN up to z ∼ 3

Aims. We study the ensemble X-ray variability properties of active galactic nuclei (AGN) over large ranges of timescale (20 ks ≤ T ≤ 14 yr), redshift (0 ≤ z ≲ 3), luminosity (1040 erg s−1 ≤ LX ≤ 1046 erg s−1), and black hole (BH) mass (106 ≤ M⊙ ≤ 109). Methods. We propose the use of the variance-frequency diagram as a viable alternative to the study of the power spectral density (PSD), which is not yet accessible for distant, faint, and/or sparsely sampled AGN. Results. We show that the data collected from archival observations and previous literature studies are fully consistent with a universal PSD form, which does not show any evidence for systematic evolution of shape or amplitude with redshift or luminosity, even if there may be differences between individual AGN at a given redshift or luminosity. We find new evidence that the PSD bend frequency depends on BH mass and possibly on accretion rate. We finally discuss the implications for current and future AGN population and cosmological studies.

Preliminary study of heart rate variability in Criollo horses for the elucidation of their neurophysiological characteristics of autonomic nerve function.

The Criollo is an Argentine horse breed with a calm temperament. Although its temperament is considered to be related to its neurophysiological characteristics, the details of this are unknown. Therefore, we analyzed the heart rate variability in Criollos as a preliminary study to deepen the neurophysiological understanding of their autonomic function. Electrocardiograms were recorded from Criollos and Thoroughbreds, and the power spectrum of heart rate variability was analyzed. Compared with Thoroughbreds, Criollos showed (i) a significantly higher high-frequency component, which is an index of parasympathetic nerve activity, and (ii) tendency toward a lower ratio of low- to high-frequency power, which is an index of the autonomic balance. These results revealed that parasympathetic nerves might be more active in Criollos compared with Thoroughbreds.

A Universal Power-law Prescription for Variability from Synthetic Images of Black Hole Accretion Flows

We present a framework for characterizing the spatiotemporal power spectrum of the variability expected from the horizon-scale emission structure around supermassive black holes, and we apply this framework to a library of general relativistic magnetohydrodynamic (GRMHD) simulations and associated general relativistic ray-traced images relevant for Event Horizon Telescope (EHT) observations of Sgr A*. We find that the variability power spectrum is generically a red-noise process in both the temporal and spatial dimensions, with the peak in power occurring on the longest timescales and largest spatial scales. When both the time-averaged source structure and the spatially integrated light-curve variability are removed, the residual power spectrum exhibits a universal broken power-law behavior. On small spatial frequencies, the residual power spectrum rises as the square of the spatial frequency and is proportional to the variance in the centroid of emission. Beyond some peak in variability power, the residual power spectrum falls as that of the time-averaged source structure, which is similar across simulations; this behavior can be naturally explained if the variability arises from a multiplicative random field that has a steeper high-frequency power-law index than that of the time-averaged source structure. We briefly explore the ability of power spectral variability studies to constrain physical parameters relevant for the GRMHD simulations, which can be scaled to provide predictions for black holes in a range of systems in the optically thin regime. We present specific expectations for the behavior of the M87* and Sgr A* accretion flows as observed by the EHT.

First Sagittarius A* Event Horizon Telescope Results. IV. Variability, Morphology, and Black Hole Mass

In this paper we quantify the temporal variability and image morphology of the horizon-scale emission from Sgr A*, as observed by the EHT in 2017 April at a wavelength of 1.3 mm. We find that the Sgr A* data exhibit variability that exceeds what can be explained by the uncertainties in the data or by the effects of interstellar scattering. The magnitude of this variability can be a substantial fraction of the correlated flux density, reaching ∼100% on some baselines. Through an exploration of simple geometric source models, we demonstrate that ring-like morphologies provide better fits to the Sgr A* data than do other morphologies with comparable complexity. We develop two strategies for fitting static geometric ring models to the time-variable Sgr A* data; one strategy fits models to short segments of data over which the source is static and averages these independent fits, while the other fits models to the full data set using a parametric model for the structural variability power spectrum around the average source structure. Both geometric modeling and image-domain feature extraction techniques determine the ring diameter to be 51.8 ± 2.3 μas (68% credible intervals), with the ring thickness constrained to have an FWHM between ∼30% and 50% of the ring diameter. To bring the diameter measurements to a common physical scale, we calibrate them using synthetic data generated from GRMHD simulations. This calibration constrains the angular size of the gravitational radius to be μas, which we combine with an independent distance measurement from maser parallaxes to determine the mass of Sgr A* to be M ⊙.

Constraining energy-dependent emissivity profiles of AGN inflows

Abstract The emissivity of the accretion flow is a key parameter affecting the shape of both the energy and variability power spectrum of AGN. We explore the energy-dependence of the power spectrum for five AGN, across the XMM-Newton bandpass, and across the 0.01-1 mHz frequency range, finding a ubiquitous flattening of the power spectrum towards higher energies. We develop a framework to explore this behaviour and thereby extract the energy dependence of the emissivity assuming a simple disc-like geometry for the inflow. We find that the emissivity ranges from R−2 at energies around the soft excess and increases to R−4 or steeper above 4-6 keV. We describe the changing emissivity index with a linear function in energy, finding the best-fitting slopes to vary between AGN. We attempt to correlate the slope of the linear function against key AGN parameters but, as yet, the sample size is too small to confirm hints of a correlation with Eddington ratio.

Effects of renal denervation on sleep apnea and arrhythmia in rats with myocardial infarction

BackgroundSympathetic hyperactivity and poor sleep quality have been reported in patients with myocardial infarction (MI). Sleep is an important modulator of cardiovascular function. We aimed to evaluate the effects of renal denervation (RDN) on cardiac autonomic activity and disordered sleep patterns in rats with MI. MethodsWireless transmission of polysomnographic recordings was performed in sham and left coronary artery (LCA) ligation male rats during normal daytime sleep before and after RDN. Spectral analyses of electroencephalogram and electromyogram (EMG) recordings were performed to define active waking, quiet sleep, and paradoxical sleep. Cardiac autonomic activity was measured by analyzing the power spectrum of heart rate variability. Central sleep apnea events were measured by analyzing the EMG recordings of the diaphragm. ResultsIn the LCA ligation group, there was a higher low-frequency (LF)/high-frequency (HF) power ratio during sleep; the LF/HF ratio decreased significantly in the rats that underwent RDN in all sleep stages when compared with that in the rats that did not. The frequency of sleep interruptions increased without RDN in the LCA ligation group when compared with that in the sham group. This change was ameliorated and prevented with RDN in the LCA ligation group. ConclusionsOur results demonstrate significant sleep fragmentation with sympathetic hyperactivity after MI and that RDN prevents autonomic dysfunction and disordered sleep. RDN may then reduce sleep apnea and sleep-related sudden cardiac death after MI by restoring autonomic homeostasis.

Jet Parameters in the Black Hole X-Ray Binary MAXI J1820+070

Abstract We study the jet in the hard state of the accreting black hole (BH) binary MAXI J1820+070. From the available radio-to-optical spectral and variability data, we put strong constraints on the jet parameters. We find while it is not possible to uniquely determine the jet Lorentz factor from the spectral and variability properties alone, we can estimate the jet opening angle (≈1.°5 ± 1°), the distance at which the jet starts emitting synchrotron radiation (∼3 × 1010 cm), and the magnetic field strength there (∼104 G), with relatively low uncertainty, as they depend weakly on the bulk Lorentz factor. We find the breaks in the variability power spectra from radio to submillimeter wavelength are consistent with variability damping over the timescale equal to the travel time along the jet at any Lorentz factor. This factor can still be constrained by the electron–positron pair-production rate within the jet base, which we calculate based on the observed X-ray/soft-gamma-ray spectrum, and the jet power, required to be less than the accretion power. The minimum (∼1.5) and maximum (∼4.5) Lorentz factors correspond to the dominance of pairs and ions, and the minimum and maximum jet power, respectively. We estimate the magnetic flux threading the BH and find the jet can be powered by the Blandford–Znajek mechanism in a magnetically arrested flow accretion flow. We point out the similarity of our derived formalism to that of core shifts, observed in extragalactic radio sources.

A-44 Implications of the Heart Rate Variability Power Spectrum on the Relationship between Prenatal Anxiety Exposure and Child Anxiety in 5-Year-Olds

Abstract Objective To assess the role of the heart rate variability (HRV) in the relationship between prenatal anxiety exposure and subsequent child anxiety levels. Methods A longitudinal study of mother–child dyads (subsample of 89) measured maternal anxiety during the second trimester of pregnancy (self-reported via STAI-S) and subsequent child anxiety (maternal-reported via BASC-3) and baseline autonomic physiological measures (high and low frequency band of HRV power spectrum) at 5-years-old. Mediation analysis was conducted to test whether child high and/or low frequency HRV mediates the relationship between prenatal anxiety and child anxiety. Results Prenatal anxiety predicted child anxiety (β = 0.137, p = 0.004) and high frequency HRV (β = −0.009, p < 0.001), but not low frequency HRV (β = −0.002, p = 0.231). Mediation analysis using bootstrapping procedure revealed that high frequency HRV (β = 0.044, 95% CI [0.007, 0.085]), but not low frequency HRV (β = 0.0117, 95% CI [−0.007, 0.047]), mediated the relationship between prenatal anxiety and child anxiety. After controlling for high frequency HRV, prenatal anxiety was no longer associated with child anxiety (β = 0.0753, p = 0.148). Conclusion Results indicate that in-utero exposure to maternal anxiety influences the child’s high frequency but not low frequency HRV. Importantly, changes in only high frequency HRV from prenatal anxiety is driving the relationship between prenatal anxiety and child anxiety levels, indicating that maternal anxiety during pregnancy affects the development of the autonomic nervous system with long term effects on child emotional regulation. The results suggest that the high frequency portion of the HRV power spectrum should be assessed in a multidimensional model of fetal programming and subsequent mental health risk of the child.

Stellar Transits across a Magnetized Accretion Torus as a Mechanism for Plasmoid Ejection

Abstract The close neighborhood of a supermassive black hole contains not only the accreting gas and dust but also stellar-sized objects, such as late-type and early-type stars and compact remnants that belong to the nuclear star cluster. When passing through the accretion flow, these objects perturb it by the direct action of stellar winds, as well as their magnetic and gravitational effects. By performing general-relativistic magnetohydrodynamic simulations, we investigate how the passages of a star can influence the supermassive black hole gaseous environment. We focus on the changes in the accretion rate and the emergence of blobs of plasma in the funnel of an accretion torus. We compare results from 2D and 3D numerical computations that have been started with comparable initial conditions. We find that a quasi-stationary inflow can be temporarily inhibited by a transiting star, and the plasmoids can be ejected along the magnetic field lines near the rotation axis. We observe the characteristic signatures of the perturbing motion in the power spectrum of the accretion variability, which provides an avenue for a multi-messenger detection of these transient events. Finally, we discuss the connection of our results to multiwavelength observations of galactic nuclei, with the emphasis on ten promising sources (Sgr A*, OJ 287, J0849+5108, RE J1034+396, 1ES 1927+65, ESO 253–G003, GSN 069, RX J1301.9+2747, eRO-QPE1, and eRO-QPE2).

Line-of-sight and non-line-of-sight links for dispersive terahertz wireless networks

Despite the rapidly growing interest in exploiting millimeter and terahertz waves for wireless data transfer, the role of reflected non-line-of-sight (NLOS) paths in wireless networking is one of the least explored questions. In this paper, we investigate the idea of harnessing these specular NLOS paths for communication in directional networks at frequencies above 100 GHz. We explore several illustrative transmitter architectures, namely, a conventional substrate-lens dipole antenna and a leaky-wave antenna. We investigate how these high-gain directional antennas offer both new challenges and new opportunities for exploiting NLOS paths. Our results demonstrate the sensitivity to antenna alignment, power spectrum variations, and the disparity in supported bandwidth of various line-of-sight (LOS) and reflected path configurations. We show that NLOS paths can, under certain circumstances, offer even higher data rates than the conventional LOS path. This result illustrates the unique opportunities that distinguish THz wireless systems from those that operate at lower frequencies.

Cross-Spectral Analysis of Electrocardiographic and Nostril Airflow Signals Identifies Two Respiratory Frequencies of Heart Rate Modulation

Respiration is known to be a significant modulator of heart rate, and the high-frequency component in the power spectrum of heart rate variability (HRV) is believed to be caused mainly by respiration. To investigate the effect of respiration on heart rate, cross-spectral analysis of electrocardiographic (ECG) and nostril airflow signals was performed in healthy subjects to find the common features of ECG and respiration. Forty-two healthy subjects were included in this study. The autospectra of respective ECG and nostril airflow signals and the cross-spectra of ECG and nostril airflow signals were obtained and compared with the corresponding conventional HRV measures. We found that there were two spectral peaks at around 0.03 Hz and 0.3 Hz in the autospectrum of nostril airflow and the cross-spectrum of ECG and nostril airflow. In addition, the cross-spectral normalized high-frequency power (nHFPcs) was significantly larger than that of conventional HRV, while the cross-spectral normalized very low-frequency power (nVLFPcs), normalized low-frequency power (nLFPcs), and low-/high-frequency power ratio (LHRcs) were significantly lower than those of the conventional HRV. The cross-spectral nLFPcs and LHRcs had positive correlations with their corresponding HRV measures. We conclude that cross-spectral analysis of ECG and nostril airflow signals identifies two respiratory frequencies at around 0.03 Hz and below and around 0.3 Hz and can yield significantly enhanced nHFPcs and significantly suppressed nVLFPcs, as compared to their counterparts in conventional HRV. Both very low-frequency and high-frequency components of HRV are caused in part or mainly by respiration.

A Three-Stage Inter-Channel Calibration Approach for Passive Radar on Moving Platforms Exploiting the Minimum Variance Power Spectrum.

Research in passive radar has moved its focus towards passive radar on moving platforms in recent years with the purpose of moving target indication and ground imaging via synthetic aperture radar. This is also fostered by the progress in hardware miniaturization, which alleviates the installation of the required hardware on moving platforms. Terrestrial transmitters, commonly known as illuminators of opportunity in the passive radar community, usually emit the signals in the Very High Frequency (VHF) or Ultra High Frequency (UHF) band. Due to the long wavelengths of the VHF/UHF band, there are constraints on the size of the used antenna elements, and therefore, the number of antenna elements to be employed is limited, especially as the platform carrying the passive radar system is intended to be small, potentially even an unmanned aerial vehicle. In order to detect moving targets hidden by Doppler shifted clutter returns, one common approach is to suppress the clutter returns by applying clutter suppression techniques that rely on spatial and temporal degrees of freedom, such as Displaced Phase Center Antenna (DPCA) or Space-Time Adaptive Processing. It has been shown that the DPCA approach is a meaningful technique to suppress the clutter if two antenna elements are employed. However, if the employed receiving channels are not carefully calibrated, the clutter suppression is shown to be not effective. Here, we suggest a three-stage calibration technique in order to perform the calibration of two receiving channels, which involves the exploitation of the direct signal, a data-adaptive amplitude calibration, and finally, a data-adaptive calibration of phase mismatches between both receiving channels by the estimation of the Minimum Variance Power Spectrum of the clutter. The validity of the proposed approach is shown with simulated data and demonstrated on real data from a fast ground moving platform, showing improved clutter cancellation capabilities.

Blazar variability power spectra from radio up to TeV photon energies: Mrk 421 and PKS 2155−304

ABSTRACT We present the results of the power spectral density (PSD) analysis for the blazars Mrk 421 and PKS 2155−304, using good-quality, densely sampled light curves at multiple frequencies, covering 17 decades of the electromagnetic spectrum, and variability time-scales from weeks up to a decade. The data were collected from publicly available archives of observatories at radio from Owens Valley Radio Observatory, optical and infrared (B, V, R, I, J, H, and Kbands), X-rays from the Swift and the Rossi X-ray Timing Explorer, high and very high energy (VHE) γ-rays from the Fermi and Very Energetic Radiation Imaging Telescope Array System as well as the High Energy Stereoscopic System. Our results are: (1) the power-law form of the variability power spectra at radio, infrared, and optical frequencies have slopes ∼1.8, indicative of random-walk-type noise processes; (2) the power-law form of the variability power spectra at higher frequencies, from X-rays to VHE γ-rays, however, have slopes ∼1.2, suggesting a flicker noise-type process; and (3) there is significantly more variability power at X-rays, high and VHE γ-rays on time-scales ≲ 100 d, as compared to lower energies. Our results do not easily fit into a simple model, in which a single compact emission zone is dominating the radiative output of the blazars across all the time-scales probed in our analysis. Instead, we argue that the frequency-dependent shape of the variability power spectra points out a more complex picture, with highly inhomogeneous outflow producing non-thermal emission over an extended, stratified volume.