Frequency Separation Research Articles

Optical absorption of conduction electrons in semiconductor nanowires in the presence of the electron–phonon interaction

We calculate the energy states and the optical absorption coefficient for electrons in a nanowire in the presence of the Rashba and the longitudinal-optical phonon interactions. The interplay of those interactions results in a splitting in the electron dispersion relation at zero wavevector that grows linearly for the ground state as the strength of the lateral quantum confinement increases. For higher states, the energy splitting increases more rapidly till the state of resonant polaron is reached, then it increases slowly due to the pinning effect. The frequency separation between the well-resolved absorption peaks and their number are greatly influenced by the state of the polarons.

On the Effect of Frequency Separation, Mass Ratio, Solidity, and Aerodynamic Resonances in Coupled Mode Flutter of a Linear Compressor Cascade

Abstract At a low mass ratio of structure to air, the work-per-cycle approach, or better known as the energy method, will lead to nonconservative results as aerodynamic coupling of modeshapes acts destabilizing. Using the p–k method to solve the aeroelastic stability equation, the effects of various structural aspects are investigated for a two-dimensional compressor cascade in subsonic and transonic flow conditions. The investigated key parameters are frequency separation, mass ratio, and solidity. Furthermore, the effect of a high frequency dependency of the aerodynamic forces is presented. Such phenomena can happen in case of aerodynamic or acoustic resonances. If the resonance peaks are close to the aeroelastic frequency, a discontinuous behavior of the frequency or damping solution can lead to a rapid destabilization of the system, once the aeroelastic frequency moves from one side to the other of the peak. In these regimes, it is crucial to have a high quality representation of the frequency-dependent generalized aerodynamic forces (GAFs) for an accurate prediction of the flutter onset.

Short-time Fourier transform and embedding method for recurrence quantification analysis of EEG time series

Electroencephalography (EEG) allows recording of cortical activity at high temporal resolution. Creating features useful for the analysis of the EEG recording can be challenging. Here we introduce a new method of pre-processing the time-series for the analysis of the resting state and binary task classification using recurrence quantification analysis (RQA) and compare it with the existing state-of-the-art approach based on signal embedding. To reveal patterns that unfold brain dynamics, we present a new pipeline that does not rely on selection of embedding parameters for RQA. Instead of using EEG time-series signals directly, Short-term Fourier transform (STFT) is used to generate new time-series, based on the power spectra from sliding, overlapping windows. Recurrence plots are created in a standard way from embedded EEG signals, and the STFT vectors. The efficiency of RQA features extracted from such plots is compared in classification of EEG segments that correspond to open and closed eye conditions. In contrast to the common approaches to such analysis, no filtering into separate frequency bands was needed. Differences between the two representations of EEG signals are illustrated using histograms of RQA features and UMAP plots. Classification results at the 95.9% level were obtained using selected features for less than 10 electrodes.

A Novel Approach to Classify Telescopic Sensors Data Using Bidirectional-Gated Recurrent Neural Networks

Asteroseismology studies the physical structure of stars by analyzing their solar-type oscillations as seismic waves and frequency spectra. The physical processes in stars and oscillations are similar to the Sun, which is more evolved to the red-giant branch (RGB), representing the Sun’s future. In stellar astrophysics, the RGB is a crucial problem to determine. An RGB is formed when a star expands and fuses all the hydrogen in its core into helium which starts burning, resulting in helium burning (HeB). According to a recent state by NASA Kepler mission, 7000 HeB and RGB were observed. A study based on an advanced system needs to be implemented to classify RGB and HeB, which helps astronomers. The main aim of this research study is to classify the RGB and HeB in asteroseismology using a deep learning approach. Novel bidirectional-gated recurrent units and a recurrent neural network (BiGR)-based deep learning approach are proposed. The proposed model achieved a 93% accuracy score for asteroseismology classification. The proposed technique outperforms other state-of-the-art studies. The analyzed fundamental properties of RGB and HeB are based on the frequency separation of modes in consecutive order with the same degree, maximum oscillation power frequency, and mode location. Asteroseismology Exploratory Data Analysis (AEDA) is applied to find critical fundamental parameters and patterns that accurately infer from the asteroseismology dataset. Our key findings from the research are based on a novel classification model and analysis of root causes for the formation of HeB and RGB. The study analysis identified that the cause of HeB increases when the value of feature Numax is high and feature Epsilon is low. Our research study helps astronomers and space star oscillations analyzers meet their astronomy findings.

An all-digital CMOS temperature sensor with a wide supply voltage range

This paper proposes a MOSFET-based all-digital temperature sensor fabricated in a standard 55-nm CMOS process. The temperature sensing elements of the sensor are composed of ring oscillators, which convert temperature information into frequency information. The frequency ratio’s proportional to absolute temperature (PTAT) feature is generated by using two separate frequency oscillators with varied temperature sensitivity. The frequency-to-digital converter (FDC) converts frequency information into digital representation without introducing any overhead reference clock. A die area of 1915µm2 is occupied, owing to the all-digital architecture. After two-point calibration, the proposed sensor achieves an error of -0.4°C∼+0.6°C throughout a temperature range of -40°C∼125°C. With the help of class-adjustable oscillators, the sensor can function in a wide supply voltage range from 0.5V to 1.2V. It obtains a resolution of 0.166°C at room temperature with a dissipation of 2.5µW.

Explaining the deterioration of the relative timing accuracy for across-channel by a simple mathematical model

The perceptual simultaneity range, within which two asynchronous pure tones are perceived to start simultaneously, and the gap detection threshold are known to be wide when the frequency separation of the tones is large. It is generally said that the accuracy of the relative timing for different frequency channels deteriorates. However, there is no clear explanation of why such deteriorations are necessary. This study aimed to show that a simple mathematical model leads to the deterioration of relative timing accuracy for two tones with different frequencies. As a result of the calculations, the model simulated the deterioration of the perceptual simultaneity range not only with the increase of the frequency separation but also with the decrease of the frequency region of two tones. The model also simulated the behavior of the gap detection threshold for two different frequencies (across-channel) with its asymmetric deterioration. Further, the model simulated the behavior of the gap detection threshold for two identical frequencies (within-channel). These results suggest that one simple mathematical model may explain the mechanisms underlying perceptual simultaneity, within-channel gap detection, and between-channel gap detection for two tones.

KIC 3440495: A Rapidly Rotating δ Scuti-γ Doradus Hybrid Pulsator in a Binary System

In this paper, we study the pulsation properties of KIC 3440495 using Kepler and TESS data. A Fourier analysis of the light curve reveals 24 pulsation modes as well as 29 frequencies associated with rotation. The rotation frequency is derived to be f rot = 2.322909(2) day−1, and the rotational modulation is determined to be caused by starspots. A large frequency separation of Δν = 54.5 μHz is found by using a Fourier transform, the autocorrelation function, a histogram of frequency differences, and an échelle diagram. We use the large separation to estimate the refined stellar parameters of the star to be v = [239, 279] km s−1, M = [1.5, 1.65] M ⊙, R equator = [2.03, 2.30] R ⊙, R polar = [1.72, 1.78] R ⊙, and ω = [0.61, 0.77]. The phase modulations of the pulsating frequencies show a long-term trend which may be attributed to an orbital effect of a binary system; hence, the star may be a fast rotating pulsator in a binary system. KIC 3440495 has an amplitude spectrum similar to Altair, and is identified as a potential sister of Altair. Based on studies of Altair, KIC 3330495 is presumably a young star at a similar evolutionary stage.

Mathematical Model of an Antenna-Waveguide Path with Separation of Signals by Frequency–Polarization

Introduction. The creation of antenna-waveguide paths of multi-band mirror antennas (AWP MMA) is a significant task in the development of antenna-feeder devices for satellite communication systems (SSS). This task involves the construction of an adequate mathematical model of AWP MMA both without and with the implementation of an auto-tracking function built using the "frequency separation – polarization separation" method. However, the existing mathematical models have been developed only for specific AWP MMA types, thus making them unsuitable for the development of new AWP MMA. The model proposed in this paper can be used for an arbitrary number of combined frequency ranges and types of polarization.Aim. Development of a mathematical model of the AWP MMA of SSS both without and with the implementation of an auto-tracking function built using the "frequency separation – polarization separation" method.Materials and methods. The mathematical model under consideration assumes a description of the AWP MMA using block matrices. Each of these matrices describes the complex amplitudes of signals arising in each of the AWP MMA devices. This, in turn, makes it possible to analyze the influence of the parameters of each device on the characteristics of the AWP MMA of SSS as a whole with an arbitrary number of combined frequency ranges and types of polarization.Results. Two options for the construction of AWP MMA of SSS are proposed. The first option can be used in communication system antennas with software support, while the second option is applicable when a monopulse tracking method is implemented. To construct an AWP MMA model, it is proposed to use a matrix description of the characteristics of AWP MMA devices. This allows the structure of the considered AWP MMA to be varied within a wide range.Conclusion. The developed mathematical model makes it possible to describe the characteristics of each of the devices in the AWP MMA system using a certain multipole. The proposed model provides ample opportunities for controlling, at the stages of development, production and debugging, not only the characteristics of each device in the AWP MMA, but also the transmission coefficient and polarization isolation in each frequency range of the entire AWP MMA. The presented dependencies can be used to assess the relationship between parameter tolerances and the limits of changes in the characteristics of the motor vehicle.

Investigation on the reconstruction of wave bimodal spectrum in the lagoon near islands and reefs

Due to the intricate topography and geomorphology of coral reefs, waves propagating from deep water areas to transitional or shallow water near islands and reefs will exhibit features of wave spectra that are very different from those in the deep sea. Thus, a reconstruction of the wave spectra is necessary. In this study, double Gaussian functions are first proposed to identify the characteristic frequencies of wave bimodal spectra, such as peak frequencies corresponding to the low frequency part and high frequency part, and separation frequencies differentiating between the low frequency part and the high frequency part, based on the observed data of wave spectra in the lagoon near islands and reefs of the South China Sea (SCS). The wave bimodal spectra close to the islands and reefs are then rebuilt using the Ochi-Hubble spectrum type. The high frequency and low frequency portions of the bimodal wave spectra are used to determine the significant wave heights, peak frequency and shape characteristics, respectively. The wave motions exhibit basically linear characteristics when two typical sea conditions, such as summer typhoon waves and winter Northeast monsoon waves, are investigated in detail. The superposition of wind waves and swells on the one hand, and the presence of the bottom on the other, have an impact on the generation of the bi-modal spectrum. The bi-modal spectra that were reconstructed and those that were observed have a correlation coefficient that is greater than 90%. The study on the reconstruction of the bimodal spectrum in the paper will provide a reference for the description of the bimodal spectrum near islands and reefs.

Demixing Sines and Spikes Using Multiple Measurement Vectors

We address the line spectral estimation problem with multiple measurement corrupted vectors. Such scenarios appear in many practical applications such as radar, optics, and seismic imaging in which the measurements can be modeled as the sum of a spectrally sparse and a block-sparse signal known as outlier. Our aim is to demix the two components and for this purpose, we design a convex problem whose objective function promotes both of the structures. Using the Positive Trigonometric Polynomials (PTP) theory, we reformulate the dual problem as a Semidefinite Program (SDP). Our theoretical results state that for a fixed number of measurements N and constant number of outliers, up to O(N) spectral lines can be recovered using our SDP problem as long as a minimum frequency separation condition is satisfied. Our simulation results also show that increasing the number of samples per measurement vectors reduces the minimum required frequency separation for successful recovery.

Single-frequency fiber Fabry-Perot Brillouin laser.

We demonstrate single-frequency stimulated Brillouin lasing in short fiber Fabry-Perot resonators. A sub-milliwatt threshold for lasing is observed in resonators with high quality factors of ∼1.5 × 108 and effective resonator lengths as short as ∼5 mm. The strong dispersion of fiber Bragg gratings results in unequal frequency separations for neighboring pairs of longitudinal modes with separation differences larger than the Brillouin gain bandwidth, thereby avoiding cascaded lasing. Our achievement will enable compact, robust, efficient narrow-linewidth light sources.

EA-Net: Edge-aware network for brain structure segmentation via decoupled high and low frequency features

Automatic brain structure segmentation in Magnetic Resonance Image (MRI) plays an important role in the diagnosis of various neuropsychiatric diseases. However, most existing methods yield unsatisfactory results due to blurred boundaries and complex structures. Improving the segmentation ability requires the model to be explicit about the spatial localization and shape appearance of targets, which correspond to the low-frequency content features and the high-frequency edge features, respectively. Therefore, in this paper, to extract rich edge and content feature representations, we focus on the composition of the feature and utilize a frequency decoupling (FD) block to separate the low-frequency and high-frequency parts of the feature. Further, a novel edge-aware network (EA-Net) is proposed for jointly learning to segment brain structures and detect object edges. First, an encoder–decoder sub-network is utilized to obtain multi-level information from the input MRI, which is then sent to the FD block to complete the frequency separation. Further, we use different mechanisms to optimize both the low-frequency and high-frequency features. Finally, these two parts are fused to generate the final prediction. In particular, we extract the content mask and the edge mask from the optimization feature with different supervisions, which forces the network to learn the boundary features of the object. Extensive experiments are performed on two public brain MRI T1 scan datasets (the IBSR dataset and the MALC dataset) to evaluate the effectiveness of the proposed algorithm. The experiments show that the EA-Net achieves the best performance compared with the state-of-the-art methods, and improves the segmentation DSC score by 1.31% at most compared with the U-Net model and its variants. Moreover, we evaluate the EA-Net under different noise disturbances, and the results demonstrate the robustness and superiority of our method under low-quality noisy MRI. Code is available at https://github.com/huqian999/EA-Net.

Photonic microwave frequency divider with a tunable division ratio and harmonic suppression capability

A photonic microwave frequency divider that is capable to realise tunable high order frequency division, is presented. It is based on injecting an RF phase modulated optical signal into an off-the-shelf DFB laser operating at period-N state. Optical frequency components with a frequency separation of 1/N times the input RF signal frequency are generated by the DFB laser. An optical bandpass filter can be employed to select two optical frequency components to be detected by a photodetector to obtain a divide-by-N RF signal without harmonic components. The proposed frequency divider can be operated over a wide frequency range and has high reconfigurability as it is free of electrical components. Experimental results demonstrate the realisation of frequency division operation with a tunable 1/2 to 1/5 division ratio for different input RF signal frequencies of 8 to 20 GHz by adjusting the DFB laser forward bias current. Over 35 dB harmonic component suppression is demonstrated. A proof-of-concept experiment is also set up to show the frequency divider based on an optically injected semiconductor laser is capable to operate at a high input RF signal frequency of 50 GHz and has a tunable high order division ratio of 1/2 to 1/8.

Lightweight soundproofing meta-panel for separate wide frequency bands

We propose a lightweight soundproofing meta-panel that suppresses noise in separate wide frequency bands. The meta-panel has a multi-scale lattice structure sandwiched by two thin membranes. High sound isolation over a wide frequency range is achieved by inducing negative effective material properties of the meta-panel. Unlike a single-scale lattice structure, in which total transmission is unavoidable at certain frequencies due to resonances of the membranes, the meta-panel isolates sound waves effectively in separate wide bands with the aid of multiple reflections within the multi-scale lattice structure. A sound transmission loss exceeding 16.7 dB was realized within the range 100–1750 Hz by a meta-panel sample fabricated via three-dimensional printing. Aiming at practical applications in electric cars, we evaluated the insertion loss of the meta-panel in a box-shaped structure for dual-band noise which consists of road noise (100–400 Hz) and motor noise (1050–1350 Hz) recorded from an actual electric car. The proposed meta-panel had an overall sound pressure level reduction of about 19 dB for the given dual-band noise with a small areal density of 1.51 kg/m2, which is 1/20 times lighter than a steel plate with an equivalent reduction level.

Low-Complexity Acoustic Scene Classification Using Time Frequency Separable Convolution

Replacing 2D-convolution operations by depth-wise separable time and frequency convolutions greatly reduces the number of parameters while maintaining nearly equivalent performances in the context of acoustic scene classification. In our experiments, the models’ sizes can be reduced by 6 to 14 times with similar performances. For a 3-class audio classification, replacing 2D-convolution in a CNN model gives roughly a 2% increase in accuracy. In a 10-class audio classification with multiple recording devices, replacing 2D-convolution in Resnet only reduces around 1.5% of the accuracy.

The role of temporal coherence and temporal predictability in the build-up of auditory grouping

The cochlea decomposes sounds into separate frequency channels, from which the auditory brain must reconstruct the auditory scene. To do this the auditory system must make decisions about which frequency information should be grouped together, and which should remain distinct. Two key cues for grouping are temporal coherence, resulting from coherent changes in power across frequency, and temporal predictability, resulting from regular or predictable changes over time. To test how these cues contribute to the construction of a sound scene we present listeners with a range of precursor sounds, which act to prime the auditory system by providing information about each sounds structure, followed by a fixed masker in which participants were required to detect the presence of an embedded tone. By manipulating temporal coherence and/or temporal predictability in the precursor we assess how prior sound exposure influences subsequent auditory grouping. In Experiment 1, we measure the contribution of temporal predictability by presenting temporally regular or jittered precursors, and temporal coherence by using either narrow or broadband sounds, demonstrating that both independently contribute to masking/unmasking. In Experiment 2, we measure the relative impact of temporal coherence and temporal predictability and ask whether the influence of each in the precursor signifies an enhancement or interference of unmasking. We observed that interfering precursors produced the largest changes to thresholds.

Spin-wave nonreciprocity and formation of lateral standing spin waves in CoFeB/Ta/NiFe meander-shaped films

Studying the spin-wave (SW) propagation in 3D periodic structures opens new possibilities for joining functional units placed on the different layers of the magnonic circuitry. In the path toward 3D magnonics, the main challenge is the fabrication of large-scale 3D magnetic structures with nanometric precision control of geometry and material composition. In this work, we study the dependence on the Ta spacer thickness of the magnonic band structure, measured by Brillouin light scattering spectroscopy, of CoFeB/Ta/NiFe meander-shaped bilayers fabricated on pre-patterned Si substrate with thickness steps of 50 nm. Both propagating and stationary SW modes are observed. While the frequency of the dispersive mode slightly depends on the Ta spacer thickness, the frequency position of the three stationary modes in the lowest frequency range of the spectra significantly increases by increasing the Ta thickness. Micromagnetic calculations indicate that each of the three stationary modes is composed of a doublet of modes whose frequency separation, within each doublet, increases by increasing the mode frequency. The origin of this frequency separation is ascribed to the dynamic dipolar coupling between the magnetic layers that generate a significant frequency nonreciprocity of counterpropagating SWs. For these reasons, the investigated structures offer potential application as the nonreciprocal versatile interconnections performing the frequency selective regimes of signal propagation in magnonic circuits.

Is Bianchi I a bouncing cosmology in the Wheeler-DeWitt picture?

We provide a quantum picture for the emergence of a bouncing cosmology, according to the idea that a semiclassical behavior of the Universe towards the singularity is not available in many relevant Minisuperspace models. In particular, we study the Bianchi I model in vacuum adopting the isotropic Misner variable as an internal clock for the quantum evolution. The isomorphism between the Wheeler-DeWitt equation in this Minisuperspace representation and the Klein-Gordon one for a relativistic scalar field allows to identify the positive and negative frequency solutions as associated to the collapsing and expanding Universe respectively. We clarify how any Bianchi I localized wave packet unavoidably spreads when the singularity is approached and therefore the semiclassical description of the model evolution in the Planckian region loses its predictability. Then, we calculate the transition amplitude that a collapsing Universe is turned into an expanding one, according to the standard techniques of relativistic quantum mechanics, thanks to the introduction of an ekpyrotic-like matter component which mimics a time-dependent potential term and breaks the frequency separation. In particular, the transition probability of this "Quantum Big Bounce" acquires a maximum value when the mean values of the momenta conjugate to the anisotropies in the collapsing Universe are close enough to the corresponding mean values in the expanding one, depending on the variances of the in-going and out-going Universe wave packets. This symmetry between the pre-Bounce and post-Bounce mean values reflects what happens in the semiclassical bouncing cosmology, with the difference that here the connection of the two branches takes place on a pure probabilistic level.

Electrochemical Impedance Characteristics of a Low-Temperature Single Cell for CO2/H2O Co-Reduction to Produce Syngas (CO+H2)

In this study, the electrochemical impedance characteristics of CO2/H2O co-reduction to produce CO/H2 syngas were investigated in a low-temperature single cell. The effect of the operating conditions on the single-cell performance was evaluated at different feed concentrations and cell voltages, and the corresponding electrochemical impedance spectroscopy (EIS) data were collected and analyzed. The Nyquist plots exhibited two semicircles with separated characteristic frequencies of approximately 1 kHz and tens of Hz. The high-frequency semicircles, which depend only on the catholyte concentration, could be correlated to the charge transfer processes in competitive CO2 reduction and hydrogen evolution reactions at the cathodes. The EIS characteristics of the CO2/H2O co-reduction single cell could be explained by the equivalent circuit suggested in this study. In this circuit, the cathodic mass transfer and anodic charge transfer processes are collectively represented by a parallel combination of resistance and a constant phase element to show low-frequency semicircles. Through nonlinear fitting using the equivalent circuit, the parameters for each electrochemical element, such as polarization resistances for high- and low-frequency processes, could be quantified as functions of feed concentration and cell voltage.

Extension of the Asfgrid for Correcting Asteroseismic Large Frequency Separations

The asteroseismic scaling relation, Δν ≈ ρ 0.5, linking a star’s large frequency separation, Δν, and its mean density, ρ, is not exact. Yet, it provides a very useful way to obtain fundamental stellar properties. Common ways to make the relation more accurate is to apply correction factors to it. Because the corrections depend on stellar properties, such as mass, T eff, and metallicity, it is customary to interpolate these properties over stellar model grids that include both Δν, measured from adiabatic frequencies of the models, and the models’ stellar density; hence linking both sides of the scaling relation. A grid and interpolation tool widely used for this purpose, known as Asfgrid, was published by Sharma & Stello. Here, we present a significant extension of Asfgrid to cover higher- and lower-mass stars and to increase the density of grid points, especially in the low-metallicity regime.