Spectral Density Profile Research Articles

Dynamic control of cascaded four-wave mixing via re-configurable dispersion.

We integrate a spatial light modulator-based dispersion controller into a cascaded four-wave mixing (CFWM) system. By tuning the group delay dispersion (GDD) and fourth-order dispersion (FOD) terms, we control the CFWM phase matching and demonstrate an output bandwidth tuning of over 3.3×. At the maximum bandwidth, our system covers the telecommunications S-, C-, and L-bands (1466-1641 nm) with an average output power of 300 mW, which is contained in 52 individual lines spaced 374 GHz apart. This method represents a reconfigurable alternative to photonic crystal fibers for dispersion engineering and allows for the use of step-index fiber and customizable power spectral density (PSD) profiles.

Seismic noise in South China Sea: High-quality time-frequency analysis from 0.01 to 125 Hz.

An efficient and precise time-frequency analysis method for real-time ocean bottom seismometer (RTOBS) data in the South China Sea (SCS) is presented. Overcoming the limitations of conventional methods, the method involves temporal segmentation, unique frequency octaves, and Fourier transforms to generate power spectral density (PSD) and probability density function profiles. The method demonstrates superior precision, computational efficiency, and full-bandwidth (0 to Nyquist) capability compared to traditional techniques, as validated through theoretical and empirical evaluations. Applied to SCS RTOBS data, it unveils temporal PSD variations, shedding light on underwater noise sources like earthquakes, offshore blasting, ship-induced disturbances, and tidal effects. Establishing background noise levels in the SCS supports noise source categorization and ocean environment monitoring. Furthermore, comparing onshore and offshore seismic stations advances interdisciplinary research, fostering a comprehensive understanding of acoustics and seismology in the region.

In-silico testing of new pharmacology for restoring inhibition and human cortical function in depression

Reduced inhibition by somatostatin-expressing interneurons is associated with depression. Administration of positive allosteric modulators of α5 subunit-containing GABAA receptor (α5-PAM) that selectively target this lost inhibition exhibit antidepressant and pro-cognitive effects in rodent models of chronic stress. However, the functional effects of α5-PAM on the human brain in vivo are unknown, and currently cannot be assessed experimentally. We modeled the effects of α5-PAM on tonic inhibition as measured in human neurons, and tested in silico α5-PAM effects on detailed models of human cortical microcircuits in health and depression. We found that α5-PAM effectively recovered impaired cortical processing as quantified by stimulus detection metrics, and also recovered the power spectral density profile of the microcircuit EEG signals. We performed an α5-PAM dose-response and identified simulated EEG biomarker candidates. Our results serve to de-risk and facilitate α5-PAM translation and provide biomarkers in non-invasive brain signals for monitoring target engagement and drug efficacy.

Study on Linewidth and Phase Noise Characteristics of a Narrow Linewidth External Cavity Diode Laser.

In the field of inter-satellite laser communication, achieving high-quality communication and compensating for the Doppler frequency shift caused by relative motion necessitate lasers with narrow linewidths, low phase noise, and the ability to achieve mode-hop-free tuning within a specific range. To this end, this paper investigates a novel external cavity diode laser (ECDL) with a frequency-selective F-P etalon structure, leveraging the external cavity F-P etalon structure in conjunction with an auxiliary filter to achieve single longitudinal mode selection. The laser undergoes linewidth testing using a delayed self-heterodyne beating method, followed by the testing of its phase noise and frequency noise characteristics using a noise analyzer, yielding beat spectra and noise power spectral density profiles. Furthermore, the paper introduces an innovative bidirectional temperature-scanning laser method to achieve optimal laser-operating point selection and mode-hop-free tuning. The experimental results showcase that the single longitudinal mode spectral side-mode suppression ratio (SMSR) is around 70 dB, and the output power exceeds 10 mW. Enhancing the precision of the F-P etalon leads to a more pronounced suppression of low-frequency phase noise, reducing the Lorentzian linewidth from the initial 10 kHz level to a remarkable 5 kHz level. The bidirectional temperature-scanning laser method not only allows for the selection of the optimal operating point but also enables mode-hop-free tuning within 160 pm.

Frequency-specific functional difference between gyri and sulci in naturalistic paradigm fMRI.

Disentangling functional difference between cortical folding patterns of gyri and sulci provides novel insights into the relationship between brain structure and function. Previous studies using resting-state functional magnetic resonance imaging (rsfMRI) have revealed that sulcal signals exhibit stronger high-frequency but weaker low-frequency components compared to gyral ones, suggesting that gyri may serve as functional integration centers while sulci are segregated local processing units. In this study, we utilize naturalistic paradigm fMRI (nfMRI) to explore the functional difference between gyri and sulci as it has proven to record stronger functional integrations compared to rsfMRI. We adopt a convolutional neural network (CNN) to classify gyral and sulcal fMRI signals in the whole brain (the global model) and within functional brain networks (the local models). The frequency-specific difference between gyri and sulci is then inferred from the power spectral density (PSD) profiles of the learned filters in the CNN model. Our experimental results show that nfMRI shows higher gyral-sulcal PSD contrast effect sizes in the global model compared to rsfMRI. In the local models, the effect sizes are either increased or decreased depending on frequency bands and functional complexity of the FBNs. This study highlights the advantages of nfMRI in depicting the functional difference between gyri and sulci, and provides novel insights into unraveling the relationship between brain structure and function.

Coronal height constraint in IRAS 13224–3809 and 1H 0707–495 by the random forest regressor

ABSTRACT We develop a random forest regressor (RFR) machine learning model to trace the coronal evolution in two highly variable active galactic nuclei (AGNs) IRAS 13224-3809 and 1H 0707-495 observed with XMM–Newton, by probing the X-ray reverberation features imprinted on their power spectral density (PSD) profiles. Simulated PSDs in the form of a power law, with a similar frequency range and bins to the observed data, are produced. Then, they are convolved with relativistic disc-response functions from a lamp-post source before being used to train and test the model to predict the coronal height. We remove some bins that are dominated by Poisson noise and find that the model can tolerate the frequency-bin removal up to ∼10 bins to maintain a prediction accuracy of R2 > 0.9. The black hole mass and inclination should be fixed so that the accuracy in predicting the source height is still >0.9. The accuracy also increases with the reflection fraction. The corona heights for both AGN are then predicted using the RFR model developed from the simulated PSDs, whose frequency range and bins are specifically adjusted to match those from each individual observation. The model suggests that their corona varies between ∼5–18 rg, with R2 > 0.9 for all observations. Such high accuracy can still be obtained if the difference between the true mass and the trained value is ${\lesssim}10\ \hbox{per cent}$. Finally, the model supports the height-changing corona under the light-bending scenario, where the height is correlated to source luminosity in both IRAS 13224-3809 and 1H 0707-495.

Generation of entangled-photons by a quantum dot cascade source in polarized cavities: Using cavity resonances to boost signals and preserve the entanglements.

Motivated by recent advances in the development of single photon emitters for quantum information sciences, here we design and formulate a quantum cascade model that describes cascade emission by a quantum dot (QD) in a cavity structure while preserving entanglement that stores information needed for single photon emission. The theoretical approach is based on a photonic structure that consists of two orthogonal cavities in which resonance with either the first or second of the two emitted photons is possible, leading to amplification and rerouting of the entangled light. The cavity-QD scheme uses a four-level cascade emitter that involves three levels for each polarization, leading to two spatially entangled photons for each polarization. By solving the Schrodinger equation, we identify the characteristic properties of the system, which can be used in conjunction with optimization techniques to achieve the "best" design relative to a set of prioritized criteria or constraints in our optical system. The theoretical investigations include an analysis of emission spectra in addition to the joint spectral density profile, and the results demonstrate the ability of the cavities to act as frequency filters for the photons that make up the entanglements and to modify entanglement properties. The results provide new opportunities for the experimental design and engineering of on-demand single photon sources.

Measurement and analysis of truck vibration levels in logistic Spain distribution to simulate package testing

AbstractThe aim of this study was to measure the vibration levels in one of the types of truck most used in Spain for the shipment of packaged goods, formed by tractor unit and air‐suspension semi‐trailer with 26 tonnes (26 000 kg) payload capacity, considering the most representative routes of the main Spanish road network. The data presented in this study will enable the development of new specific vibration tests and will help product and package engineers to reduce damage in transit. In this study, 30 transport routes recording nearly 10 000 km of the Spanish main road network have been selected and analysed, and power spectral density (PSD) profiles are provided to simulate truck transport in Spain using random vibration test methods. The resulting PSD profiles were established by generating two grms levels (0.21 and 0.15) obtaining the highest intensity from the calculation of the upper one‐sided normal tolerance limit (NTL) (30,95,50) and an average intensity profile at −6 dB with respect to the calculated NTL curve, which represents 70% of the lowest grms values of the study. This study uses NTL analysis to explore the vibration characteristics of a typical heavy goods transport vehicle type for various routes along main highways in Spain and propose new transport simulation test protocols dedicated to the Spanish main road distribution environment.

Fourier Analysis of Magnetic Fields in the Ionosphere of Mars

AbstractThe two main sources of the magnetic field in the Martian ionosphere are the solar wind interaction with the planet, and, mainly in the southern hemisphere, remnant crustal magnetization. The magnetic fields measured by the Mars Atmosphere and Volatile EvolutioN (MAVEN) and Mars Global Surveyor spacecraft displayed a wide range of spatial scales, from the global (i.e., L ≈ 103 km) to mesoscale (L ≈ 102 km) to small‐scale (L < 10 km). Hamil et al. (2022) used MAVEN magnetometer and Langmuir Probe data to study these structures and suggested that they might be advected into the ionosphere from the solar wind and magnetosheath. In the current study, we apply a Fourier analysis to the fields and interpret the resulting power spectral density profiles versus frequency. The power spectral density function found from MAVEN data resembles that of the solar wind magnetic field (or interplanetary magnetic field) (i.e., power law with an index of about −2), but shifted upward in frequency by a factor of about 100. From a comparison of ionospheric power spectra with solar wind power spectra, we deduce that plasma, carrying a magnetic field with it moves from the magnetic pile‐up region downward into the ionosphere with speeds of roughly tens of meters per second. The derived power spectra in the ionosphere, in addition to the basic power law shape, show hints of extra power at a spatial scale of about 10 km, and this might be due to the creation of a magnetic structure within the ionosphere itself.

Signatures of natural selection in tree topology shape of serially sampled viral phylogenies

Tree shape metrics can be computed fast for trees of any size, which makes them promising alternatives to intensive statistical methods and parameter-rich evolutionary models in the era of massive data availability. Previous studies have demonstrated their effectiveness in unveiling important parameters in viral evolutionary dynamics, although the impact of natural selection on the shape of tree topologies has not been thoroughly investigated. We carried out a forward-time and individual-based simulation to investigate whether tree shape metrics of several kinds could predict the selection regime employed to generate the data. To examine the impact of the genetic diversity of the founder viral population, simulations were run under two opposing starting configurations of the genetic diversity of the infecting viral population. We found that four evolutionary regimes, namely, negative, positive, and frequency-dependent selection, as well as neutral evolution, were successfully distinguished by tree topology shape metrics. Two metrics from the Laplacian spectral density profile (principal eigenvalue and peakedness) and the number of cherries were the most informative for indicating selection type. The genetic diversity of the founder population had an impact on differentiating evolutionary scenarios. Tree imbalance, which has been frequently associated with the action of natural selection on intrahost viral diversity, was also characteristic of neutrally evolving serially sampled data. Metrics calculated from empirical analysis of HIV datasets indicated that most tree topologies exhibited shapes closer to the frequency-dependent selection or neutral evolution regimes.

Feature Identification and Statistical Characteristics of Quasi-periodic Pulsation in Solar Flares using the Markov-Chain-Monte-Carlo Approach

Quasi-periodic pulsation (QPP) is a common phenomenon in solar flares. Studying QPP is important to further our understanding of the physical processes operating in flares. However, detection of QPP is complicated by the presence of noise in flaring lightcurves. In this study, we apply the Bayesian-based Markov-Chain-Monte-Carlo (MCMC) technique to the QPP detection. We use MCMC to fit the Fourier power spectral density (PSD) profiles of flaring lightcurves, aiming to determine a quasi-periodic component by model comparison and test statistics. Two models fitting the PSD were compared: the first model consists of colored and white noise only, and the second model adds a spectral peak of a Gaussian shape representing a short-living oscillatory signal. To evaluate MCMC of the QPP detection, we test it on 100 synthetic signals with spectral properties similar to those observed in flares. Subsequently, we analyzed QPP events in 699 flare signals in the 1–8 Å channel recorded by the Geostationary Operational Environmental Satellite from 2010 to 2017, including 250 B-class, 250 C-class, 150 M-class, and 49 X-class flares. Approximately 57% X-class, 39% M-class, 20% C-class, and 16% B-class flares are found to show a strong evidence of QPP, whose periods range mainly from 6.2 to 75.3 s. The results demonstrate that QPP events are easier to detect in more powerful flares. The distribution of the detected QPP periods is found to follow a logarithmic normal distribution. The distributions in the four flare classes are similar. This suggests that the established distribution is a common feature for flares of different classes.

Defining a vibration test profile for assessing the durability of electric motorcycle battery assemblies

There has been little published research critically examining the vibration loading that battery assemblies within large sized electric two wheelers (ETWs) experience during their lifetime. Much of the existing research has been focused on assessing the battery packs of electric passenger vehicles, which have a different dynamic response to their two wheeled counterparts. Existing automotive procedures, therefore, cannot be applied to these modes of transport. It is important therefore that the magnitude and frequency of the vibration inputs that the ETW battery will be exposed to during the vehicle's life is understood.For the first time, this study describes a methodology to derive random power spectral density (PSD) profiles that are representative of 60,000 miles of UK customer electric motorcycle (EM) usage for a vehicle operating in the large traditional motorcycle class. The derived PSDs are suitable for testing frame mounted batteries for mechanical durability using modern shaker table facilities and are derived utilising vibration measurements from a contemporary EM (Harley Davidson Livewire). In addition, it compares the measurements from a current production EM to that of profiles derived from passenger electric vehicles (EVs) published within existing studies to highlight the key differences between vibration environments experienced by batteries within passenger EVs and EMs.

Boosting Energy Storage of Poly(vinylidene difluoride) Nanocomposite Based Flexible Self-Standing Film with Low Amount of Hydroxylated V2O5

Polymer-ceramic based nanocomposite dielectric materials have become an attraction for researchers due to their lightweight and high dielectric breakdown strength as well as good dielectric properties. We have synthesized poly(vinylidene difluoride) (PVDF)/hydroxylated-V2O5 (Hy-V2O5) ferroelectric polymer nanocomposite self-standing film, with an average thickness of 0.07 ± 0.005 mm. The phase identification, surface analysis, and structural analysis were performed using differential scanning calorimetry, X-ray photoelectron spectroscopy analysis, and X-ray diffraction, respectively. The analysis of atomic force micrographs reveals lower surface roughness of the nanocomposite films and confirms that the film is suitable for energy storage rather than charge transport with the help of the isotropic power spectral density (PSD) profile. The loading of a low amount of Hy-V2O5 filler in PVDF significantly enhances the ferroelectric polarization, making it highly suitable for high energy storage applications. Enhancement of the dielectric constant (from ∼9 to 29.86) and polarization (Pmax for PVDF = 0.86 μC/cm2 to Pmax for PVDF/Hy-V2O5 = 2.7 μC/cm2 at the 1000 kV/cm field) is obtained. The energy density for the nanocomposite increased to 220% of that of the pure PVDF. Due to the low amount of filler, there is no substantial reduction in the dielectric breakdown strength of the nanocomposite, which is maintained at 1766.93 kV/cm.

Low-Noise Optical Accelerometers: Bridging the Gaps among Geophones, Accelerometers, and Broadbands in a Deep Borehole

Abstract Earthquakes and other seismic sources produce waves with frequency content spanning many orders of magnitude. Recording a broader frequency band of interest has historically required deploying multiple instruments designed to work the best within limited, overlapping frequency ranges. Here, we detail a 300 m deep borehole deployment of a sensor package, including three new optical accelerometers that can potentially replace many dedicated instruments with a single, low-noise sensor. These instruments are designed with a flat frequency response from 0.005 to 1500 Hz, spanning the flat response segments of broadband sensors and geophones, as well as a low-noise floor and high sensitivity. The sensors have been functioning normally for over four years, fully grouted at depths of >100 m. Year-long power spectral density (PSD) profiles show that the optical accelerometers have a lower noise floor than a colocated geophone for all frequencies, with 20 dB noise reduction at 250 Hz. PSD comparisons to a broadband sensor installed at the surface show a 5–30 dB noise reduction for the optical accelerometer above 1 Hz, although this is likely due, in part, to the broadband sensor being subjected to much higher surface noise. At periods >5 s, the broadband sensor shows up to 20 dB lower noise than the optical accelerometer, which in turn has up to 50 dB lower noise floor than the colocated geophone. Finally, modeling the Brune displacement spectrum for theoretical seismicity within 1 km of the borehole shows that the optical accelerometers could potentially deliver a detection threshold improvement of one magnitude unit relative to the colocated geophone.

X-ray intraday variability and power spectral density profiles of the blazar 3C 273 with XMM–Newton during 2000–2021

ABSTRACT We present X-ray intraday variability and power spectral density (PSD) analyses of the longest 23 pointed XMM–Newton observations of the blazar 3C 273 that were taken during 2000–2021. These good time intervals contain between 5 and 24.6 h of data. Variability has been estimated in three energy bands: 0.2–2 keV (soft), 2–10 keV (hard), and 0.2–10 keV (total). 9 of the 23 observations exhibited some variability, though no major variations exceeding 5 per cent were detected. Typical time-scales for variability were ∼1 ks. For those variable light curves, we find that a power-law model provides good fits to each PSD, with most of the slopes between −1.7 and −2.8. Although no variations of hardness ratio (HR) could be measured in any individual observation, an anticorrelation in flux and HR is found in long term data that indicates a harder when brighter trend. Our flux and spectral analyses indicate that both particle acceleration and synchrotron cooling processes make an important contribution to the emission from this blazar.

Anisotropic thermal transport in twisted bilayer graphene

Recently, twisted bilayer graphene (TBLG) has attracted enormous attention owing to its peculiar electronic properties. In this work, the anisotropic thermal conductivity of TBLG is comprehensively investigated. It is reported that interlayer twisting can be a practical approach for thermal transport regulation with high accuracy. A strong non-monotonic correlation between anisotropic thermal conductivity and twisting angles is revealed. Extensive phonon behavior analyses reveal the physical mechanism. The anisotropic thermal transport in TBLG is explained by the calculated phonon density of states (PDOS). Meanwhile, the phonon spectra and phonon relaxation times extracted from spectral energy density (SED) profiles explain the decreasing trend of thermal conductivity with increasing twisting angles. The increase in thermal conductivity is attributed to the combined effects of twist and anisotropy. The reported anisotropic thermal conductivity is important to the thermal modulation and our analyses provide a valuable complement to the phonon studies of TBLG.

Prediction of vibration induced damage in photovoltaic modules during transportation: finite element model and field study

The transportation of the photovoltaic (PV) modules involves excessive vibrations and shocks. These dynamic loads can crack the solar cells and glass of the PV modules. The cracks generated in solar cells during the transportation phase may not always have immediate implications on the electrical performance of the PV modules. However, in the long-run, cracks generated during transportation of the modules may propagate during operation in field due to wind load, snow load and thermal stresses. The propagation of cracks may create electrical isolation in the cells of a PV module, which can cause loss of electrical power. Therefore, it is important to minimize the damage in PV modules due to transportation and mechanical handling. In this work, PV modules have been transported in packaging following the industry practices to cover a distance of 270 km with accelerometers attached on several modules. Finite element (FE) modelling has been used to calculate natural frequency of vibration for the assembly of the PV modules by simulating the conditions close to the actual transportation experiment. This study shows that transportation makes the modules vibrate at their natural frequency. The first four natural frequencies of vibration calculated through the FE simulations match well with the peaks observed in the power spectral density profiles experienced by PV modules during transportation. Mode shapes corresponding to the first four natural frequencies have also been visualized to identify the contours with maximum displacement. It is hypothesized that out of all the cells, those falling within the contour of maximum displacement would have higher propensity for damage during the transportation. The results presented here can be useful for PV community to improve the packaging methodology, dimensions and material selection of the photovoltaic modules.

Free Layer Thickness Dependence of the Stability in Co2(Mn0.6Fe0.4)Ge Heusler Based CPP-GMR Read Sensor for Areal Density of 1 Tb/in2.

Current-perpendicular-to-the-plane giant magnetoresistance (CPP-GMR) read sensors based on Heusler alloys are promising candidates for ultrahigh areal densities of magnetic data storage technology. In particular, the thickness of reader structures is one of the key factors for the development of practical CPP-GMR sensors. In this research, we studied the dependence of the free layer thickness on the stability of the Co2(Mn0.6Fe0.4)Ge Heusler-based CPP-GMR read head for an areal density of 1 Tb/in2, aiming to determine the appropriate layer thickness. The evaluations were done through simulations based on micromagnetic modelling. The reader stability indicators, including the magnetoresistance (MR) ratio, readback signal, dibit response asymmetry parameter, and power spectral density profile, were characterized and discussed. Our analysis demonstrates that the reader with a free layer thickness of 3 nm indicates the best stability performance for this particular head. A reasonably large MR ratio of 26% was obtained by the reader having this suitable layer thickness. The findings can be utilized to improve the design of the CPP-GMR reader for use in ultrahigh magnetic recording densities.

Measurement of the mechanical reservoir spectral density in an optomechanical system

To investigate the dynamical behavior of a quantum system embedded in a memory environment, it is crucial to obtain the knowledge of the reservoir spectral density. However, such knowledge is usually based on a priori assumptions about the environment. In this paper, we put forward a method to obtain key information about the reservoir spectral density of an optomechanical resonator without additional assumptions about the spectral shape. This is achieved by detecting and analysing the optical transmission rate of the emitted light. In the weak optomechanical singlephoton coupling regime, we establish a simple relation between the output light spectrum and the reservoir spectral density. This provide a straightforward and effective way for reconstructing the spectral density profile in single or even multiple decoherence channels.

Optimal Sizing of CPP-GMR Read Sensors for Magnetic Recording Densities of 1–4 Tb/in²

Several studies have confirmed that current-perpendicular-to-the-plane giant magnetoresistance (CPP-GMR) technology is appropriate for next-generation read sensors for ultrahigh areal densities (ADs) of data storage applications. Since the physical dimension of the read sensor is a crucial factor for developing the reader to overcome its limitations, this paper proposes an optimal sizing prediction of the CPP-GMR read heads for ADs of 1-4 Tb/in2. Micromagnetic modelling was performed in the simulations. The appropriate length of the stripe height (SH) and the read width (RW) of the readers was estimated based on a consideration of sensor outputs including the readback signal, asymmetry parameter, dibit response and power spectral density (PSD) profile. It was found that a variation of SH and RW lengths had an influential impact on the readback signal waveform. Those affectations were further characterized through the echoes of dibit response showing that shortening the SH length or increasing the RW length could improve the resolution and reduce the distortion occurring in the readback signal. Moreover, the PSD profile indicated that the reader operation became more stable at shorter SH lengths or longer RW lengths. The head response spectrum was also examined. In addition, the magnitude of the bias current was studied in relation to the head response. Lastly, the optimal physical dimension (SH $\times $ RW) of the CPP-GMR readers for ADs of 1-4 Tb/in2 was predicted to be ( $40 \times 48$ ) nm, ( $28 \times 29$ ) nm, ( $25 \times 26$ ) nm and ( $19 \times 20$ ) nm, respectively. The results can be utilized to design the CPP-GMR sensors at ultrahigh magnetic recording capacities.