Periodic Signal Research Articles

High performance SERS boosting by Fabry- Pérot cavities of silica-gold-silicon multilayers

Surface-enhanced Raman scattering (SERS), an advanced technique for molecular spectroscopy, relies heavily on the preparation of SERS active materials that can significantly enhance the Raman scattering signals for highly sensitive detection of trace molecules. Traditionally, SERS measurements are performed on silicon or silica substrates, the SERS performance is determined by the structure of SERS materials. Here, we show that the SERS signal can be amplified and modulated using Fabry-Pérot (F-P) cavities made of silica-silicon (SiO2-Si) or silica-gold-silicon (SiO2-Au-Si) multilayers as substrates. Periodic SERS signal variations as SiO2 thickness increases are observed, exhibiting optimal enhancement with the SiO2 thickness of 250 nm due to the optical interference in the cavity. Although the signal enhancement by optical interference is weaker than that by plasmonic resonance, additional signal amplification is essential for highly sensitive SERS materials. Moreover, we applied this strategy to detect thiram in bean sprout extracts, demonstrating that the detection sensitivity is two orders of magnitude higher than that using Si substrates. The utilization of the pseudo-internal standard intensity calibration method facilitates the quantitative analysis of thiram concentrations. Our results provide a promising approach for further amplification of SERS signals with great potential for practical applications.

Symmetry in Signals: A New Insight

Symmetry is a fundamental property of many natural systems, which is observable through signals. In most out-of-equilibrium complex dynamic systems, the observed signals are asymmetric. However, for certain operating modes, some systems have demonstrated a resurgence of symmetry in their signals. Research has naturally focused on examining time invariance to quantify this symmetry. Measures based on the statistical and harmonic properties of signals have been proposed, but most of them focused on harmonic distortion without explicitly measuring symmetry. This paper introduces a new mathematical framework based on group theory for analyzing signal symmetry beyond time invariance. It presents new indicators to evaluate different types of symmetry in non-stochastic symmetric signals. Both periodic and non-periodic symmetric signals are analyzed to formalize the problem. The study raises critical questions about the completeness of symmetry in signals and proposes a new classification for periodic and non-periodic signals that goes beyond the traditional classification based on Fourier coefficients. Furthermore, new measures such as “symmetrometry” and “distorsymmetry” are introduced to quantify symmetry. These measures outperform traditional indicators like Total Harmonic Distortion (THD) and provide a more accurate measurement of symmetry in complex signals from applications where duty cycle plays a major role.

Robust sensing via the standard deviation with a quantum sensor

Quantum sensing has a bright future for applications in need of impeccable sensitivities. The study of periodic fields has resulted in various techniques, which deal with the limited coherence time of the quantum sensor in several ways. However, the periodic signal to measure could include forms of randomness as well, such as changes in phase or in frequency. In such cases, long measurement times required to detect the smallest of field amplitudes hamper the effectiveness of conventional techniques. In this paper, we propose and explore a robust sensing technique to combat this problem. For the technique, instead of measuring the signal amplitude directly, we measure another global property of the signal, in this case the standard deviation. This results in a much-improved sensitivity. We analyze the advantages and limitations of this technique, and we demonstrate the working with a measurement using a nitrogen-vacancy center. This work encourages scouting measurements of alternative statistics.

Modulation of Phase-Locking Characteristics of NbOx Memristor by Ag Doping.

Memristors based on niobium oxide have attracted wide interest due to their applications in artificial neural network. Phase-locking (PL) characteristics of NbOx newly explored roots in complex nonlinear dynamics and exhibits great potential in periodical signal handling because of its bioinspired nature. In this study, we fabricate a Pd/Nb/Ag-NbOx/Nb/Pd memristive structure and study the effects of Ag doping on the PL characteristics. We clearly see that the NbOx memristor responds to signal in three distinct patterns. For the low-frequency input, the memristor fires spike series and locks the phase near during the positive period of sinusoidal input, and it encodes the input features by the spike number per period. For the middle-frequency input, the memristor fires one spike per period at a definite phase. The output has the same frequency as the input. The locked phase is proportional to the input frequency. For the high-frequency input, the memristor transforms high frequency to low frequency signal and locks at a definite phase higher than 2π. We combined the microstructural analysis and chaos dynamics to know that Ag doping will lower the activation energy, enhance the responding rate, and enhance thermal conductivity, which extends the locked frequency to 1.7 times the value of the undoped NbOx memristor. We also obtained the locked frequency of even 40 MHz after modulating the elementary circuit configuration according to the material modification and chaos model. Our study proposes to handle a signal with high efficiency resembling auditory sense and inspires a novel artificial intelligent computation prototype.

Dynamics and Detection of Pulsed Tremor at Whakaari (White Island), Aotearoa New Zealand

AbstractVolcanic tremor is a crucial indicator for assessing the state and hazard potential of volcanic systems. At Whakaari (White Island volcano, Aotearoa New Zealand), a pulsed tremor signal emerged after a hydrothermal explosion in August 2012. The tremor accompanied the extrusion of a lava dome, before gradually disappearing prior to the onset of renewed hydrothermal activity in January 2013. We interpret this seismic signal to represent discrete gas transfers from a magmatic intrusion toward a permeable cap—possibly a hydrothermal seal—in the upper layers of Whakaari's hydrothermal system. Such tremor may thus be associated with heightened potential for hazardous explosive activity but is difficult to detect using conventional seismic monitoring parameters. To highlight the emergence of subtle periodic signals, we experiment with Lomb‐Scargle periodograms (LS). LS detect the tremor 5 days before it becomes visible in seismograms, thus facilitating the recognition of such elusive seismic patterns.

Groundwater-surface water exchanges in an alluvial plain in southern France subjected to pumping: A coupled multitracer and modeling approach

Study regionThe study was conducted in an alluvial plain between the Rhône and the Ouvèze Rivers (in the southeast of France) extensively exploited for drinking water. The research area is characterized by significant groundwater-surface interactions influenced by groundwater pumping activities. Study focusThe aim of this study is to enhance the understanding of interactions between rivers and alluvial aquifers by combined multi-tracer and numerical modeling approaches. Over an 18-month period, groundwater temperature, piezometric levels, and river surface water levels were continuously monitored. Field campaigns focused on conductivity, stable isotopes of water, and radon-222 activity concentration in both groundwater and surface water. Radon-222 was used to quantify water exchanges between the river and the aquifer. A MODFLOW model, calibrated using piezometric data and PEST, was employed to simulate groundwater flow and reactive transport of radon-222 using MT3DMS. New hydrological insights for the regionThe study reveals that river water recharges the aquifer, with radon-222 data delineating this recharge zone. The methodology extended the interpretation of periodic groundwater temperature signals to isotopic signals, allowing the identification of dispersivity and Darcy's velocity. The Ouvèze River was found to contribute approximately 55 % of the pumping water supply, alongside the Rhône. These findings provide valuable insights for sustainable water resource management, demonstrating the relevance of using natural tracers in scenarios where artificial tracers are impractical.

Single pulse shaping for higher harmonic demodulation in terahertz time-domain spectroscopy

We present a simple, highly stable, low noise, and rapid detection scheme using higher harmonic demodulation applied to terahertz time domain spectroscopy (THz-TDS). The presence of higher harmonics in the detected periodic signal is because of the non-sinusoidal shape of a single pulse, which is controlled by an ultrafast current pre-amplifier. Instead of using external signal modulators, the use of the inherent repetition rate (frep) of the femtosecond laser and its harmonics as reference for the lock-in amplifier simplifies the setup, while allows rapid and low noise detection owing to the megahertz modulation frequencies. Unlike the signal detected at the fundamental frep, signals detected at higher harmonics have much lower offset and are unaffected by perturbations in the environment present during measurements, which is an essential characteristic for an analytical tool. Our proposed technique can be readily integrated to existing THz-TDS systems and is applicable to scans with rapid acquisition times and to scans that require long periods of time (e.g., hyperspectral imaging).

On the nature of the eccentric eclipsing binary star SY Phe with a pulsating γ Dor component

ABSTRACT Spectroscopic observations of the eccentric binary system SY Phe were made at the South African Astronomical Observatory in 2019, 2020, and 2021, and its mid-resolution spectra were obtained. The radial velocities of the component stars were measured using the cross-correlation method and Fourier disentangling of the spectra. The spectral type (hence the effective temperature) of the primary star was determined from a model-atmosphere analysis. The radial velocity and Transiting Exoplanet Survey Satellite (TESS) light curves of the system were analysed, and its absolute parameters were derived. A strong (5.2 mmag) periodic signal with a frequency typical of $\gamma$ Dor stars (1.169 cycles per day) dominates the Fourier spectrum of the light curve between the eclipses. Apsidal motion parameters of SY Phe were calculated by studying eclipse timing variations. The Geneva evolution models indicate an evolutionary age of 2 Gyr and solar metallicity for the primary component; however, although the position of the secondary component in the H–R diagram matches the isochrone of 2 Gyr, it appears to have a larger radius and higher effective temperature than expected for its determined mass. Here, the secondary component has too large a radius, which is in accordance with the radius discrepancy problem that has been encountered in other studies, especially in late-type dwarfs, and has not been solved for half a century.

Search for thermonuclear burst oscillations in the Swift/BAT data set

This study comprehensively analyzes type I X-ray bursts observed by Swift/BAT from 2005 to April 2024 to search for X-ray burst oscillations (XBOs) in neutron star low-mass X-ray binaries. XBOs, periodic signals detected within type I X-ray bursts, typically range from 11 to 620 Hz and are often observed in the soft X-ray data of these bursts. Using the high-sensitivity and precise timing capabilities of the Swift/BAT, we found 50 type I X-ray bursts from 37 neutron star low-mass X-ray binaries. We conducted a detailed timing analysis of these bursts. For sources with known burst oscillation frequencies, our findings largely corroborate previous studies. However, many sources displayed low confidence levels in the oscillation signals, with Z12 values between 10 and 20. For sources without known oscillation/spin frequencies, we utilized FFT analysis to search for signals across a broad frequency range. This approach revealed potential oscillation signals, with several bursts showing significance levels exceeding 3σ, including those from MAXI J1421–613, XTE J1701–407, XMM J174457–2850.3, Swift J1734.5–3027, IGR J17473–2721, Swift J174805.3–244637, Swift J181723.1–164300, and X 1832–330.

Spiking neural networks-based generation of caterpillar-like soft robot crawling motions

Robots have been widely used in daily life in recent years. Unlike conventional robots made of rigid materials, soft robots utilize stretchable and flexible materials, allowing flexible movements similar to those of living organisms, which are difficult for traditional robots. Previous studies have used periodic signals to control soft robots, which lead to repetitive motions and make it challenging to generate environment-adapted motions. To address this issue, control methods can be learned through deep reinforcement learning to enable soft robots to select appropriate actions based on observations, improving their adaptability to environmental changes. In addition, as mobile robots have limited onboard resources, it is necessary to conserve battery consumption and achieve low-power control. Therefore, the use of spiking neural networks (SNNs) with neuromorphic chips enables low-power control of soft robots. In this study, we investigated the learning methods for SNNs aimed at controlling soft robots. Experiments were conducted using a caterpillar-like soft robot model based on previous studies, and the effectiveness of the learning method was evaluated.

Multiplicative noise induced bistability and stochastic resonance

Abstract Stochastic resonance is a well established phenomenon, which proves relevant for a wide range of applications, of broad trans-disciplinary breath. Consider a one dimensional bistable stochastic system, characterized by a deterministic double well potential and shaken by an additive noise source. When subject to an external periodic drive, and for a proper choice of the noise strength, the system swings regularly between the two existing deterministic fixed points, with just one switch for each oscillation of the imposed forcing term. This resonant condition can be exploited to unravel weak periodic signals, otherwise inaccessible to conventional detectors. Here, we will set to revisit the stochastic resonance concept by operating in a modified framework where bistability is induced by the nonlinear nature of the multiplicative noise. A candidate model is in particular introduced which fulfils the above requirements while allowing for analytical progress to be made. Working with reference to this case study, we elaborate on the conditions for the onset of the generalized stochastic resonance mechanism. As a byproduct of the analysis, a novel resonant regime is also identified which displays no lower bound for the frequencies that can be resolved, at variance with the traditional setting.

Derivative Sampling of Periodic and Nonperiodic Band-Limited Signals — Fourier Spectrum and Interpolation Formula

Derivative Sampling of Periodic and Nonperiodic Band-Limited Signals — Fourier Spectrum and Interpolation Formula

AstroSat and Insight-HXMT Observations of the Long-period X-Ray Pulsar 4U 2206+54

We report the timing and spectral studies of the accreting X-ray pulsar 4U 2206+54 using AstroSat and Insight-HXMT observations taken in 2016 and 2020 respectively. X-ray pulsations from the system are detected by both missions. The AstroSat discovered a significant periodic signal at ∼5619 s in 2016, and Insight-HXMT found a pulsation period at ∼5291 s in 2020. A comparison of its spin-period evolution with the present spin-period estimates shows that the neutron star in 4U 2206+54 now has recently been undergoing a spin-up episode after attaining to its slow pulsations of 5750 s around 2015 from its prolonged spin-down phase. The present average spin-up rate of the pulsar is found to be at ∼1.2 × 10−13 Hz s−1. The phase-averaged spectra of the pulsar in 1–60 keV could be explained with a high-energy cutoff power-law continuum model; no evident line features are found with AstroSat. The application of Comptonization models such as comptt and compmag to the phase-averaged spectra of 4U 2206+54 reveals a hotter source photon region near the pulsar with an emission size extending to ∼2–2.8 km. Using the quasi-spherical settling accretion theory, we explain the present spin-up and the possibility of the strong magnetic field of the pulsar.

Asteroid Period Solutions from Combined Dense and Sparse Photometry

Deriving high-quality light curves for asteroids and other periodic sources from survey data is challenging owing to many factors, including the sparsely sampled observational record and diurnal aliasing, which is a signature imparted into the periodic signal of a source that is a function of the observing schedule of ground-based telescopes. In this paper we examine the utility of combining asteroid observational records from the Zwicky Transient Facility and the Transiting Exoplanet Survey Satellite, which are the ground- and space-based facilities, respectively, to determine to what degree the data from the space-based facility can suppress diurnal aliases. Furthermore, we examine several optimizations that are used to derive the rotation periods of asteroids, which we then compare to the reported rotation periods in the literature. Through this analysis we find that we can reliably derive the rotation periods for ∼85% of our sample of 222 objects that are also reported in the literature and that the remaining ∼15% are difficult to reliably derive, as many are asteroids that are insufficiently elongated, which produces a light curve with an insufficient amplitude and, consequently, an incorrect rotation period. We also investigate a binary classification method that biases against reporting incorrect rotation periods. We conclude the paper by assessing the utility of using other ground- or space-based facilities as companion telescopes to the forthcoming Rubin Observatory.

Assessments of GPS satellite orbiting period effects on diurnal and semi-diurnal luni-solar declinations utilizing Galileo satellites

Global Navigation Satellite Systems (GNSS) can observe a variety of surface deformations on Earth, including periodic oscillations at different frequencies. An example of such phenomena is ocean tide loadings (OTL), which result from the redistribution of water mass. The Global Positioning System (GPS) exhibits orbital geometry that causes its revisit and orbital periods to coincide with the diurnal and semi-diurnal luni-solar declination constituents, known as K1 and K2, respectively. Consequently, the system faces challenges in accurately estimating these periodic oscillations due to its orbital artifacts. This study aims to quantify the extent to which GPS orbital artifacts introduce periodic signals into the K1 and K2 constituents by utilizing the Galileo system and determining the most suitable positioning approach. A dataset from the International GNSS Service (IGS), spanning 40 days in 2024 and covering six stations, was analyzed. Coordinates were estimated using both kinematic positioning every 5 minutes and a 6-hour static precise point positioning (PPP) mode with a 3-hour shift. The power spectra for the east, north, and up components indicated that, on average, the GPS system contributes 52.8% to the K1 constituents and 66.3% to the K2 constituents. Despite expectations that the diurnal K1 and semi-diurnal K2 tidal constituents would be more prominent in the power spectra of the GPS comparing to that of natural signature or of other navigation system (Galileo for this study), the diurnal K1 tidal constituent appeared weak in the kinematic mode power spectra for the GPS system. These findings validate that the overlapped-static PPP mode is a more appropriate approach for estimating these periodic deformations.

Periodicity significance testing with null-signal templates: reassessment of PTF’s SMBH binary candidates

ABSTRACT Periodograms are widely employed for identifying periodicity in time series data, yet they often struggle to accurately quantify the statistical significance of detected periodic signals when the data complexity precludes reliable simulations. We develop a data-driven approach to address this challenge by introducing a null-signal template (NST). The NST is created by carefully randomizing the period of each cycle in the periodogram template, rendering it non-periodic. It has the same frequentist properties as a periodic signal template, and we show with simulations that the distribution of false positives is the same as with the original periodic template, regardless of the underlying data. Thus, performing a periodicity search with the NST acts as an effective simulation of the null (no-signal) hypothesis, without having to simulate the noise properties of the data. We apply the NST method to the supermassive black hole binaries (SMBHB) search in the Palomar Transient Factory (PTF), where Charisi et al. had previously proposed 33 high signal-to-noise candidates utilizing simulations to quantify their significance. Our approach reveals that these simulations do not capture the complexity of the real data. There are no statistically significant periodic signal detections above the non-periodic background. To improve the search sensitivity, we introduce a Gaussian quadrature based algorithm for the Bayes Factor with correlated noise as a test statistic. We show with simulations that this improves sensitivity to true signals by more than an order of magnitude. However, the Bayes Factor approach also results in no statistically significant detections in the PTF data.

Radial velocity analysis of stars with debris discs

ABSTRACT This study aims to identify potential exoplanet signals from nearby stars with resolved debris discs. However, the high activity of many stars with debris discs limits the detection of periodic signals. Our study is constrained to a sample of 29 stars that have appropriate radial velocity data and debris disc measurements sufficient to resolve their inclination. Our results confirm and update previous findings for exoplanets around HD 10647, HD 115617, HD 69830, GJ 581, HD 22049, and HD 142091, and we identify long-term activity signals around HD 207129 and HD 202628. We utilize the inclination angles of the debris discs, assuming co-planarity between debris disc and exoplanet orbit, to determine the ‘disc-aligned’ masses of radial velocity exoplanets in this study. The ‘disc-aligned’ masses of HD 69830 b, HD 69830 c, and 61 Vir b suggests that they may be classified as ‘hot’ or ‘warm’ Jupiters and so might be nearby examples of planets that have undergone recent type-II disc migration.

On the Consistency of Stochastic Noise Properties and Velocity Estimations from Different Analysis Strategies and Centers with Environmental Loading and CME Corrections

The analysis of the Global NFavigation Satellite System (GNSS) time series provides valuable information for geodesy and geodynamics researcFh. Precise data analysis strategies are crucial for accurately obtaining the linear velocity of GNSS stations, enabling high-precision applications of GNSS time series. This study investigates the impact of different stochastic noise models on velocity estimations derived from GNSS time series, specifically under conditions of environmental loading correction and common mode error (CME) removal. By comparing data from various data centers, we find that post-correction, different analysis strategies exhibit high consistency in their noise characteristics and velocity estimation results. Across various analysis strategies, the optimal noise models were predominantly Power Law with White Noise (PLWN) and Fractional Noise with White Noise (FNWN), with the optimal noise models including COMB/JPL, COMB/SOPAC, and COMB/NGL for approximately 50% of the datasets. Most of the stations (approximately 80%) showed velocity differences below 0.3 mm/year and velocity estimation uncertainties below 0.1 mm/year. Nonetheless, variations in amplitudes and periodic signals persisted due to differences in the processing of raw GNSS observations. For instance, the NGL and JPL datasets, which were processed using GipsyX 2.1 software, showed higher amplitudes of the 5.5-day periodic signal. These findings provide a solid empirical foundation for advancing data analysis methods and enhancing the reliability of GNSS time series results in future research.

Enhancing Unmanned Marine Vehicle Security: A Periodic Watermark-Based Detection of Replay Attacks

This paper explores a periodic watermark-based replay attack detection method for Unmanned Marine Vehicles modeled in the framework of the Takagi–Sugeno fuzzy system. The precise detection of replay attacks is crucial for ensuring the security of Unmanned Marine Vehicles; however, traditional timestamp-based or encoded measurement-dependent detection approaches often sacrifice system performance to achieve higher detection rates. To reduce the potential performance degradation, a periodic watermark-based detection scheme is developed, in which a compensation signal together with a periodic Gaussian watermark signal is integrated into the actuator. By compensation calculations conducted with all compensatory signals in each period, the position corresponding to a minimum value of the detection function can be derived. Then, the time that the attacks occurred can be ensured with the aid of the comparison between this position with the watermark signal in the same period. An application on a UMV is shown to demonstrate the effectiveness of the presented scheme in detecting replay attacks while minimizing control costs.

An auditory selective attention brain-computer interface system based on auditory steady-state response

Auditory steady-state response (ASSR) is a brain steady-state response induced by periodic sound signals, which can be used to build an auditory brain-computer interface (BCI), thereby providing a pathway for visually impaired patients to communicate with the outside world. Most of existing ASSR-based BCI studies use linear discriminant classifier (LDA) and spatial coherence to detect ASSRs. Therefore, there is an urgent need for efficient electroencephalogram (EEG) decoding methods to improve the performance of ASSR-based BCI systems. In this study, we elicited ASSRs using sinusoidal amplitude modulated (SAM) tones that simultaneously delivered different modulation frequencies (i.e., 37 Hz for the left channel and 43 Hz for the right channel). Subjects were asked to focus their attention on the auditory stimulation on one side according to the auditory cue. Filter bank common spatial pattern (FBCSP) algorithm was innovatively introduced to detect the ASSRs. Offline results showed that the brain region with strong ASSRs was the central forehead area, and when subjects paid attention to the auditory stimulation at 37 Hz or 43 Hz, the ASSR response of 37 Hz or 43 Hz on the corresponding side would be enhanced compared to the no attention condition. Online results obtained from twelve healthy subjects showed that the mean recognition accuracy of the proposed ASSR-based BCI system achieved a mean accuracy of 82.22 ± 3.11 %. Moreover, the present study further verified that weak auditory stimuli with low stimulus intensity (i.e., 40 dB SPL) could also be used to build ASSR-based BCIs, and achieved an online mean accuracy of 78.89 ± 2.54 %. These results verified that the FBCSP algorithm could be used for detecting ASSRs and the feasibility of the proposed ASSR-based BCI system, providing a great idea for building a high-speed ASSR-based BCI system.