High Time Resolution Research Articles

Characterizing Supply Reliability Through the Synergistic Integration of VRE towards Enhancing Electrification in Kenya

Decentralized electrical power systems, driven by variable renewable energy sources such as solar PV and wind, have the potential to provide accessible and sustainable energy, contributing to the realization of a zero-carbon transition. However, these sources are susceptible to extreme weather conditions, presenting a challenge to the reliability of the power system. With abundant resources and a significant rural population lacking access to electricity, Africa has emerged as a key area for research on variable renewable energy-based electricity generation. Despite this focus, there remains a substantial gap in understanding at regional-scale the potential and variability of solar and wind power across various time scales, as well asthe impact of available resource synergy. Thisstudy aims to bridge this knowledge gap by conducting comprehensive simulations of hybrid wind and solar energy systems, both on-grid and off-grid, across 20 geographically diverse locations in Kenya. Using high-resolution hourly time step data, we examine the effect of resource complementarity on system reliability at varying time scales: daily, monthly and annually. The study findings shows the available VRE resource exhibit moderate tendency for complementarity, and optimizing their deployment can reduce hourly variability by 20%, significantly enhancing supply reliability, especially in the northern and eastern regions.

Core inductive electric field during sawtooth crashes on DIII-D

Sawtooth crashes on tokamak plasmas exhibit relaxation much faster than resistive time scales via a mechanism not fully understood. Using core magnetic measurements from the Radial Interferometer-Polarimeter (RIP) diagnostic on the DIII-D tokamak, Grad–Shafranov equilibria constrained by internal magnetic measurements that have high time resolution ( <1 µs) can be computed, allowing analysis of how equilibrium parameters such as safety factor q, current density J, and parallel electric field E∥ , particularly on-axis, evolve. At the sawtooth crash, on-axis safety factor q 0 is observed to rise by 5% but remain below 1 throughout the cycle, and on-axis current density J 0 is observed to drop by 5%. On-axis parallel electric field E∥(0) is found to be balanced by ηJ0 (resistivity times on-axis current density) except during the 200 µs crash period, where E∥(0) reaches 22 V m−1, exceeding ηJ0 by a factor of more than 2000. These first measurements in tokamak plasmas verify that generalized Ohm’s law is not balanced during the crash by resistive effects alone; this is a finding expected due to the relaxation being much faster than resistive timescales. Measurement of the electric field during the tokamak sawtooth serves to illuminate the physical mechanisms at work.

Optical dating of charcoal kiln remains from WWII: A test of accuracy

The majority of relic charcoal kilns in Europe are more recent than 1650 CE and cannot be precisely dated using radiocarbon dating (14C). Quartz-based optically stimulated luminescence (OSL) dating of the sediments associated with the kiln remains has been suggested as a viable alternative. Owing to the lack of reliable and sufficiently precise independent age information, however, it remains to be established whether OSL dating can yield accurate ages for post-1650 CE features. This is explicitly investigated in this study by applying a commonly adopted quartz OSL methodology to three relic charcoal kilns which are known to have been constructed and operated between December 1941 and March/April 1942 CE.We first document the quartz luminescence characteristics and show through procedural tests that the adopted single-aliquot regenerative dose procedure should be appropriate for equivalent dose determination. Four samples collected from the uppermost part of the charcoal-rich layers in the three features yield the youngest optical ages and are considered coeval. Their average age is 1928 ± 13 CE (95% probability), which matches the independent age reasonably well. The precision associated with the individual OSL ages ranges between 7 and 14% (1 sigma total uncertainty) and it might ideally be possible to establish relative chronologies with a higher time resolution. Finally, we briefly discuss our entire set of OSL ages in relation to future strategies for sampling charcoal kilns remains. In general, we conclude that OSL dating can be particularly advantageous to help resolving chronometric issues that pertain to post-1650 CE relic charcoal kilns.

Orbital-paced Oceanic Anoxic Event 2 evolution and astrochronology in the Mentelle Basin (Australia) at southern high latitudes

The Oceanic Anoxic Event 2 (OAE 2) is widely regarded as one of the most significant global-scale biological and environmental perturbations in the Mesozoic Era. However, the duration and driving mechanisms of this event at southern high latitudes remain largely unknown due to a lack of available geological records. Here, we present a cyclostratigraphic analysis of high-resolution records of lightness variability (L*) and gamma-ray attenuation (GRA) bulk density, which are associated with changes of marine primary productivity and continental weathering, respectively, from Site U1516 located in the Mentelle Basin, offshore southwest Australia. This analysis permits establishment of an astronomical time framework for a stratigraphic interval of 455.205–485.24 m rCCSF (revised Core Composite Depth below Sea Floor) by tuning the 100 kyr filter to short eccentricity. The studied section encompasses the entire OAE 2 interval at the depth of 460.13–473.94 m rCCSF. Based on the established high-resolution astronomical time scale using astronomical tuning of L* records to the short eccentricity cycles (100 kyr), the duration of OAE 2 is estimated to be ∼990 kyr at Site U1516. A relatively high amplitude of short eccentricity occurred at the build-up stage, accompanied by a gradual rise in obliquity amplitude during the recovery phase of the OAE 2. Combining previous proposals for enhanced oceanic water stratification and terrestrial weathering, we suggest that obliquity, coupled with short eccentricity, paced the evolution of this event at southern high latitudes by controlling insolation changes received by the Earth's surface.

EEG-based TSK fuzzy graph neural network for driver drowsiness estimation

With the development of brain-computer interface (BCI), electroencephalogram (EEG) is considered to be one of the best physiological signals to detect the fatigue state of drivers due to its advantages of extremely high time resolution and low use cost. However, since EEG is sensitive to noise/artifacts, and there is non-stationarity and low signal-to-noise ratio in inter-subject/intra-subject, the accurate estimation of driver drowsiness state remains challenging. Therefore, this paper proposes the EEG-based TSK fuzzy graph neural network (TSKG) to solve the regression problem of driver drowsiness estimation by combining transfer learning (TL), graph convolutional neural network (GCN), information theory, and TSK fuzzy neural network. TSKG extracts the relevant features in EEG through mutual information minimization and regards the fuzzy rules as graph structure data. The extracted relevant features and the original features are used to optimize the fuzzy rules through GCN. TSKG is tested on the fatigue driving dataset, and Root Mean Square Error (RMSE) and Correlation Coefficient (CC) are 0.1681 and 0.7118, respectively. Especially when dealing with difficult samples, TSKG has significantly better generalization performance.

Warming effect of the desert regulates spatio-temporal distribution of cotton Verticillium wilt for the oasis agriculture ecosystem

Verticillium wilt (VW) is threatening global cotton yield and quality. However, the accurate spatio-temporal dynamics of cotton VW in large regions remain unclear, especially in the complicated oasis agriculture ecosystem. We explored the spatio-temporal distribution of VW in the cotton-dominated region of Northern Xinjiang characterized by a typical desert-oasis irrigation agriculture ecosystem, utilizing reconstructed high-resolution time series remote sensing data from 2019 to 2021. Results revealed that the area of VW-infected cotton remained consistently around 20 % each year. However, there were significant seasonal variations, with outbreaks peaking in August. Regarding the spatial pattern of cotton VW, the mean temperature (TMP) difference in irrigated cotton fields along the Gurbantunggut Desert-oasis gradient reaches a maximum of approximately 1 ℃ caused by warming effect of the desert on the oasis (WEDO) during the cotton growing period. This TMP difference drives the spatial pattern of cotton VW incidence characterized by a low-to-high-to-moderate trend. WEDO significantly suppresses the cotton VW incidence due to relatively higher TMP, forming the low-risk zone for cotton VW within 16 km near the Gurbantunggut Desert. Our study significantly enhances the understanding of the spatio-temporal dynamics of cotton VW in the distinctive oasis irrigation agricultural ecosystem and advances the accurate monitoring and assessment of cotton VW across large regions.

HD 110067 c has an aligned orbit

Planetary systems in mean motion resonances hold a special place among the planetary population. They allow us to study planet formation in great detail as dissipative processes are thought to have played an important role in their existence. Additionally, planetary masses in bright resonant systems can be independently measured via both radial velocities and transit timing variations. In principle, they also allow us to quickly determine the inclination of all planets in the system since, for the system to be stable, they are likely all in coplanar orbits. To describe the full dynamical state of the system, we also need the stellar obliquity, which provides the orbital alignment of a planet with respect to the spin of its host star and can be measured thanks to the Rossiter–McLaughlin effect. It was recently discovered that HD 110067 harbors a system of six sub-Neptunes in resonant chain orbits. We here analyze an ESPRESSO high-resolution spectroscopic time series of HD 110067 during the transit of planet c. We find the orbit of HD 110067 c to be well aligned, with a sky-projected obliquity of λ =6+24-26 deg. This result indicates that the current architecture of the system was reached through convergent migration without any major disruptive events. Finally, we report transit-timing variation in this system as we find a significant offset of 19 ± 4 min in the center of the transit compared to the published ephemeris.

LCGCT: A light curve generator in customisable-time-bin based on time-series database

In the era of time-domain astronomy, scientists often need to generate light curves with varying time-bin. However, an increase in time resolution typically leads to a substantial increase in data transmission. To enhance the data processing efficiency in time-domain astronomy, we propose a novel time-series data model for storing time-series observation data, and we construct the LCGCT, a tool designed to produce light curves with customisable time bins. To validate our approach, we utilise the 7-year MAXI/GSC (Gas Slit Camera of the Monitor of All-sky X-ray Image) X-ray source catalogue, incorporating its 24-h binned light curves for a comparative analysis with our approach. The results obtained confirm the accuracy and effectiveness of our proposed approach. Subsequently, we compare the storage capacity and query performance of LCGCT with a PostgreSQL-based implementation, and results show that LCGCT conserves 75% of the storage space and achieves three times the query speed. Owing to its noteworthy storage and query performance, our proposed time-series data model-based LCGCT can be used in time-domain astronomical projects with high time resolution.

DynGMA: A robust approach for learning stochastic differential equations from data

Learning unknown stochastic differential equations (SDEs) from observed data is a significant and challenging task with applications in various fields. Current approaches often use neural networks to represent drift and diffusion functions, and construct likelihood-based loss by approximating the transition density to train these networks. However, these methods often rely on one-step stochastic numerical schemes, necessitating data with sufficiently high time resolution. In this paper, we introduce novel approximations to the transition density of the parameterized SDE: a Gaussian density approximation inspired by the random perturbation theory of dynamical systems, and its extension, the dynamical Gaussian mixture approximation (DynGMA). Benefiting from the robust density approximation, our method exhibits superior accuracy compared to baseline methods in learning the fully unknown drift and diffusion functions and computing the invariant distribution from trajectory data. And it is capable of handling trajectory data with low time resolution and variable, even uncontrollable, time step sizes, such as data generated from Gillespie's stochastic simulations. We then conduct several experiments across various scenarios to verify the advantages and robustness of the proposed method.

Quantitative analysis of temporal stability and instrument performance during field experiments of an airborne QCLAS via Allan–Werle-plots

Allan–Werle-plots are an established tool in infrared absorption spectroscopy to quantify temporal stability, maximum integration time and best achievable precision of a measurement instrument. In field measurements aboard a moving platform, however, long integration times reduce time resolution and smooth atmospheric variability. A high accuracy and time resolution are necessary as well as an appropriate estimate of the measurement uncertainty. In this study, Allan-Werle-plots of calibration gas measurements are studied to analyze the temporal characteristics of a Quantum Cascade Laser Absorption Spectrometer (QCLAS) instrument for airborne operation. Via least-squares fitting the individual noise contributions can be quantified and different dominant regimes can be identified. Through simulation of data according to the characteristics from the Allan-Werle-plot, the effects of selected intervals between in-flight calibrations can be analyzed. An interval of 30\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$30\\,$$\\end{document}min is found sufficient for successful drift correction during ground operation. The linear interpolation of the sensitivity increases the accuracy and lowers the measurement uncertainty from 1.1%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$1.1\\,\\%$$\\end{document} to 0.2%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$0.2\\,\\%$$\\end{document}. Airborne operation yields similar results during segments of stable flight but suffers from additional flicker and sinusoidal contributions. Simulations verify an appropriate interval of 30\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$30\\,$$\\end{document}min in airborne operation. The expected airborne measurement uncertainty is 2.45 ppbv.

Forecasting water resources from satellite image time series using a graph-based learning strategy

Abstract. In the context of climate change, it is important to monitor the dynamics of the Earth’s surface in order to prevent extreme weather phenomena such as floods and droughts. To this end, global meteorological forecasting is constantly being improved, with a recent breakthrough in deep learning methods. In this paper, we propose to adapt a recent weather forecasting architecture, called GraphCast, to a water resources forecasting task using high-resolution satellite image time series (SITS). Based on an intermediate mesh, the data geometry used within the network is adapted to match high spatial resolution data acquired in two-dimensional space. In particular, we introduce a predefined irregular mesh based on a segmentation map to guide the network’s predictions and bring more detail to specific areas. We conduct experiments to forecast water resources index two months ahead on lakes and rivers in Italy and Spain. We demonstrate that our adaptation of GraphCast outperforms the existing frameworks designed for SITS analysis. It also showed stable results for the main hyperparameter, i.e., the number of superpixels. We conclude that adapting global meteorological forecasting methods to SITS settings can be beneficial for high spatial resolution predictions.

Scour-depth variability controls channel-scale stratigraphy in experimental braided rivers

ABSTRACT Braided rivers distribute sediment across landscapes, often forming wide channel belts that are preserved in stratigraphy as coarse-grained deposits. Theoretical work has established quantitative links between the depth distribution of formative channels in a braided river and the geometry of their preserved strata. However, testing these predictive relationships between geomorphic process and stratigraphic product requires examining how braided rivers and their deposits coevolve, with high resolution in both space and time. Here, using a series of four runs of a physical experiment, we examine the controls of water discharge and slope on the resulting geometry of preserved deposits. Specifically, we focus on how a twofold variation in water discharge and initial riverbed slope affects the spatiotemporal distribution of channel depths and the geometry of preserved deposits of a braided river. We find that the channel depths in the laboratory experiment are described by a two-parameter gamma distribution and the deepest scours correspond to zones of erosion at channel-belt margins and channel-thread confluences in the channel belt. We use a reduced-complexity flow model to reconstruct flow depths, which were shallower compared to channel thalweg depths. Synthetic stratigraphy built from timeseries of topographic surfaces shows that the distribution of cut-and-fill-unit thickness is invariant across the experiments and is determined by the variability in scour depths. We show that the distribution of cut-and-fill-unit thickness can be used to reconstruct formative-channel-depth distributions and that the mean thickness of these units is 0.31 to 0.62 times the mean formative flow depth across all experiments. Our results suggest that variations in discharge and slope do not translate to measurable differences in preserved cut-and-fill-unit thickness, suggesting that changes in external forcings are likely to be preserved in braided river deposits only when they exceed a certain threshold of change.

The time between Palaeolithic hearths.

Resolving the timescale of human activity in the Palaeolithic Age is one of the most challenging problems in prehistoric archaeology. The duration and frequency of hunter-gatherer camps reflect key aspects of social life and human-environment interactions. However, the time dimension of Palaeolithic contexts is generally inaccurately reconstructed because of the limitations of dating techniques1, the impact of disturbing agents on sedimentary deposits2 and the palimpsest effect3,4. Here we report high-resolution time differences between six Middle Palaeolithic hearths from El Salt Unit X (Spain) obtained through archaeomagnetic and archaeostratigraphic analyses. The set of hearths covers at least around 200-240 years with 99% probability, having decade- and century-long intervals between the different hearths. Our results provide a quantitative estimate of the time framework for the human occupation events included in the studied sequence. This is a step forward in Palaeolithic archaeology, a discipline in which human behaviour is usually approached from a temporal scale typical of geological processes, whereas significant change may happen at the smaller scales of human generations. Here we reach a timescale close to a human lifespan.

Microfluidic paper-based chemiluminescence sensing platform based on functionalized CaCO3 for time-resolved multiplex detection of avian influenza virus biomarkers

Multiplex detection can enhance diagnostic precision and improve diagnostic efficiency, providing important assistance for epidemiological investigation and epidemic prevention. There is a great need for multi-detection sensing platforms to accurately diagnose diseases. Herein, we reported a μPAD-based chemiluminescence (CL) assay for ultrasensitive multiplex detection of AIV biomarkers, based on three DNAzyme/Lum/PEI/CaCO3. Three time-resolved CL signals were sequentially generated with detection limits of 0.32, 0.34, and 0.29 pM for H1N1, H7N9, and H5N1, respectively, and with excellent selectivity against interfering DNA. The recovery test in human serum displayed satisfactory analysis capabilities for complex biological samples. The μPAD-based CL assay achieved multiplex detection within 70 s, with a high time resolution of 20 s. The proposed strategy has the advantages of low cost, high sensitivity, good selectivity, and wide time resolution, the μPAD-based CL assay has shown great potential in the early and accurate diagnosis of diseases.

RRER: A refined registration method based on contrast minimum for event and RGB cameras

AbstractThe precise perception of the surrounding environment in traffic scenes is an important part of an intelligent transportation system. The event camera could provide complementary information to traditional frame‐based cameras, such as high dynamic range, and high time resolution, in the perception of traffic targets. To improve the precision and reliability of perception as well as facilitate lots of RGB camera‐based studies introduced to event cameras directly, a refined registration method for event‐based cameras and RGB cameras on the basis of pixel‐level region segmentation is proposed, to provide a fusion method at pixel level. A total of eight sequences and a dataset containing 260 typical traffic scenes are contained in the experiment dataset, both selected from DSEC, a traffic event‐based dataset. The registered event image shows a better spatial consistency with RGB images visually. Compared to the baseline, the evaluation indicators, such as the performance of the contrast, the proportion of overlapping pixels, and average registration accuracy have been improved. In the traffic object segmentation task, the average boundary displacement error of our method has decreased and the max decline value has reached 79.665%, compared to the boundary displacement error between ground truth and baseline. These results indicate prospective applications in the perception of intelligent transportation systems combined with event and RGB cameras. The traffic dataset with pixel‐level semantic annotations will be provided soon.

Statistical Analysis of Flux Enhancements of Energetic Electrons in the Low-Latitudinal Ionosphere According to the Data from the NOAA/POES and MetOp Satellites from 1998 to 2022

The intense precipitation of energetic electrons from the Earth’s radiation belt (ERB) is one of the most important sources of ionization in the ionosphere and atmosphere. A large-scale statistical analysis is carried out of the data from continuous low-orbit satellite observations of solar-cycle variations in the flux enhancements of the ERB electrons with energy >30 keV at an altitude of 850 km, acquired from the NOAA/POES and MetOp satellites in the interval from 1998 to 2022. The basic features of artificial failures in the satellite database with high-time resolution measurements in the interval from 2014 to 2022 are found and described. Appropriate data correction is carried out. It is shown that the average annual number of days with electron flux enhancements increases rapidly within three years after the solar-cycle maximum and reaches its greatest value near the middle of the declining phase of solar activity. Then the frequency of event occurrence begins to decrease noticeably within an 8-year interval, including the minimum, rising, and maximum phases of the solar cycle. The minimum level is achieved at the maximum solar activity.

Generating high-resolution hyperspectral time series datasets based on unsupervised spatial-temporal-spectral fusion network incorporating a deep prior

Over the past decade, image fusion has emerged as an indispensable tool for surface monitoring due to its capability to reconstruct high-quality surface reflectance. While satisfactory progress has been made in the spatial-spectral and spatial-temporal fusion of remote sensing images, the fusion of spatial-temporal-spectral data remains a challenging task. This challenge arises from the presence of multiple nonlinear relationships caused by inconsistent temporal, spatial, and spectral resolutions. In this paper, we propose a novel approach to address the spatial-temporal-spectral fusion of remote sensing images using a triple discriminator Generative Adversarial Network called TDGAN. Our approach represents the first attempt at spatial-temporal-spectral fusion based on deep learning techniques. Specifically, TDGAN achieves unsupervised learning by incorporating a deep spectral transformation prior, explores the application performance of the Swin Transformer in spectral super-resolution for the first time. Additionally, three discriminators are designed based on the prior consistencies: phenological consistency for data acquired at different times and spatial-spectral consistency for data acquired at the same time. These discriminators effectively enhance the prediction accuracy of missing hyperspectral images. Extensive simulations and real experiments were conducted to evaluate the effectiveness of our proposed TDGAN. The results demonstrate its robustness and comparable performance to other state-of-the-art methods. The proposed approach provides high-quality hyperspectral datasets with high spatial and temporal resolutions, facilitating continuous land cover observations.

A preliminary study on the application of electrical impedance tomography based on cerebral perfusion monitoring to intracranial pressure changes.

In intracranial pathologic conditions of intracranial pressure (ICP) disturbance or hemodynamic instability, maintaining appropriate ICP may reduce the risk of ischemic brain injury. The change of ICP is often accompanied by the change of intracranial blood status. As a non-invasive functional imaging technique, the sensitivity of electrical impedance tomography (EIT) to cerebral hemodynamic changes has been preliminarily confirmed. However, no team has conducted a feasibility study on the dynamic detection of ICP by EIT technology from the perspective of non-invasive whole-brain blood perfusion monitoring. In this study, human brain EIT image sequence was obtained by in vivo measurement, from which a variety of indicators that can reflect the tidal changes of the whole brain impedance were extracted, in order to establish a new method for non-invasive monitoring of ICP changes from the level of cerebral blood perfusion monitoring. Valsalva maneuver (VM) was used to temporarily change the cerebral blood perfusion status of volunteers. The electrical impedance information of the brain during this process was continuously monitored by EIT device and real-time imaging was performed, and the hemodynamic indexes of bilateral middle cerebral arteries were monitored by transcranial Doppler (TCD). The changes in monitoring information obtained by the two techniques were compared and observed. The EIT imaging results indicated that the image sequence showed obvious tidal changes with the heart beating. Perfusion indicators of vascular pulsation obtained from EIT images decreased significantly during the stabilization phase of the intervention (PAC: 242.94 ± 100.83, p < 0.01); perfusion index which reflects vascular resistance increased significantly in the stable stage of intervention (PDT: 79.72 ± 18.23, p < 0.001). After the intervention, the parameters gradually returned to the baseline level before compression. The changes of EIT indexes in the whole process are consistent with the changes of middle cerebral artery velocity related indexes shown in TCD results. The EIT image combined with the blood perfusion index proposed in this paper can reflect the decrease of cerebral blood flow under the condition of increased ICP in real time and intuitively. With the advantages of high time resolution and high sensitivity, EIT provides a new idea for non-invasive bedside measurement of ICP.

A benchmark rapidly oscillating chemically peculiar (roAp) star: alpha Cir

The brightest chemically peculiar magnetic (mCP) star is also pulsating. Precise photometric and spectroscopic data, preferably with a long time base, are needed to investigate its evolutionary aspects as well. The present investigation of \ offers a space-based high-precision photometry study with high time resolution, covering 20+ years and supplemented by high resolution spectroscopy from the ground. We discuss the controversial rotation periods that have been recently reported and we consider new determinations of the actual values. We process the complex pulsation frequency spectrum, considering the implications in modelling the structure of We developed an automated Bayesian algorithm to consistently search for periodic signals in the WIRE, SMEI, TESS, and BRITE space photometric datasets, complemented by radial velocity data from HARPS. New observations in 2021 and 2023 from TESS and BRITE indicate a detection of as a triple system. The rotation period of has been determined as $4.4792890 The TESS data show a rich frequency spectrum including three $l=0$, six $l=1$, two $l=2,$ and one $l=3$ modes. Of these, five are shown to be rotationally split. The dipole modes show significant curvature in the echelle diagram, probably due to the strong magnetic field of Overall continues to be a cornerstone of mCP stars. A confirmation of the triple system requires additional space photometry and/or high-resolution spectroscopy to increase the time base. These data are also needed to improve the quality of the pulsation frequency spectrum and to investigate the evolutionary effects at play. A detailed seismic modelling study that considers the effects of a magnetic field on pulsation is subsequently recommended.

Spurious signals identification in Brillouin light scattering spectrum

AbstractBrillouin light scattering (BLS) is the inelastic scattering of light from elementary excitations with periodic density modulation. The characteristics of non‐contact, high sensitivity, and high resolution in energy, wavevector, time, space, and phase make the BLS spectrometer widely used in investigating many intriguing physical phenomena, including the acoustic phonon confinement effects, Bose‐Einstein condensation (BEC), supercurrent, and soliton formation. Generally, the quick and correct assignment of the signals in the BLS spectra is a prerequisite for further investigations. Herein, we experimentally identify the high‐order spurious signals in the BLS spectra, which make the interpretation of the spectra difficult. The additional signals are demonstrated to originate from the laser and the temperature‐controlled laser filter used for laser filtering. Our results would contribute to the rapid assignment of the signals from the sample after excluding the spurious signals reported here. Moreover, the series of high‐order modes spaced by the free spectral range can serve as a weak broadband light source, which has great potential for investigating the optical responses of materials.