Solar Neighborhood Research Articles

Deep deterministic policy gradient caching method for privacy protection in Internet of Vehicles

To address the problem of low cache hit ratio in edge nodes for privacy-preserving in the Internet of Vehicles (IoV), a deep deterministic policy gradient caching (DDPGC) method was proposed. First, a taxi certified by a trusted authority acted as a second-level caching edge node to acquire hotspot data and store it in the local cache. It then broadcasted this information to the neighboring service requesting vehicles (SRVs). SRVs cached the broadcasted data locally and search for service requests in the order of priority of local cache, taxi, and cloud server when such requests arise. Secondly, a neural network was deployed in taxis and SRVs to maximize the caching benefit through deep reinforcement learning for decision replacement of their cached data. Finally, when SRVs were located in vehicle sparsity and could not obtain request data from neighboring vehicles, a combination of k-anonymity and random response perturbation mechanisms generated anonymity sets to send requests to cloud servers in an anonymous manner to obtain services while protecting user location privacy. Simulation experimental results show that DDPGC can effectively improve the vehicle cache hit ratio, reduce the frequency of SRV interaction with the cloud server, and effectively protect user privacy security.

PillarVTP: vehicle trajectory prediction method based on local point cloud aggregation and receptive field expansion

PillarVTP: vehicle trajectory prediction method based on local point cloud aggregation and receptive field expansion

Vibration Position Detection of Robot Arm Based on Feature Extraction of 3D Lidar.

In the process of construction, pouring and vibrating concrete on existing reinforced structures is a necessary process. This paper presents an automatic vibration position detecting method based on the feature extraction of 3D lidar point clouds. Compared with the image-based method, this method has better anti-interference performance to light with reduced computational consumption. First, lidar scans are used to capture multiple frames of local steel bar point clouds. Then, the clouds are stitched by Normal Distribution Transform (NDT) for preliminary matching and Iterative Closest Point (ICP) for fine-matching. The Graph-Based Optimization (g2o) method further refines the precision of the 3D registration. Afterwards, the 3D point clouds are projected into a 2D image. Finally, the locations of concrete vibration points and concrete casting points are discerned through point cloud and image processing technologies. Experiments demonstrate that the proposed automatic method outperforms ICP and NDT algorithms, reducing the mean square error (MSE) by 11.5% and 11.37%, respectively. The maximum discrepancies in identifying concrete vibration points and concrete casting points are 0.059 ± 0.031 m and 0.089 ± 0.0493 m, respectively, fulfilling the requirement for concrete vibration detection.

BEBOP VI. Enabling the detection of circumbinary planets orbiting double-lined binaries with the DOLBY method of radial–velocity extraction

ABSTRACT Circumbinary planets, orbiting both stars in a binary system, offer the opportunity to study planet formation and orbital migration in an environment different from that around single stars. However, despite the fact that $\gt 90~\% $ of binary systems in the solar neighbourhood are spectrally resolved double-lined binaries, there has been only one detection of a circumbinary planet orbiting a double-lined binary using the radial velocity method so far. Spectrally disentangling binary components is challenging due to blending of spectral lines and inaccuracies in spectral modelling. These inaccuracies add scatter to the measurements, which can hide the weak radial velocity signature of circumbinary exoplanets. We have obtained new high signal-to-noise, high-resolution spectra with the SOPHIE spectrograph, mounted on the 193 cm telescope at Observatoire de Haute-Provence (OHP), for six bright, double-lined binaries for which circumbinary exoplanet detection has been attempted in the past. To extract radial velocities, we use the DOLBY code, a recent method of spectral disentangling using Gaussian processes to model the time-varying components. We analyse the resulting radial velocities with a diffusive nested sampler to seek planets, and compute sensitivity limits. We do not detect any new circumbinary planet. However, we show that the combination of new data, new radial velocity extraction methods, and improved statistical methods to determine a data set’s sensitivity to planets leads to an approximately one order of magnitude improvement compared to previous results. This improvement brings us into the range of known circumbinary exoplanets and paves the way for future observation campaigns targeting double-lined binaries.

Comparing dark matter and MOND hyphotheses from the distribution function of A, F, early-G stars in the solar neighbourhood

ABSTRACT Dark matter is hypothetical matter assumed to address the historically known as missing mass problem in galaxies. However, alternative theories, such as Modified Newtonian Dynamics (MOND), have been notably successful in explaining the missing mass problem in various astrophysical systems. The vertical distribution function of stars in the solar neighbourhood serves as a proxy to constrain galactic dynamics in accordance to its contents. We employ both the vertical positional and velocity distribution of stars in cylindrical coordinates with a radius of 150 pc and a half-height of 200 pc from the galactic plane. Our tracers consist of main-sequence A, F, and early-G stars from the GAIA, RAVE, APOGEE, GALAH, and LAMOST catalogues. We attempt to solve the missing mass in the solar neighbourhood, interpreting it as either dark matter or MOND. Subsequently, we compare both hypotheses Newtonian gravity with dark matter and MOND, using the Bayes factor (BF) to determine which one is more favoured by the data. We found that the inferred dark matter in the solar neighbourhood is in range of $\sim (0.01 \!-\! 0.07) \, \textrm {M}_{\odot } \, \textrm {pc}^{-3}$. The wide range of inferred dark matter density is caused by the peculiar behaviour of F-type stars, which could be a sign of dynamical disequilibrium. We also determine that the MOND hypothesis’s acceleration parameter $a_0$ is $(1.26 \pm 0.13) \times 10^{-10} \, \textrm {m} \, \textrm {s}^{-2}$ for simple interpolating function. The average of BF for all tracers between the two hypotheses is $\log \textrm {BF}\sim 0.1$, meaning no strong evidence in favour of either the dark matter or MOND hypotheses.

Could very low-metallicity stars with rotation-dominated orbits have been driven by the bar?

The most metal-poor stars ( Fe/H are the ancient fossils from the early assembly epoch of our Galaxy. They very likely formed before the the thick disk. Recent studies have shown that a non-negligible fraction of them have prograde planar orbits, which means that their origin is a puzzle. It has been suggested that a later-formed rotating bar could have driven these old stars from the inner Galaxy outward and transformed their orbits so that they became more dominated by rotation. However, it is unclear whether this mechanism can explain these stars as observed in the solar neighborhood. We explore whether this scenario is feasible by tracing these stars backward in an axisymmetric Milky Way potential with a bar as perturber. We integrated their orbits backward for 6 Gyr under two bar models: one model with a constant pattern speed, and the other with a decelerating speed. Our experiments show that for the constantly rotating bar model, the stars of interest are little affected by the bar and cannot have been driven from a spheroidal inner Milky Way to their current orbits. In the extreme case of a decelerating bar, some of the very metal-poor stars on planar and prograde orbits can be brought from the inner Milky Way, but $ of them were nevertheless already dominated by rotation phi $ geq 1000 km s$^ $ kpc) 6 Gyr ago. The chance that these stars started with spheroid-like orbits with low rotation ($J_ phi $ lesssim 600 km s$^ $ kpc) is very low ($<$ 3$<!PCT!>$). We therefore conclude that within the solar neighborhood, the bar is unlikely to have shepherded a significant fraction of spheroid stars in the inner Galaxy to produce the overdensity of stars on prograde planar orbits that is observed today.

Compact and high excitation molecular clumps in the extended ultraviolet disk of M83

The extended ultraviolet (XUV) disks of nearby galaxies show ongoing massive-star formation, but their parental molecular clouds remain mostly undetected despite searches in CO(1-0) and CO(2-1). The recent detection of 23 clouds in the higher excitation transition CO(3-2) within the XUV disk of M83 thus requires an explanation. We test the hypothesis introduced to explain the non-detections and recent detection simultaneously: The clouds in XUV disks have a clump-envelope structure similar to those in Galactic star-forming clouds, having dense star-forming clumps (or concentrations of multiple clumps) at their centers, which predominantly contribute to the CO(3-2) emission and are surrounded by less dense envelopes, where CO molecules are photo-dissociated due to the low-metallicity environment there. We utilized new high-resolution ALMA CO(3-2) observations of a subset (11) of the 23 clouds in the XUV disk of M83. We confirm the compactness of the CO(3-2)-emitting dense clumps (or their concentrations), finding clump diameters below the spatial resolution of 6-9 pc. This is similar to the size of the dense gas region in the Orion A molecular cloud, a local star-forming cloud with massive-star formation. The dense star-forming clumps are common between normal and XUV disks. This may also indicate that once the cloud structure is set, the process of star formation is governed by the cloud's internal physics rather than by external triggers. This simple model explains the current observations of clouds with ongoing massive-star formation, although it may require some adjustment, for example including the effect of cloud evolution, to describe star formation in molecular clouds more generally.

Local H i absorption towards the magellanic cloud foreground using ASKAP

ABSTRACT We present the largest Galactic neutral hydrogen H i absorption survey to date, utilizing the Australian SKA Pathfinder Telescope at an unprecedented spatial resolution of 30 arcsec. This survey, GASKAP-H i, unbiasedly targets 2714 continuum background sources over 250 square degrees in the direction of the Magellanic Clouds, a significant increase compared to a total of 373 sources observed by previous Galactic absorption surveys across the entire Milky Way. We aim to investigate the physical properties of cold (CNM) and warm (WNM) neutral atomic gas in the Milky Way foreground, characterized by two prominent filaments at high Galactic latitudes (between $-45^{\circ }$ and $-25^{\circ }$). We detected strong H i absorption along 462 lines of sight above the 3$\sigma$ threshold, achieving an absorption detection rate of 17 per cent. GASKAP-H i’s unprecedented angular resolution allows for simultaneous absorption and emission measurements to sample almost the same gas clouds along a line of sight. A joint Gaussian decomposition is then applied to absorption-emission spectra to provide direct estimates of H i optical depths, temperatures, and column densities for the CNM and WNM components. The thermal properties of CNM components are consistent with those previously observed along a wide range of Solar neighbourhood environments, indicating that cold H i properties are widely prevalent throughout the local interstellar medium. Across our region of interest, CNM accounts for $\sim$30 per cent of the total H i gas, with the CNM fraction increasing with column density towards the two filaments. Our analysis reveals an anticorrelation between CNM temperature and its optical depth, which implies that CNM with lower optical depth leads to a higher temperature.

Self-interacting scalar dark matter around binary black holes

Gravitational waves can provide crucial insights about the environments in which black holes live. In this work, we use numerical relativity simulations to study the behavior of self-interacting scalar (wavelike) dark matter clouds accreting onto isolated and binary black holes. We find that repulsive self-interactions smoothen the “spike” of an isolated black hole and saturate the density. Attractive self-interactions enhance the growth and result in more cuspy profiles, but can become unstable and undergo explosions akin to the superradiant bosenova that reduce the local cloud density. We quantify the impact of self-interactions on an equal-mass black hole merger by computing the dephasing of the gravitational-wave signal for a range of couplings. We find that repulsive self-interactions saturate the density of the cloud, thereby reducing the dephasing. For attractive self-interactions, the dephasing may be larger, but if these interactions dominate prior to the merger, the dark matter can undergo bosenova during the inspiral phase, disrupting the cloud and subsequently reducing the dephasing. Published by the American Physical Society 2024

Nucleosynthesis Contribution of Neutrino-dominated Accretion Flows to the Solar Neighborhood

The elemental abundances of stars reflect the complex enrichment history of the Galaxy. To explore and explain the metal enrichment history of the cosmic environment near our solar system, we study the evolution of 56Fe abundance over time and [Mg/Fe] versus [Fe/H] evolution in the solar neighborhood. Core-collapse supernovae make the dominant contribution in the early stages, while Type Ia supernovae (SNe Ia) have a delayed and dominant impact in the later stages. In this work, we consider the nucleosynthesis contribution of neutrino-dominated accretion flows (NDAFs) formed at the end of the lives of massive stars. The results show that the [Fe/H] gradually increases over time and eventually reaches [Fe/H] = 0 and above, reproducing the chemical enrichment process in the solar neighborhood. Before the onset of SNe Ia, the ratio of 56Fe mass to the total gas mass increases by a factor of at most ∼1.44 when NDAFs are taken into account. We find that by including NDAF in our models, the agreement with the observed metallicity distribution of metal-poor stars in the solar neighborhood (<1 kpc) is improved while not significantly altering the location of the metallicity peak. This inclusion can also reproduce the observed evolutionary change of [Mg/Fe] at [Fe/H] ∼ −1.22, bringing the ratio to match the solar abundance. Our results provide an extensive understanding of metallicity evolution in solar environments by highlighting the nucleosynthesis contribution of NDAF outflows in the solar neighborhood.

Infrared surface brightness technique applied to RR Lyrae stars from the solar neighborhood

Context. The Baade-Wesselink (BW) method, also known as the pulsation parallax method, allows us to estimate distances to individual pulsating stars. Accurate geometric parallaxes obtained by the Gaia mission serve us in the calibration of the method and in the determination of its precision. This method also provides a way of determining mean radii of pulsating stars. Aims. The main aim of this work is to determine the scatter and possible dependence of p-factors of RR Lyrae stars on their pulsation periods. The secondary objective is to determine the mean radius-period relations for these stars. Methods. Our calibrations for RR Lyrae stars are based on photometric data gathered at the Cerro Murphy Observatory and parallaxes from the Data Release 3 of the Gaia space mission. We obtained spectroscopic data specifically for this project using high-resolution spectrographs. We used the infrared surface brightness (IRSB) version of the method that relies on a surface brightness-color relation that is dependent on the (V − K) color. It allows us to estimate stellar angular diameters, while tracing variations of the stellar radius using measurements of the stellar radial velocity obtained from spectroscopy. We present results based on four different empirical surface brightness-color relations, with three relations for dwarfs and subgiants and one for classical Cepheids. Results. We present our calibration of projection factors and determination of the mean radii for nine Galactic RR Lyrae stars. We obtained a spread of p-factors of around 0.07–0.08 for our sample of RR Lyrae stars from the solar neighborhood. However, depending on a given SBCR, we also found relations between the p-factor and the pulsation period for RRab stars with a root mean square (rms) scatter around the relation of around 0.05, but with relatively large uncertainty on the relation parameters. We also present relations between the mean radius and period for RR Lyrae pulsating in the fundamental mode with an rms scatter around the relation of 0.012 R⊙. We observe a clear offset between p-factors obtained using the IRSB technique (with a mean p value between 1.39 and 1.45) and values inferred using the SPIPS tool. This confirms that different implementations of the BW method are sensitive to various components of the p-factor. On the other hand, we obtain a similar scatter for p, as observed in a previous study based on the SPIPS tool. Our period-radius relations are in a good agreement with both the inference based on SPIPS and theoretical predictions.

The Imprint of Dark Matter on the Galactic Acceleration Field

Measurements of the accelerations of stars enabled by time-series extreme-precision spectroscopic observations, pulsar timing, and eclipsing binary stars in the solar neighborhood offer insights into the mass distribution of the Milky Way that do not rely on traditional equilibrium modeling. Given the measured accelerations, we can determine a total mass density and infer the amount of dark matter (DM) by accounting for the mass in stars, gas, and dust. Leveraging FIRE-2 simulations of Milky Way–mass galaxies we compare vertical acceleration profiles between cold DM (CDM) and self-interacting DM (SIDM) with a constant cross section of 1 cm2 g−1 across three halos with diverse assembly histories. Notably, significant asymmetries in vertical acceleration profiles near the midplane at fixed radii are observed in both CDM and SIDM, particularly in halos recently affected by mergers with satellites of Sagittarius/SMC-like masses or greater. These asymmetries offer a unique window into exploring the merger history of a galaxy. We show that SIDM halos manifest a more oblate shape and consistently exhibit higher local stellar and DM densities and steeper vertical acceleration gradients, up to 10%–30% steeper near the solar neighborhood. However, similar magnitude changes can arise from azimuthal variations in the baryonic components at a fixed radius and external influences like mergers, making it difficult to distinguish between CDM and SIDM using acceleration measurements in a single galaxy.

Deciphering the Kinematic Substructure of Local Dark Matter with LAMOST K Giants

Numerical simulations indicate that correlations exist between the velocity distributions of stars and dark matter (DM). We study the local DM velocity distribution based on these correlations. We select K giants from LAMOST DR8 cross-matched with Gaia DR3, which have robust measurements of velocity and metallicity, and separate them into the disk, halo substructure, and isotropic halo components in the chemodynamical space utilizing the Gaussian mixture model. The substructure component is highly radially anisotropic and possibly related to the Gaia–Enceladus–Sausage (GES) merger event, while the isotropic halo component is accreted from the earliest mergers following the Maxwell–Boltzmann distribution (standard halo model [SHM]). We find that the GES-like substructure contributes ∼85% of the local nondisk stars in the solar neighborhood, which is nearly invariant when applying different volume cuts or additional angular momentum constraints. Utilizing the metallicity–stellar mass relation and the stellar mass–halo mass relation, we find that ∼25−15+24% of local DM is in the kinematic substructure. Combined with the stellar distributions of nondisk components, we modify the heliocentric velocity distribution of local DM. It shifts to a lower speed with a sharper peak compared to the SHM and updates the detection limits of DM direct detection experiments. We discuss extensively the degeneracies present in the GMM fitting and propose that more kinematic and chemical information such as α abundance could help to break the degeneracy in the future. Our work confirms that the local DM velocity distribution deviates significantly from the SHM and needs to be properly accounted for in the DM detection experiments.

M giants with IGRINS

Context. Neutron-capture elements represent an important nucleosynthetic channel in the study of the Galactic chemical evolution of stellar populations. For stellar populations behind significant extinction, such as those in the Galactic centre and along the Galactic plane, abundance analyses based on near-infrared (NIR) spectra are necessary. Previously, spectral lines from the neutron-capture elements, such as copper (Cu), cerium (Ce), neodymium (Nd), and ytterbium (Yb), have been identified in the H band, while yttrium (Y) lines have been identified in the K band. Aims. Due to the scarcity of spectral lines from neutron-capture elements in the NIR, the addition of useful spectral lines from other neutron-capture elements is highly desirable. The aim of this work is to identify and characterise a spectral line suitable for abundance determination from the most commonly used s-process element, namely barium. Methods. We observed the NIR spectra of 37 M giants in the solar neighbourhood at high spectral resolution and with a high signal-to-noise ratio using the IGRINS spectrometer on the GEMINI South telescope. The full H- and K-bands were recorded simultaneously at R = 45 000. Using a manual spectral synthesis method, we determined the fundamental stellar parameters for these stars and derived the barium abundance from the Ba line (6s5d 3D2 → 6s6p 3P2o) at λair = 23 253.56 Å in the K band. Results. We demonstrate that the Ba line in the K band at 2.33 μm (λ23 253.56) is useful for abundance analyses from the spectra of M giants. The line becomes progressively weaker at higher temperatures and is only useful in M giants and the coolest K giants at supersolar metallicities. Conclusions. We can now add Ba to the trends of the heavy elements Cu, Zn, Y, Ce, Nd, and Yb, which can be retrieved from high-resolution H- and K-band spectra. This opens up the study of nucleosynthetic channels, including the s-process and the r-process, in dust-obscured populations. Thus, these elements can be studied for heavily dust-obscured regions of the Galaxy, such as the Galactic centre.

A new measurement of the Galactic 12C/13C gradient from sensitive HCO+ absorption observations

We present a new constraint on the Galactic 12C/13C gradient with sensitive HCO+ absorption observations against strong continuum sources. The new measurements suffer less from beam dilution, optical depths, and chemical fractionation, allowing us to derive the isotopic ratios precisely. The measured 12C/13C ratio in the solar neighborhood (66±5) is consistent with those obtained from CH+. Two measurements toward the GC are 42.2±1.7 and 37.5±6.5. Though the values are a factor of two to three higher than those derived from dense gas tracers (e.g., H2CO, complex organic molecules) toward Sagittarius (Sgr) B2 regions, our results are consistent with the absorption measurements from c-C3H2 toward Sgr B2 (~40) and those from CH+ toward Sgr A* and Sgr B2(N) (&gt;30). We have calculated a new Galactic 12C/13C gradient of (6.4±1.9)RGC/kpc+(25.9±10.5) and found an increasing trend of the 12C/13C gradient obtained from high-density to low-density gas tracers, suggesting that opacity effects and chemical fractionation may have a strong impact on the isotopic ratios observed in high-density regions.

Filling in the blanks

Context. In the solar neighbourhood, only ∼2% of stars in the Gaia survey have a line-of-sight velocity (vlos) contained within the RVS catalogue. These limitations restrict conventional dynamical analysis, such as finding and studying substructures in the stellar halo. Aims. We aim to present and test a method to infer a probability density function (PDF) for the missing vlos of a star with 5D information within 2.5 kpc. This technique also allows us to infer the probability that a 5D star is associated with the Milky Way’s stellar Disc or the stellar Halo, which can be further decomposed into known stellar substructures. Methods. We use stars from the Gaia DR3 RVS catalogue to describe the local orbital structure in action space. The method is tested on a 6D Gaia DR3 RVS sample and a 6D Gaia sample crossmatched to ground-based spectroscopic surveys, stripped of their true vlos. The stars predicted vlos, membership probabilities, and inferred structure properties are then compared to the true 6D equivalents, allowing the method’s accuracy and limitations to be studied in detail. Results. Our predicted vlos PDFs are statistically consistent with the true vlos, with accurate uncertainties. We find that the vlos of Disc stars can be well-constrained, with a median uncertainty of 26 km s−1. Halo stars are typically less well-constrained with a median uncertainty of 72 km s−1, but those found likely to belong to Halo substructures can be better constrained. The dynamical properties of the total sample and subgroups, such as distributions of integrals of motion and velocities, are also accurately recovered. The group membership probabilities are statistically consistent with our initial labelling, allowing high-quality sets to be selected from 5D samples by choosing a trade-off between higher expected purity and decreasing expected completeness. Conclusions. We have developed a method to estimate 5D stars’ vlos and substructure membership. We have demonstrated that it is possible to find likely substructure members and statistically infer the group’s dynamical properties.

Massive White Dwarfs in the 100 pc Sample: Magnetism, Rotation, Pulsations, and the Merger Fraction

We present a detailed model atmosphere analysis of massive white dwarfs with M > 0.9 M ⊙ and T eff ≥ 11,000 K in the Montreal White Dwarf Database 100 pc sample and the Pan-STARRS footprint. We obtained follow-up optical spectroscopy of 109 objects with no previous spectral classification in the literature. Our spectroscopic follow-up is now complete for all 204 objects in the sample. We find 118 normal DA white dwarfs, including 45 massive DAs near the ZZ Ceti instability strip. There are no normal massive DBs: the six DBs in the sample are strongly magnetic and/or rapidly rotating. There are 20 massive DQ white dwarfs in our sample, and all are found in the crystallization sequence. In addition, 66 targets are magnetic (32% of the sample). We use magnetic white dwarf atmosphere models to constrain the field strength and geometry using offset dipole models. We also use magnetism, kinematics, and rotation measurements to constrain the fraction of merger remnant candidates among this population. The merger fraction of this sample increases from 25% for 0.9–1 M ⊙ white dwarfs to 49% for 1.2–1.3 M ⊙. However, this fraction is as high as 78−7+4 % for 1.1–1.2 M ⊙ white dwarfs. Previous works have demonstrated that 5%–9% of high-mass white dwarfs stop cooling for ∼8 Gyr due to the 22Ne distillation process, which leads to an overdensity of Q-branch stars in the solar neighborhood. We demonstrate that the overabundance of the merger remnant candidates in our sample is likely due to the same process.

CyberAIBot: Artificial Intelligence in an Intrusion Detection System for CyberSecurity in the IoT

The cyber ecosystem presents two interesting properties. Attackers and defenders are normally the same entity; a detailed knowledge of defensive strategies optimises an attack whereas a good defence, based on a layered structure also includes attacks. In addition, Artificial Intelligence (AI) provides new techniques and tools to both attackers and defenders such as Generative Adversarial Networks (GANs) based on Generators and Discriminators for impersonation or Deep Learning (DL) for exhaustive scanning. To address this dilemma, this article presents CyberAIBot: Artificial Intelligence in an Intrusion Detection System for CyberSecurity in the Internet of Things (IoT) aimed at Operational Technology (OT) and Information Technology (IT) network traffic. CyberAIBot is based on a Deep Learning management structure in a private or local edge cloud computing approach where AI makes decisions as close as possible to the source of data. CyberAIBot gradually detects, learns, and adapts to different cyber attacks. In detail, CyberAIBot uses Deep Learning (DL) technical clusters trained in specific attacks and a Deep Learning (DL) management cluster specialises in taking management decisions rather than technical evaluations. This management cluster supervises conflicting classifications from the deep learning technical clusters. CyberAIbot is trained against several datasets and its performance is evaluated between two classification algorithms, the Long Short-Term Memory (LSTM) networks and Support Vector Machines (SVMs). The SVM DL clusters learn faster (average 15x) although the LSTM DL clusters perform better (average 30%). The LSTM DL management cluster performs better than the SVM DL management cluster although it recognises fewer traffic types. The total number of data points analysed by CyberAIBot is 5.52E+08, equivalent to the distance between the planet Earth to the Moon in meters.

Optimization and performance improvement of distributed data storage in hybrid storage systems

With the rapid development of information technology, the storage and processing of massive data has become one of the important challenges facing the current computing field. Traditional centralized storage systems have been unable to meet the needs of big data applications, while distributed storage systems have become the infrastructure of modern data centers because of their high scalability and high availability. However, in practical applications, a single distributed storage model is often difficult to balance cost-effectiveness and performance requirements. Therefore, this paper proposes a hybrid storage system model combining local storage and cloud storage resources and discusses a series of optimization strategies for this model. The focus of the research is to improve the overall performance of the system through the design of intelligent data sharding, redundancy and fault tolerance mechanisms, and the application of effective load balancing technology. The effectiveness and superiority of the proposed method are verified by testing and analyzing several typical application scenarios on the experimental platform. The experimental results show that the optimized hybrid storage system not only significantly improves the speed of data access, but also effectively reduces the storage cost, demonstrating its potential in future large-scale data management.

The California Legacy Survey. V. Chromospheric Activity Cycles in Main-sequence Stars

We present optical spectroscopy of 710 solar neighborhood stars collected over 20 years to catalog chromospheric activity and search for stellar activity cycles. The California Legacy Survey stars are amenable to exoplanet detection using precise radial velocities, and we present their Ca ii H and K time series as a proxy for stellar and chromospheric activity. Using the High Resolution Echelle Spectrometer at Keck Observatory, we measured stellar flux in the cores of the Ca ii H and K lines to determine S-values on the Mount Wilson scale and the log(RHK′) metric, which is comparable across a wide range of spectral types. From the 710 stars, with 52,372 observations, 285 stars were sufficiently sampled to search for stellar activity cycles with periods of 2–25 yr, and 138 stars showed stellar cycles of varying length and amplitude. S-values can be used to mitigate stellar activity in the detection and characterization of exoplanets. We used them to probe stellar dynamos and to place the Sun's magnetic activity into context among solar neighborhood stars. Using precise stellar parameters and time-averaged activity measurements, we found tightly constrained cycle periods as a function of stellar temperature between log(RHK′) of −4.7 and −4.9, a range of activity in which nearly every star has a periodic cycle. These observations present the largest sample of spectroscopically determined stellar activity cycles to date.