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At least 703 records · Page 39

Kmt-2022-Blg-0440lb: A New q < 10 −4 Microlensing Planet With the Central-Resonant Caustic Degeneracy Broken

We present the observations and analysis of a high-magnification microlensing planetary event, KMT-2022-BLG-0440, for which the weak and short-lived planetary signal was covered by both the KMTNet survey and follow-up observations. The binary-lens models with a central caustic provide the best fits, with a planet/host mass ratio, q = 0.75–1.00 ×10 −4 at 1 σ. The binary-lens models with a resonant caustic and a brown-dwarf mass ratio are both excluded by ∆χ 2 > 70. The binary-source model can fit the anomaly well but is rejected by the ‘colour argument’ on the second source. From Bayesian analyses, it is estimated that the host star is likely a K or M dwarf located in the Galactic disc, the planet probably has a Neptune-mass, and the projected planet-host separation is 1.9 +0.6 −0.7 or 4.6 +1.4 −1.7 au, subject to the close/wide de generac y. This is the third q < 10 −4 planet from a high-magnification planetary signal ( A ≳ 65). Together with another such planet, KMT-2021-BLG-0171Lb, the ongoing follow-up program for the KMTNet high-magnification events has demonstrated its ability to detect high-magnification planetary signals for q < 10 −4 planets, which are challenging for the current microlensing surveys.

planets and satellites: detection↗

Transfer-AE: A novel autoencoder-based impact detection model for structural digital twin

Accurately detecting the location and intensity of impacts is crucial for ensuring structural safety. Currently, AI-based structural impact detection methods are widely used for their excellent detection accuracy. However, their generalization capability is limited by the scenarios present in the training data. Many complex and dangerous impact scenarios are difficult to conduct real-world experiments on to collect sufficient samples. To capture all impact scenarios and fully leverage the advantages of AI-based detection technologies, advanced methods involve combining real-world structural monitoring data with corresponding numerical models to construct digital twins. These methods continuously refine the created numerical models with limited real-world data and provide diverse impact scenarios through numerical model simulations. However, there are inevitable differences between digital models and physical models that are challenging to correct through mechanical means. This discrepancy in data distribution between the two models significantly hinders the application of digital twin technology in impact/event identification tasks. To address this challenge, this study proposes a novel model based on autoencoders, named Transfer-AE. Transfer-AE encodes the common features of digital twins in the latent space to bridge the uncertainty gap at a macro scale between numerical models and physical models and synchronously fits the magnitude and location of the impact load in the decoder. This enables consistent detection results for the same impact event, whether the sample comes from the numerical model or the physical model. Transfer-AE includes two operating modes: Mode 1 has a fixed computational complexity with stable inference speed, but the training cost and difficulty increase with data distribution. Mode 2's computational complexity increases with data distribution, but it has a fixed training cost and speed. In both cases involving the geodesic dome structure simulating a deep space habitat and the IASC-ASCE benchmark structure, Transfer-AE demonstrated the best performance in impact localization and quantification tasks compared to mainstream domain-adaptive transfer models.

Chengjia Han↗

High-Performance Monitoring Architecture for Large-Scale Distributed Systems Using Event Filtering

Monitoring is an essential process to observe and improve the reliability and the performance of large-scale distributed (LSD) systems. In an LSD environment, a large number of events is generated by the system components during its execution or interaction with external objects (e.g. users or processes). Monitoring such events is necessary for observing the run-time behavior of LSD systems and providing status information required for debugging, tuning and managing such applications. However, correlated events are generated concurrently and could be distributed in various locations in the applications environment which complicates the management decisions process and thereby makes monitoring LSD systems an intricate task. We propose a scalable high-performance monitoring architecture for LSD systems to detect and classify interesting local and global events and disseminate the monitoring information to the corresponding end- points management applications such as debugging and reactive control tools to improve the application performance and reliability. A large volume of events may be generated due to the extensive demands of the monitoring applications and the high interaction of LSD systems. The monitoring architecture employs a high-performance event filtering mechanism to efficiently process the large volume of event traffic generated by LSD systems and minimize the intrusiveness of the monitoring process by reducing the event traffic flow in the system and distributing the monitoring computation. Our architecture also supports dynamic and flexible reconfiguration of the monitoring mechanism via its Instrumentation and subscription components. As a case study, we show how our monitoring architecture can be utilized to improve the reliability and the performance of the Interactive Remote Instruction (IRI) system which is a large-scale distributed system for collaborative distance learning. The filtering mechanism represents an Intrinsic component integrated with the monitoring architecture to reduce the volume of event traffic flow in the system, and thereby reduce the intrusiveness of the monitoring process. We are developing an event filtering architecture to efficiently process the large volume of event traffic generated by LSD systems (such as distributed interactive applications). This filtering architecture is used to monitor collaborative distance learning application for obtaining debugging and feedback information. Our architecture supports the dynamic (re)configuration and optimization of event filters in large-scale distributed systems. Our work represents a major contribution by (1) survey and evaluating existing event filtering mechanisms In supporting monitoring LSD systems and (2) devising an integrated scalable high- performance architecture of event filtering that spans several kev application domains, presenting techniques to improve the functionality, performance and scalability. This paper describes the primary characteristics and challenges of developing high-performance event filtering for monitoring LSD systems. We survey existing event filtering mechanisms and explain key characteristics for each technique. In addition, we discuss limitations with existing event filtering mechanisms and outline how our architecture will improve key aspects of event filtering.

Maly, K.↗

Detection of a proton beam during the impulsive phase of a stellar flare

A transient event consistent with the predicted temporal and spectral signatures of an energetic proton beam was detected in the impulsive phase of a small flare on the red dwarf star AU Microscopii. It consisted of a prominent increase in the flux in the red wing of Lyman-alpha near 1223 A, simultaneously with the peak of a flare observed in the 1206 A transition region line of Si III. The probability that the red wing event was a chance fluctuation is one chance in 2.5 x 10 exp 4. This observation represents a confirmation of the prediction by Orrall and Zirker (1976) in which downstreaming protons accelerated during the impulsive phase of a flare charge exchange with ambient neutral hydrogen and emit Lyman-alpha radiation from 1 to 15 A redward of line center.

Woodgate, Bruce E.↗

Constraints to the decays of Dirac neutrinos from SN 1987A

The decay mode of a keV-mass Dirac neutrino is addressed with reference to the nineteen neutrino events associated with SN 1987A that were detected by the Kamiokande II and Irvine-Brookhaven-Michigan detectors. A complementary constraint is presented which is based upon a distinctive signal associated with the decay of wrong-helicity neutrinos that was not seen: high-energy (50 MeV and higher) neutrino events. The absence of such events excludes the decay of wrong-helicity neutrinos into proper-helicity neutrinos for a Dirac neutrino of mass between 1 and 300 keV. The constraint also rules out models of the 17-keV neutrino.

Dodelson, Scott↗

Periodic Impact Cratering and Extinction Events Over the Last 260 Million Years

The claims of periodicity in impact cratering and biological extinction events are controversial. Anewly revised record of dated impact craters has been analyzed for periodicity, and compared with the record of extinctions over the past 260 Myr. A digital circular spectral analysis of 37 crater ages (ranging in age from 15 to 254 Myr ago) yielded evidence for a significant 25.8 +/- 0.6 Myr cycle. Using the same method, we found a significant 27.0 +/- 0.7 Myr cycle in the dates of the eight recognized marine extinction events over the same period. The cycles detected in impacts and extinctions have a similar phase. The impact crater dataset shows 11 apparent peaks in the last 260 Myr, at least 5 of which correlate closely with significant extinction peaks. These results suggest that the hypothesis of periodic impacts and extinction events is still viable.

extinction↗

Kankakee Water Resources: Monitoring Temperature and Vegetation to Detect River Flow Impediments at Energy Intake Structures

In recent years, unpredictable grassing events have occurred at the Dresden Generating Station, located on the Kankakee River in northern Illinois. Grassing events are characterized by large mats of aquatic vegetation that accumulate downstream, resulting in the clogging of water intake structures and leading to major disruptions in power generation. Currently, employees at the Dresden Generating Station are responsible for reactively responding to each grassing event individually. This project, in partnership with Constellation Nuclear and the United States Geological Survey (USGS), assessed the feasibility of using Earth observations (Landsat 9 OLI-2, Landsat 8 OLI, Sentinel-2 MSI, DOVE PlanetScope, WorldView-3, and GPM IMERG) to detect floating aquatic vegetation within the Kankakee River and identify predictive factors that trigger grassing events, as doing so will provide the Dresden Generating Station the ability to anticipate future grassing events and enhance general hydrologic modeling efforts held by the USGS. The results of this study illustrated that, while aquatic vegetation can be detected by satellites with up to moderate spatial resolution (30 m), temporal resolution is a major limiting factor for tracking movements in floating aquatic vegetation and identifying predictive measures for these events. In addition, correlation results suggest a possible negative relationship between grassing events and river discharge (-0.875 correlation coefficient). In the future, pairing these results with ground control surveys and sensors with higher temporal capabilities would allow our project partners to predict and proactively address future grassing events, ensuring the reliable operation of the Dresden Generating Station.

Marisa Smedsrud↗

Effect of detector dead time on the performance of optical direct-detection communication links

Avalanche photodiodes (APDs) operating in the Geiger mode can provide a significantly improved single-photon detection sensitivity over conventional photodiodes. However, the quenching circuit required to remove the excess charge carriers after each photon event can introduce an undesirable dead time into the detection process. The effect of this detector dead time on the performance of a binary pulse-position-modulated (PPM) channel is studied by analyzing the error probability. It is shown that, when background noise is negligible, the performance of the detector with dead time is similar to that of a quantum-limited receiver. For systems with increasing background intensities, the error rate of the receiver starts to degrade rapidly with increasing dead time. The power penalty due to detector dead time is also evaluated and shown to depend critically on badkground intensity as well as dead time. Given the expected background strength in an optical channel, therefore, a constraint must be placed on the bandwidth of the receiver to limit the amount of power penalty due to detector dead time.

Chen, C.-C.↗

Aspects of clear air turbulence severity forecasting and detection

Factors influencing the accuracy of the forecasts of incidences of clear air turbulence (CAT) are discussed, along with techniques for improved verification. Descriptive ranking terms for the intensity of CAT events, ranging from light to extreme, are developed, and meteorological parameters used for predictions are reviewed, including jetstream core location, vertical and horizontal wind shears, stable layers, tropopause height, trough speed, 500-mb vorticity, surface fronts, pressure centers and cyclogenesis, and wind speeds near mountain ridges. Methods of remote detection of CAT, particularly by using radiometry sensitive to the IR water vapor band, are noted to have had some success in detecting actual CAT events and decreasing false alarms. Statistical aspects of CAT encounter severity are discussed, including the establishment of confidence intervals for thresholds of detection of CATs of varying intensities.

Ehernberger, L. J.↗

Effect of Detector Dead Time on the Performance of Optical Direct-Detection Communication Links

Avalanche photodiodes (APDs) operating in the Geiger mode can provide a significantly improved single-photon detect ion sensitivity over conventional photodiodes. However, the quenching circuit required to remove the excess charge carriers after each photon event can introduce an undesirable dead time into the detection process. The effect of this detector dead time on the performance of a binary pulse-position-modulted (PPM) channel is studied by analyzing the error probability. It is shown that, when back- ground noise is negligible, the performance of the detector with dead time is similar to that o f a quantum-limited receiver. For systems with increasing background intensities, the error rate of the receiver starts to degrade rapidly with increasing dead time. The power penalty due to detector dead time is also evaluated and shown to depend critically on background intensity as well as dead time. Given the expected background strength in an optical channel, therefore, a constraint must be placed on the bandwidth of the receiver to limit the amount of power penalty due to detector dead time.

Chen, C.-C.↗

Temporal and Spatial Evolution of Nanoflare Heating in Solar AR

Nanoflares are thought to be prime candidates to heat the solar non-flaring active regions. However, their direct individual detection with current instrumentation remains challenging. Understanding the frequency and magnitude of nanoflares is crucial for understanding their role in coronal heating. In this study, we employ a field-aligned hydrodynamic model to simulate the evolution of an active region (AR) under nanoflare heating scenarios. By comparing the simulated emission with EUV and X-ray observations, we determine the frequency of heating events and investigate how it evolves with the AR evolution. Additionally, we analyze the impact of observational parameters, such as instrument spatial resolution and energy band, on estimating nanoflare properties. Our findings contribute to advancing our understanding of the role of nanoflares in coronal heating and refining observational parameters for detecting these events.

nano flare↗

Distribution of whistler mode bursts at Venus

Several thousand impulsive whistler mode noise bursts were detected by the Pioneer Venus wave instrument during the first 10 seasons with nightside traversals at low altitudes. The altitude distribution for these events shows that essentially all of the bursts were detected when the orbiter was less than 2000 km above the planet, suggesting that the varying plasma conditions could not maintain coherent whistler mode field-aligned guidance over greater distances. Within the 2000-km range, the distribution of the number of events versus altitude shows that there are two distinct subregions. These results are interpreted in terms of two types of whistler mode propagation from sources below the ionosphere.

Scarf, F. L.↗

Dynamic phenomena in sunspots

A detailed summary of observed dynamic phenomena associated with sunspots is presented, together with a description of the observational techniques and available analytical formulations for the processes under study. The phenomena detected thus far are grouped into aperiodic events and oscillations and waves. Aperiodic phenomena comprise umbral flares, the superpenumbra, and inverse Evershed flow. Internal, aperiodic manifestations include penumbral grains, the photospheric penumbral dark fibrils, Evershed flow, umbral dots, the inhomogeneity of the umbral magnetic field, and umbral turbulence. Oscillations and flashes are seen in the umbra, while running waves and dark puffs have been detected in the penumbra, and oscillations are located in the photosphere. All the observed features are evidence of mass motion and change on time scales of less than an hour.

Moore, R. L.↗

Gravity waves and convection in Colorado during July 1983

The dynamics of gravity-wave/convective-cell interaction is studied using NOAA data collected in NE Colorado during July and August 1983. The pressure fields measured with microbarographs, the tropospheric wind profiles obtained with a UHF wind profiler radar, and precipitation data collected with a 10-cm weather radar for four events (A, B, C, and D) are analyzed. The four disturbances are detected through a substantial depth of the troposphere. It is observed that in event A the wave and convective cells appear to be locked together; in event B, the wave and convective cells commence about the same time, but the wave velocities differ from the cell velocities; and in events C and D, the waves move faster than the maximum wind in the jet and faster than the convective cells. It is suggested that events A and B are generated by wind shear in the jet stream, and the excitation of events C and D depends on mechanisms such as vertical convective motion and acceleration in the jet flow.

Einaudi, F.↗

KMT-2021-BLG-0171Lb and KMT-2021-BLG-1689Lb: Two Microlensing Planets in the KMTNet High-Cadence Fields With Followup Observations

Follow-up observations of high-magnification gravitational microlensing events can fully exploit their intrinsic sensitivity to detect extrasolar planets, especially those with small mass ratios. To make followup observations more uniform and efficient, we develop a system, HighMagFinder, to automatically alert possible ongoing high-magnification events based on the real-time data from the Korea Microlensing Telescope Network (KMTNet). We started a new phase of follow-up observations with the help of HighMagFinder in 2021. Here we report the discovery of two planets in high-magnification microlensing events, KMT- 2021-BLG-0171 and KMT-2021-BLG-1689, which were identified by the HighMagFinder. We find that both events suffer the ‘central-resonant’ caustic degeneracy. The planet-host mass-ratio is q ∼4.7 × 10 −5 or q ∼2.2 × 10 −5 for KMT-2021-BLG-0171, and q ∼2.5 × 10 −4 or q ∼1.8 × 10 −4 for KMT-2021-BLG-1689. Together with two other events, four cases that suffer such degeneracy have been discovered in the 2021 season alone, indicating that the de generate solutions may have been missed in some previous studies. We also propose a quantitative factor to weight the probability of each solution from the phase space. The resonant interpretations for the two events are disfavoured under this consideration. This factor can be included in future statistical studies to weight degenerate solutions.

Micro gravitational lensing↗

Open-source Techniques for Automated Landslide Inventory Generation for Rapid Response

Manual mapping is the most used method for generating landslide inventories. For rapid response scenario this method becomes tedious and time consuming. The Landslide team at NASA Goddard Space Flight Center has been developing open-source landslide mapping systems for rapid generation of landslide inventories. We have developed a Python-based landslide mapping framework known as the Semi-Automatic Landslide Detection (SALaD) system that uses Object-based Image Analysis and machine learning. For production of event-based inventories, SALaD was modified to include a change detection module (SALaD-CD). Utilizing high-resolution imagery form from Planet and Maxar, we have generated multiple rapid response landslide inventories that have been used by emergency responders on the ground, the NASA Disasters program, and academia. Currently, we are exploiting deep learning frameworks for landslide mapping. We are interested to learn about efficient way to harmonize multi-sensor data for creating a long-term record of landslides, training strategies and ongoing deep learning-based efforts for natural hazard characterization within NASA and UMD.

Pukar Amatya↗

Occultation detection of a Neptune ring segment

A stellar occulation event of Neptune revealed a ring segment that was previously undetected. It appears that the object is not a complete ring, but rather a localized swarm of particles which follows a ring orbit over a limited range of longitudes. To avoid confusion with the standard use of the word ring it is suggested that the feature be called an arc. The distance of the arc zone is not precisely known because so far there has been no confirmed occultation by both an arc and the planet.

Hubbard, W. B.↗