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The physics potential of timing layers with a few tens of pico-second resolution in the calorimeters of future collider detectors is explored here. These studies show how such layers can be used for particle identification and illustrate the potential for detecting new event signatures originating from physics beyond the standard model.
Detecting and analyzing complex patterns in multivariate time-series data is crucial for decision-making in urban and environmental system operations. However, challenges arise from the high dimensionality, intricate complexity, and interconnected nature of complex patterns, which hinder the understanding of their underlying physical processes. Existing AI methods often face limitations in interpretability, computational efficiency, and scalability, reducing their applicability in real-world scenarios. This paper proposes a novel visual analytics framework that integrates two generative AI models, Temporal Fusion Transformer (TFT) and Variational Autoencoders (VAEs), to reduce complex patterns into lower-dimensional latent spaces and visualize them in 2D using dimensionality reduction techniques such as PCA, t-SNE, and UMAP with DBSCAN. These visualizations, presented through coordinated and interactive views and tailored glyphs, enable intuitive exploration of complex multivariate temporal patterns, identifying patterns’ similarities and uncover their potential correlations for a better interpretability of the AI outputs. The framework is demonstrated through a case study on power grid signal data, where it identifies multi-label grid event signatures, including faults and anomalies with diverse root causes. Additionally, novel metrics and visualizations are introduced to validate the models and assess the performance, efficiency, and consistency of latent maps generated by VAE, which have been utilized in prior studies for latent space cartography and used as a benchmark in this study, and the emerging TFT architecture under various configurations. These analyses provide actionable insights for model parameter tuning and reliability improvements. Comparative results highlight that TFT achieves shorter run times and superior scalability to diverse time-series data shapes compared to VAE. This work advances fault diagnosis in multivariate time series, fostering explainable AI to support critical system operations.
In this study, a phase fault detection algorithm is developed by employing the envelope detector method. The proposed method diagnoses faults among phases and defines fault areas in the incoming signal. The designed algorithm consists of three steps: analytical signal conversion, complex magnitude, and fault detection. Initially, an analytical signal is obtained from the incoming power signal to determine the instantaneous amplitude and phase of the signal. A complex magnitude operation is applied to analytical signals to display changes in amplitude. On the basis of the threshold values specified by the user, the last step identifies the distortion signal in terms of the type of error and size. The proposed method is tested with realistically simulated substation power signal data and real power system data from the Grid Event Signature Library. The obtained results revealed that the proposed method detects distortions accurately.
The discovery of `event signatures' and useful insights from very large historical Phasor Measurement Unit (PMU) datasets is predicated on offline Big Data analysis approaches that rely on the generation of predictive features on a massive scale. This paper presents lessons learned from a data platform perspective towards reducing barriers to adoption of Big Data analytics against a real dataset of almost half a trillion data points drawn from over 400 PMUs distributed across the North American power grid. We demonstrate software abstractions and targeted performance optimizations that can lead to significant productivity gains for power systems researchers seeking to perform offline exploratory temporal analysis and modeling tasks, with a focus on feature generation. We describe how our optimized approach goes beyond a naive application of mainstream Big Data technologies, enabling feature generation tasks, that previously took days or even weeks, to now be completed in just a few hours.
This study proposes a novel method for signal detection and feature extraction based on the spectral correlation function, enabling improved characterization of grid-signal distortions. Our approach differs from existing treatments of signal distortion in its analysis of the varied spectral content of signals observed in real-world scenarios. The method we propose has state-of-the-art discriminative power that provides meaningful and understandable characterizations of various grid events and anomalies. In conclusion, to validate the approach, we use real world data from the Grid Event Signature Library, which is maintained jointly by Oak Ridge National Laboratory and Lawrence Livermore National Laboratory.
This paper presents a measurement of the electroweak production of two jets in association with a Zγ pair, with the Z boson decaying into two neutrinos. It also presents a search for invisible or partially invisible decays of a Higgs boson with a mass of 125 GeV produced through vector-boson fusion with a photon in the final state. These results use data from LHC proton–proton collisions at $\sqrt{s}$ = 13 TeV collected with the ATLAS detector and corresponding to an integrated luminosity of 139 fb -1 . The event signature, shared by all benchmark processes considered for the measurements and searches, is characterized by a significant amount of unbalanced transverse momentum and a photon in the final state, in addition to a pair of forward jets. Electroweak $Zγ$ production in association with two jets is observed in this final state with a significance of 5.2 (5.1 expected) standard deviations. The measured fiducial cross-section for this process is 1.31 ± 0.29 fb. An observed (expected) upper limit of 0.37 (0.34$^{+0.15}_{-0.10}$) at 95% confidence level is set on the branching ratio of a 125 GeV Higgs boson to invisible particles, assuming the Standard Model production cross-section. The signature is also interpreted in the context of decays of a Higgs boson into a photon and a dark photon. An observed (expected) 95% CL upper limit on the branching ratio for this decay is set at 0.018 (0.017$^{+0.007}_{-0.005}$), assuming the Standard Model production cross-section for a 125 GeV Higgs boson.
The research objective of the supported work was to search for neutrinoless double-beta decay in 76 Ge and investigate and identify backgrounds to a double-beta decay search. Understanding the neutrino mass generation mechanism, the absolute neutrino mass scale, the neutrino mass spectrum, and the possible Majorana nature of neutrinos are some of the future discoveries of the next generation neutrino experiments. The Majorana collaboration operated the Demonstrator experiment comprising 44 kg (30 kg enriched in 76 Ge) of Ge detectors in total split between two modules contained in a low background shield at the Sanford Underground Research Facility in Lead, South Dakota. Observation of 0νββ would have profound implications for the Standard Model of particle physics by demonstrating that neutrinos are Majorana particles, that lepton number is not conserved, and it would provide a measure of the effective Majorana neutrino mass. The decay rate of 0νββ is incredibly small and may only produce a few signature events in a detector per year. Therefore, observation of this rare process demands a careful study and implementation of signal processing, detector design, and new levels of background suppression.
The U.S. DOE and the Electric Power Research Institute convened a wildfire advisory group to bring together knowledge of ignition risks, electric utility needs, the applicability of available technology, and existing technology gaps. The outcome is a five-year action plan, containing recommendations on RD&D projects, that if completed by the year 2030, may accelerate the power industry’s ability to substantially reduce wildfire ignition risks. When reviewing this document please consider it is a snapshot in time for the years 2023 and 2024, could be obsolete by the end of the decade. The following list comprises the titles and topics for the proposed follow-on demonstrations: 1. Hybrid Undergrounding RD&D, 2. Live Downed Conductor Detection RD&D, 3. Fault Energy Reduction RD&D, 4. Advanced Inspection and Response Drone, 5. Fault and PQ Event Signature Repository, 6. Advanced and Intelligent Sensor Nodes, 7. Fire Friendly Asset Coatings and Coverings, and 8. Environmental Monitoring Action Plan.
Oscillation detection and mitigation is a crucial aspect of reliable power system operation. Several transmission system operators and reliability coordinators use the RMS-energy method of oscillation detection, but the process of setting thresholds is time and labor intensive. The current industry practice in the United States is to set thresholds based on the RMS-energy's value during ambient conditions, which can often lead to nuisance alarms that require thresholds to be manually retuned. In this paper, we propose a method for setting RMS-energy thresholds that directly accounts for oscillation amplitudes specified by the user. A theoretical analysis of the statistical properties of the RMS-energy incorporates these user-specified amplitudes, resulting in thresholds that reliably detect oscillations of interest while avoiding nuisance alarms. Theoretical results are validated with simulated measurements and the real-world practicality of the method is established with publicly available field-measured data from the Grid Event Signature Library.
A review of theoretical and observational research on the magnetopause during 1987-1990. Starting with recent work on magnetic reconnection, the review proceeds to magnetopause surface wave phenomena, including the controversy over the role of solar wind pressure pulses in the coupling process and in the mimicking of flux transfer events signatures, and finishes with the magnetopause structure and associated wave phenomena. Recent advances in computer modeling of the magnetopause and the pertinent processes are also discussed.
The Mars Reconnaissance Orbiter (MRO) continues its dual-mode mission of scientific exploration and programmatic support. Now in its 13th year of flight (and its 12th year in its low-altitude, sun-synchronous orbit around Mars), the spacecraft continues in its normal flight mode and its science instruments continue to acquire a treasure trove of data which is being used to study the Martian environment (surface, sub-surface, and atmosphere). To date (July 2018), more than 333 TB of scientific data have been returned to Earth. Building onto the 2017 IAC paper: “The Mars Reconnaissance Orbiter Mission: Continuing a Record of Exploration from Mars Orbit,” [1] this paper provides a 2018 status update on the MRO Mission. A signature event since the 2017 writing is the onset and evolution of a planet-encircling dust event (PEDE), the first such event since 2007. Additional recent science highlights for MRO include the discovery of mid-latitude ice cliffs, polar cap characterization, daily global mapping of the 2018 PEDE dust activity and the atmospheric thermal response, further characterization of the tantalizing recurring slope lineae (RSL), and continued detection of surface changes. Programmatically, UHF relay support for the Mars Science Laboratory (MSL) rover Curiosity and the Mars Exploration Rover (MER) rover Opportunity continues at a pace that provides the engineers and scientists operating those surface vehicles timely information to support their mission planning and science analysis. Most of the landing site characterization requests for the NASA Mars 2020 rover and the ESA ExoMars Rover/Surface Platform (RSP) missions have been completed, with final acquisitions delayed due to the obscuring dust haze from the current PEDE. In parallel, the flight team has faced new engineering challenges as the spacecraft has aged. The team has developed and is implementing actions that are aimed at stretching spacecraft battery life. A new all-stellar capability using the spacecraft’s star trackers now allows for normal spacecraft operations without IMUs. In addition to its current relay duties, MRO will be synchronized to provide critical communications support for the InSight Entry, Descent, and Landing (EDL) event on November 26, 2018, and will be readied to support InSight’s critical commissioning phase with UHF relay support and environmental characterization. A new split-pass relay capability has been developed which will allow MRO to relay with two surface vehicles in “close proximity” on the same overflight, i.e. the InSight lander and the Curiosity rover. Extended for another year of operations by NASA, this paper will highlight recent scientific progress and describe actions that will extend MRO’s life well into the 2020’s as a key element of the Mars Exploration Program.
Results are presented of a search for a heavy Majorana neutrino Image 1 decaying into two same-flavor leptons ℓ (electrons or muons) and a quark-pair jet. A model is considered in which the Image 1 is an excited neutrino in a compositeness scenario. The analysis is performed using a sample of proton-proton collisions at s = 13 TeV recorded by the CMS experiment at the CERN LHC, corresponding to an integrated luminosity of 138 fb − 1 . The data are found to be in agreement with the standard model prediction. For the process in which the Image 1 is produced in association with a lepton, followed by the decay of the Image 1 to a same-flavor lepton and a quark pair, an upper limit at 95% confidence level on the product of the cross section and branching fraction is obtained as a function of the Image 1 mass Image 2 and the compositeness scale Λ. For this model the data exclude the existence of Image 3 (Image 4) for Image 2 below 6.0 (6.1) TeV, at the limit where Image 2 is equal to Λ. For Image 5, values of Λ less than 20 (23) TeV are excluded. These results represent a considerable improvement in sensitivity, covering a larger parameter space than previous searches in Image 6 collisions at 13 TeV.
It is suggested that existing data on the 1908 Tunguska fall precludes an interpretation of the object as an either active or extinct comet fragment. Because a fireball of the Tunguska mass is not efficiently decelerated by the earth's atmosphere, it would at an entry velocity of about 30 km/sec have had to resist aerodynamic pressures greater than one billon dyn/sq cm before disintegrating. The inherently extremely fragile cometary material could not have survived a load of this magnitude. The data on Type II fireballs with prominent terminal flares are extrapolated, to estimate Tunguska's critical dynamic pressure at the same time of explosion as being of the order of 200 million dyn/sq cm, and its preexplosion velocity as about 10 km/sec, thereby ruling out a comet-like orbit. The Tunguska object is most consistently described as a small Apollo-type asteroid, 90-190 m across.
The six largest known impact craters of the last 250 Myr (greater than or equal to 70 km in diameter), which are capable of causing significant environmental damage, coincide with four times of recognized extinction events at 36 (with 2 craters), 66, and 145 Myr ago, and possibly with two provisional extinction events at 168 and 215 Myr ago. These impact cratering events are accompanied by layers in the geologic record interpreted as impact ejecta. Chance occurrences of impacts and extinctions can be rejected at confidence levels of 99.96 percent (for 4 impact/extinctions) to 99.99 percent (for 6 impact/extinctions). These results argue that several extinction events over the last 250 Myr may be related to the effects of large-body impacts.
Questions regarding the mechanism by which the large-scale cross-tail electric field and associated convection in the magnetosphere is maintained have not yet been completely answered. According to Dungey (1961), the boundary layer (BL) inside the magnetopause (MP) in which the tailward transport of mass, momentum, and magnetic flux takes place can be produced by reconnection. Observations made with the aid of the ISEE spacecraft show that reconnection can occur both in a quasisteady form and in a more unsteady form known under the name 'flux transfer event' (FTE). The present investigation proposes observation of the ground signature of an FTE. It is pointed out that the STARE radar system has the potential for making observations pertinent to identifying and studying the ionospheric signatures of FTE's. An analysis is conducted of two periods during which the convective boundary (CB) moved into the STARE field of view. The significance of the observations is discussed.
This thesis reports a study of the prospects of using calorimetry for separating photon- from electron-initiated electromagnetic (EM) showers in liquid argon time projection chambers (LArTPCs), a prevalent need for neutrino oscillation experiments based on the LArTPC technology as $\gamma$-initiated showers are a significant background to electron neutrino ($\nu_e$) events, whose signature is electron showers. From events simulated in the LArIAT (Liquid Argon In A Testbeam) experiment's detector, we quantitatively evaluated the dependence of the calorimetric separation on the initial momentum and position (along the beamline) of the primary particle. We could conclude that the separation is more efficient if the primary particle is created inside the chamber, whereas the impact of the momentum is not as significant. Furthermore, a first step was taken towards applying the calorimetric method to the showers measured in LArIAT. A convolutional neural network (CNN) trained on simulation was deployed to find EM showers among the events collected by the experiment. The charge deposition at the beginning of the showers found is centered at a plausible value, although the width of the distribution demands further inquiry.
Flux transfer events (FTEs) were originally identified by transient bipolar variations of the magnetic field component normal to the nominal magnetopause centered on enhancements in the total magnetic field strength. Recent Cluster and THEMIS multi-point measurements provided a wide range of signatures that are interpreted as evidence for FTE passage (e.g., crater FTE's, traveling magnetic erosion regions). We use the global magnetohydrodynamic (MHD) code BATS-R-US developed at the University of Michigan to model the global three-dimensional structure and temporal evolution of FTEs during multi-spacecraft magnetopause crossing events. Comparison of observed and simulated signatures and sensitivity analysis of the results to the probe location will be presented. We will demonstrate a variety of observable signatures in magnetic field profile that depend on space probe location with respect to the FTE passage. The global structure of FTEs will be illustrated using advanced visualization tools developed at the Community Coordinated Modeling Center
Protective relays in electric power grids recognize the types of electrical faults in a few seconds. The most common detection method to detect the types of electrical faults is based on measuring the angle between the zero and negative sequence currents. However, it is not completely accurate because the phase-to-phase-ground and phase-to-ground electrical faults could have the same detection conditions. Therefore, engineers need to plot the events after an electrical fault to observe the nature of the incidents in detail. In this study, the phase-to-ground fault apparent (PGFA) admittance method with phase/ground boundaries identified the types of electrical faults located in distribution power lines and feeders. This method was based on measuring the PGFA admittance magnitudes for the faulted and nonfaulted phases, resulting in greater than zero and near zero, respectively. The PGFA admittance algorithm was built with MATLAB/Simulink software and tested with signature library and grid simulation events. The PGFA method with phase/ground boundaries was evaluated with the confusion matrix. The measured and predicted values matched in more than 90% of the tests, and the PGFA admittance method with phase/ground boundaries presented an accuracy of 94.3% and a precision of 100%.