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This presentation will discuss the following topics: Understanding the benefits of automatic anomaly detection Identifying precursors with algorithms. Overcoming the challenges of data issues in automation.
This presentation describes major anomalies and failures that have occurred on-orbit in the last 15 years for missions from NASA GSFC and those of significant relevance or relationship to GSFC. Take-aways and lessons are provided with application to the space community.
One of the critical factors affecting flight safety of unmanned aerial vehicles (UAVs) is the amount of vibration they are exposed during a flight. For UAVs under remote operation, vehicle stabilization and navigation is typically achieved by estimating its attitude and position using onboard miniature sensors such as accelerometers, gyroscopes, and GPS via an onboard autopilot. Since precise control of the UAV relies heavily on the attitude sensing, the vibration levels need to be as low as possible in order to minimize the signal noise. Incorrect sensor data can lead to uncertain state estimation causing the multirotor to drift from its desired position. Moreover, high vibrations can induce faults in the safety-critical components of the UAV such as its on-board sensors, motors and propellers. Hence, it is important to monitor the vibration levels during a UAV flight. This paper specifically looks into effect of wind on the vibrations recorded by the autopilot system in an octocopter. Using data from experimental flights under varying wind conditions, we aim to classify between a nominal and anomalous vibration level and define a safety metric known as the Vibrational Anomaly Indicator (VAI) for small UAV systems. Further, we will study effect of high vibrations on the inertial measurement unit (IMU) of an octocopter under laboratory set-up and compute the VAI from IMU measurements. Results would demonstrate the utility of VAI as an health indicator for unmanned flights either in presence of winds or from degraded on-board IMU sensor.
This presentation describes major anomalies and failures that have occurred on-orbit in the last 15 years for missions from NASA GSFC and those of significant relevance or relationship to GSFC. Take-aways and lessons are provided with application to the space community.
Using observations from the Global-scale Observations of the Limb and Disk (GOLD) mission, we investigate post-sunset ionospheric responses to the September 2019 Antarctic sudden stratospheric warming –first ever from a synoptic perspective. Observations reveal a prevalent quasi-6-day periodicity in the equatorial ionization anomaly region over South America and the Atlantic, coincident with enhanced quasi-6-day wave (Q6DW) activity in the mesosphere (Liu et al., 2021, https://doi.org/10.1029/2020JA028909). The atmosphere-ionosphere coupling via large-scale waves is rarely studied over the ocean due to the lack of observations. More importantly, further analyses suggest that multiple pathways are involved in transmitting the quasi-6-day periodicity from the middle atmosphere into the post-sunset F-region ionosphere, including modulation of F-region field aligned winds and pre-reversal enhancements by the tides and or Q6DW. A remarkable depletion in electron density, attributable to the overall change in thermosphere composition driven by the dissipative tides and or Q6DWs, is also seen during the period of enhanced Q6DW activity.
The White Sands Test Facility chemistry laboratory provides quality control for cleanroom operations including cleanliness verification of aerospace hardware by particulate counts and non-volatile residue determinations, particulate counts for liquid hypergolic propellants, gaseous helium and nitrogen propellant pressurizing agents used for ground support equipment and flight test article valve actuation, gaseous oxygen primarily used for component testing, and deionized water for refurbished propellant hardware flushing. Cleanliness verification includes particulate counts and non-volatile residue determinations to industry standard, NASA, and program specifications and levels. Particulate counts are typically to customer-specified specifications and levels including JPR 5322.1H (2016) Levels 50 and 100, Orion (MPCV 70156. Revision H (2018)) Level 100, RPTSTD-8070-0001 Revision 3 (2022), and IEST-STD-CC1246E (2013) Levels 50 and 100. The laboratory issues high pressure filter holders containing membrane filters to test operations personnel, who collect samples by flowing the required volumes of fluid through the filter holder, and the filter holder is returned to the lab for counting. A passing particulate count is required before testing may proceed. Rapid data reduction and issuing of reports indicating a pass or fail of the particulate specification are required. Corrective action and resampling invariably occurs if a sample fails. Consequently, the laboratory must maintain the highest degree of reliability to facilitate quality data used to decide if testing may proceed. Experience and continual improvements have enabled reliability. However, anomalies attributed to lab processes and hardware including filter holders, membranes, and Petri dishes have been encountered. This paper presents a summary of problems, solutions, successes, and lessons learned from particle counting experience for over 35 years.
Energy management of transmission and distribution networks is becoming more challenged with the accelerated increasing of distributed energy resources (DERs) such as distributed photovoltaic (PV) generation and distributed energy storage. To better analyze the impacts of DERs on both transmission and distribution systems, a comprehensive transmission and distribution co-simulation platform should be developed. Furthermore, with DERs more actively participated in system operation such as providing real time grid services, their cyber vulnerability should be better understood to maintain system reliability. This paper discussed a cyber-physical events emulation based transmission & distribution co-simulation platform to perform different cyber events emulation and analyze the impacts of cyber physical events happened in distribution system on the T&D system operation. The case studies with both a transmission network and a synthetic distribution network data validate that the proposed T&D co-simulation platform can perform comprehensive cyber physical events emulation. Therefore, with extensive simulation using the proposed model, the system operator can accumulate adequate training data for the system situation awareness and grid anomaly detection purpose.
Abstract Metallic nanocavity lasers provide important technological advancement toward even smaller integrable light sources. They give access to widely unexplored lasing physics in which the distinction between different operational regimes, like those of thermal or coherent light emission, becomes increasingly challenging upon approaching a device with a near‐perfect spontaneous‐emission coupling factor . In fact, quantum‐optical studies have to be employed to reveal a transition to coherent emission in the intensity fluctuation behavior of nanolasers when the input–output characteristic appears thresholdless for nanolasers. Here, a new indicator for lasing operation in high‐ lasers is identified by showing that stimulated emission can give rise to a lineshape anomaly manifested as a transition from a Lorentzian to a Gaussian component in the emission linewidth that dominates the spectrum above the lasing threshold.
The detection and localization of possible diseases in crops are usually automated by resorting to supervised deep learning approaches. In this work, we tackle these goals with unsupervised models, by applying three different types of autoencoders to a specific open-source dataset of healthy and unhealthy pepper and cherry leaf images. CAE, CVAE and VQ-VAE autoencoders are deployed to screen unlabeled images of such a dataset, and compared in terms of image reconstruction, anomaly removal, detection and localization. The vector-quantized variational architecture turns out to be the best performing one with respect to all these targets.
Abstract We identify novel structure in newly computed multi-loop amplitudes and quantum actions for even-point effective field theories, including both the nonlinear sigma model (NLSM) and double-copy gauge theories such as Born-Infeld and its supersymmetric generalizations. We exploit special properties of all even-point theories towards establishing an efficient unitarity based amplitude construction. In doing so, we find evidence that the leading IR divergence of NLSM amplitudes exponentiates when the target space is$$ \mathbbm{CP} $$ CP 1 ≅ SU(2)/U(1). We then systematically compute the two-loop anomalous behavior of Born-Infeld, and find that the counterterms needed to restore U(1) invariant behavior at loop-level can be constructed via a symmetric-structure double-copy. We also demonstrate that the divergent part of the one-minus (−+++) two-loop anomaly vanishes upon introducing an evanescent operator. In addition to these purely photonic counterterms, we verify through explicit calculation that the anomalous matrix elements that violate U(1) duality invariance can be alternatively cancelled by summing over internal$$ \mathcal{N} $$ N = 4 DBIVA superfields. Finally we find that$$ \mathcal{N} $$ N = 4 Dirac-Born-Infeld-Volkov-Akulov (DBIVA) amplitudes admit double-copy construction through two-loop order by reproducing our unitarity based result with a double copy between color-dual$$ \mathcal{N} $$ N = 4 super-Yang-Mills and our two-loop NLSM amplitudes. This result supports the possibility of color-dual representations for NLSM beyond one-loop. We conclude with an overview of howD-dimensional four-photon counterterms can be constructed in generality with the symmetric-structure double-copy, and outline a convenient way of counting evanescent operators using Hilbert series as generating functions.
We explore the use of Quantum Machine Learning (QML) for anomaly detection at the Large Hadron Collider (LHC). In particular, we explore a semi-supervised approach in the four-lepton final state where simulations are reliable enough for a direct background prediction. This is a representative task where classification needs to be performed using small training datasets - a regime that has been suggested for a quantum advantage. We find that Classical Machine Learning (CML) benchmarks outperform standard QML algorithms and are able to automatically identify the presence of anomalous events injected into otherwise background-only datasets.
Cosmological domain walls can be formed as a result of symmetry breaking at any epoch during the evolution of our universe. We study their interaction with a classical macroscopic object, like Earth or a satellite in Earth’s orbit. We set up an action that includes the interaction term between the massive classical object and the scalar field that the domain wall is made of. We use numerical calculations to solve the coupled equations of motion which describe the crossing between the domain wall and the classical object. Depending on the strength of the interaction, relative velocity and size, the object can be either stopped by the wall, or it can pass through it inducing deformations in the wall that cost energy. At the same time, the coupling to the scalar filed might change the object’s mass during the crossover. The fact that satellites in Earth’s orbit (or planets in Sun’s orbit) can change their mass and/or lose energy interacting with walls can be used as a new domain wall detection probe. For example, a typical velocity precision of a satellite is about 0.5 mm/s, which directly puts an upper limit on its mass change to ΔM/M ≲ 5 × 10 –17 . Alternatively, a known satellite flyby anomaly can easily be explained as an interaction with a closed domain wall. We also show that the presence of matter modifies the scalar filed potential and can locally create a bubble of the true vacuum, and thus trigger the decay of the false vacuum. For a critical bubble which is able to expand, such an interaction with the domain wall must be strong enough.
Experiments at a future $\mathcal{e}$⁺$\mathcal{e}$⁻ collider will be able to search for new particles with masses below the nominal centre-of-mass energy by analyzing collisions with initial-state radiation (radiative return). We show that machine learning methods that use imperfect or missing training labels can achieve sensitivity to generic new particle production in radiative return events. In addition to presenting an application of the classification without labels (CWoLa) search method in $\mathcal{e}$⁺$\mathcal{e}$⁻ collisions, our study combines weak supervision with variable-dimensional information by deploying a deep sets neural network architecture. We have also investigated some of the experimental aspects of anomaly detection in radiative return events and discuss these in the context of future detector design.
Quasi-sterile neutrinos are a natural consequence of dark sectors interacting with the Standard Model (SM) sector via neutrino- and vector-portals. Essentially, quasi-sterile neutrinos are light dark sector fermions with two generic properties: (i) they mix with the active neutrinos of the SM, and (ii) they are charged under a vector mediator that couples feebly to SM matter. Various interesting phenomenological consequences result from this class of particles. In this article, we investigate one such consequence: new, beyond the SM matter effects that can alter in-medium neutrino oscillations. In particular, for special windows of energy and matter densities, active neutrinos can resonantly oscillate into sterile neutrinos. We take advantage of this feature to build a quasi-sterile neutrino model that can explain the MiniBooNE and LSND anomalies, while remaining compatible with observations from long-baseline reactor- and accelerator-based neutrino experiments. This model is also likely compatible with the recent results reported by the MicroBooNE collaboration (albeit we cannot precisely quantify this claim due to a lack of information in MicroBooNE’s public data releases to date). Implications for solar neutrinos and $ν_e$ disappearance searches are also briefly discussed.
Abstract In the early years of nuclear explosion monitoring, experts used downwind detections with meaningful ratios of radioactive species to identify an explosion. Today’s reality is sparse networks of radionuclide monitoring stations looking for weak signals. Analysts need to discriminate between industrial background radioactivity and nuclear explosion signals, even using the detection of one isotope. Aerosol and xenon measurements potentially related to nuclear tests in 2006 and 2013 announced by the Democratic People’s Republic of Korea and from worldwide civilian background radioactivity are considered when defining radionuclide detection anomalies to objectively guide the use of limited analyst resources and reduce the possibility of not detecting nuclear explosions.
We derive an upper bound on the smuon mass assuming that the muon anomaly is explained by the supersymmetric (SUSY) contribution. In the minimal SUSY standard model, the SUSY contribution to the muon g–2 is enhanced when the Higgsino mass parameter is large. Then, the smuon-smuon-Higgs trilinear coupling is enhanced, which may destabilize the electroweak vacuum. We calculate precisely the decay rate of the electroweak vacuum in such a case. We include one-loop effects which are crucial to determine the overall normalization of the decay rate. Requiring that the theoretical prediction of the muon anomalous magnetic moment is consistent with the observed value at the 1 and 2σ levels (equal to the central value of the observed value), we found that the lightest smuon mass should be smaller than 1.38 and 1.68 TeV (1.20 TeV) for tan β (with tan β being the ratio of the vacuum expectation values of the two Higgs bosons), respectively, and the bound is insensitive to the value of tan β.
Gallium tellurides appear to be promising phase-change materials (PCMs) of the next generation for brain-inspired computing and reconfigurable optical metasurfaces. They are different from the benchmark PCMs because of sp 3 gallium hybridization in both cubic Ga 2 Te 3 and amorphous pulsed laser deposition (PLD) films. Liquid Ga 2 Te 3 also shows a viscosity η(T) anomaly just above melting when η(T) first increases and only then starts decreasing. We used high-energy X-ray diffraction to observe a transient mesoscopic immiscibility that suggested dense metallic liquid droplets in a semiconducting melt. The η(T) shape was consistent with this finding. A vanishing first sharp diffraction peak that also shifts to a higher Q indicates a high internal pressure in the metallic melt, which produces a remarkable asymmetry of the Ga–Te nearest neighbor distances and is reminiscent of high-pressure rhombohedral Ga 2 Te 3 . Finally, the observed phenomena provide a realistic scenario for a fast, multilevel SET–RESET response, which also unravels similar trends in the purported density-driven liquid polyamorphism of water, phosphorus, sulfur, and other materials.
Dry deposition could partially explain the observed response in ambient ozone to extreme hot and dry episodes. We examine the response of ozone deposition to heat and dry anomalies using three long-term co-located ecosystem-scale carbon dioxide, water vapor and ozone flux measurement records. We find that, as expected, canopy stomatal conductance generally decreases during days with dry air or soil. However, during hot days, concurrent increases in non-stomatal conductance are inferred at all three sites, which may be related to several temperature-sensitive processes not represented in the current generation of big-leaf models. This may offset the reduction in stomatal conductance, leading to smaller net reduction, or even net increase, in total deposition velocity. We find the response of deposition velocity to soil dryness may be related to its impact on photosynthetic activity, though considerable variability exists. Our findings emphasize the need for better understanding and representation of non-stomatal ozone deposition.