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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Detecting Axion Dark Matter with Black Hole Polarimetry

The axion, as a leading dark matter candidate, is the target of many on-going and proposed experimental searches based on its coupling to photons. Ultralight axions that couple to photons can also cause polarization rotation of light which can be probed by cosmic microwave background. In this work, we show that a large axion field is inevitably developed around black holes due to the Bose-Einstein condensation of axions, enhancing the induced birefringence effects. Therefore, we propose measuring the modulation of supermassive black hole imaging polarization angles as a new probe to the axion-photon coupling of axion dark matter. The oscillating axion field around black holes induces polarization rotation on the black hole image, which is detectable and distinguishable from astrophysical effects on the polarization angle, as it exhibits distinctive temporal variability and frequency invariability. We present the range of axion-photon couplings within the axion mass range $10^{-21}-10^{-16}\text{eV}$ that can be probed by the Event Horizon Telescope. The axion parameter space probed by black hole polarimetry will expand with the improvement in sensitivity on the polarization measurement and more black hole polarimetry targets with determined black hole masses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Standoff Detection of Chemical Plumes Using Swept-ECQCL Remote Detection Technology: Results from EMRTC Complex Terrain Dual Tracer Experiment

As part of the Complex Terrain Dual Tracer Experiments performed in support of the LYNM program, a swept-wavelength external cavity quantum cascade laser (swept-ECQCL) remote detection system was deployed to measure chemical plume propagation with high temporal resolution. The swept-ECQCL remote detection technology was initially developed at PNNL, and is now under further development at Opticslah, LLC under SBIR funding from DOE (DOE SBIR Phase I Project DE-SC0019855, Remote Detection Technologies, Program Manager Chris Ramos). The swept-ECQCL technology provides a single-frequency infrared laser source which is rapidly scanned over a large wavelength range to measure the infrared absorption of gases, liquids, or solids. Analysis of the measured infrared absorption spectrum is used to detect, identify, and quantify the chemical species which are present. While most previous laser-based techniques used small wavelength tuning ranges to measure only a few isolated spectral lines of a few species, the swept-ECQCL provides the large tuning range needed to measure multiple species simultaneously, and to detect broad absorption features from large molecules or condensed phase materials. In addition, the swept-ECQCL systems have high enough spectral resolution and sensitivity to measure narrow lines of small molecules and determine isotope ratios. The remote detection system for gas plumes is based on the swept-ECQCL technology, and consists of a swept-ECQCL source, infrared detector, control electronics, and beam transmitting and alignment optics. The remote detection system directs the infrared output of the swept-ECQCL to a target retro reflector typically located at ~10-10,000 m distance. The swept-ECQCL wavelength is varied continuously over a large wavelength range (>1000 nm) at rates up to 1000 Hz. The swept ECQCL light reflected from the remote target is collected and focused onto an infrared photodetector. By measuring the detector signal continuously as the swept-ECQCL wavelength is varied, a time-series of absorption spectra are measured for the gases along the beam line of-sight. Based on analysis and fitting of the measured absorption spectra, the time-dependent chemical concentrations of species are determined. Multiple species and mixtures can be detected simultaneously, for all species with absorption features above the sensor noise floor. The sensor output is thus a continuous, high-speed record of identified chemicals along with their concentrations and isotope ratios of interest. The high-speed operation enables low-noise operation in conditions of atmospheric turbulence and allows tracking of fluctuating concentrations in transient chemical plumes as needed for reliable remote detection applications. All components operate with minimal cooling requirements and no cryogens are needed. In addition, the output infrared light is invisible with an intensity below the maximum permissible exposure (MPE) threshold of 100 mW/cm2 for these infrared wavelengths and thus eye safe. The measurement concept for plume detection using the swept-ECQCL remote detection system is as follows. The ECQCL beam is directed toward a remote retro-reflector, which reflects the beam back to the ECQCL system where it is focused onto an infrared photodetector. The line-of-sight from the ECQCL system to the retro-reflector defines the measurement path. The detected infrared signal is recorded continuously and detects the absorption of molecular species along the measurement path. Before a plume release, the system measures absorption from atmospheric constituents, which in this LWIR band consist primarily of lines from H 2 O and CO 2 , with additional weaker absorption from N 2 O, NH 3 , and O 3 possibly contributing. The system then measures any changes in absorption due to the tracer compounds when they enter the measurement path. The shape of absorption features is used to distinguish and identify the different tracer compounds, and the strength of the absorption is used to determine the path-integrated concentration – also called the column density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Towards maintaining canine training aid integrity: Effects of environmental factors and operational use on the triacetone triperoxide polymer odor capture‐and‐release system

Abstract There are many factors that may affect the longevity of or guide the use of canine training aids. Literature to date has mainly focused on identifying the headspace volatiles associated with training aids or odors and only minimal research exists into how different variables may alter those volatiles. The current study examines several factors affecting canine training aids: humidity, air flow, transportation, and operational deployment, using the triacetone triperoxide polymer odor capture‐and‐release canine training aid (TATP POCR) as the target. The TATP POCR is an absorption‐based canine training aid developed to be used to safely train canines to detect the odor of the explosive TATP in operational settings. Comparisons of the TATP POCR to neat TATP are made throughout the manuscript. First, humidity increased the background components of the POCR matrix, as well as the amount of TATP recovered was above the POCR. Humidity thus affected the amount of TATP detected but did not prevent detection. Second, air flow lessened the lifetime of the TATP POCR. Third, the practice of using primary and secondary containment successfully prevented contamination, cross‐contamination, and significant target loss, thereby maintaining kit integrity. Finally, the absorption of background odors from training environments was not observed. TATP headspace concentrations between a Deployed and Control POCR kit were not significantly different at time 0 (i.e., upon opening), which suggests that the operational use does not affect the function of the TATP POCR system. This information provides pivotal evidence for explosives detection canine handlers or trainers who utilize the TATP POCR.

Legal Medicine↗
NASA NTRS2011

Tracking Object Existence From an Autonomous Patrol Vehicle

An autonomous vehicle patrols a large region, during which an algorithm receives measurements of detected potential objects within its sensor range. The goal of the algorithm is to track all objects in the region over time. This problem differs from traditional multi-target tracking scenarios because the region of interest is much larger than the sensor range and relies on the movement of the sensor through this region for coverage. The goal is to know whether anything has changed between visits to the same location. In particular, two kinds of alert conditions must be detected: (1) a previously detected object has disappeared and (2) a new object has appeared in a location already checked. For the time an object is within sensor range, the object can be assumed to remain stationary, changing position only between visits. The problem is difficult because the upstream object detection processing is likely to make many errors, resulting in heavy clutter (false positives) and missed detections (false negatives), and because only noisy, bearings-only measurements are available. This work has three main goals: (1) Associate incoming measurements with known objects or mark them as new objects or false positives, as appropriate. For this, a multiple hypothesis tracker was adapted to this scenario. (2) Localize the objects using multiple bearings-only measurements to provide estimates of global position (e.g., latitude and longitude). A nonlinear Kalman filter extension provides these 2D position estimates using the 1D measurements. (3) Calculate the probability that a suspected object truly exists (in the estimated position), and determine whether alert conditions have been triggered (for new objects or disappeared objects). The concept of a probability of existence was created, and a new Bayesian method for updating this probability at each time step was developed. A probabilistic multiple hypothesis approach is chosen because of its superiority in handling the uncertainty arising from errors in sensors and upstream processes. However, traditional target tracking methods typically assume a stationary detection volume of interest, whereas in this case, one must make adjustments for being able to see only a small portion of the region of interest and understand when an alert situation has occurred. To track object existence inside and outside the vehicle's sensor range, a probability of existence was defined for each hypothesized object, and this value was updated at every time step in a Bayesian manner based on expected characteristics of the sensor and object and whether that object has been detected in the most recent time step. Then, this value feeds into a sequential probability ratio test (SPRT) to determine the status of the object (suspected, confirmed, or deleted). Alerts are sent upon selected status transitions. Additionally, in order to track objects that move in and out of sensor range and update the probability of existence appropriately a variable probability detection has been defined and the hypothesis probability equations have been re-derived to accommodate this change. Unsupervised object tracking is a pervasive issue in automated perception systems. This work could apply to any mobile platform (ground vehicle, sea vessel, air vehicle, or orbiter) that intermittently revisits regions of interest and needs to determine whether anything interesting has changed.

Wolf, Michael↗
DOE OSTI2025

Machine-Learning Analysis of Radiative Decays to Dark Matter at the LHC

The search for weakly interacting matter particles (WIMPs) is one of the main objectives of the High Luminosity Large Hadron Collider (HL-LHC). In this work we use Machine-Learning (ML) techniques to explore WIMP radiative decays into a Dark Matter (DM) candidate in a supersymmetric framework. The minimal supersymmetric WIMP sector includes the lightest neutralino that can provide the observed DM relic density through its co-annihilation with the second lightest neutralino and lightest chargino. Moreover, the direct DM detection cross section rates fulfill current experimental bounds and provide discovery targets for the same region of model parameters in which the radiative decay of the second lightest neutralino into a photon and the lightest neutralino is enhanced. This strongly motivates the search for radiatively decaying neutralinos which, however, suffers from strong backgrounds. We investigate the LHC reach in the search for these radiatively decaying particles by means of cut-based and ML methods and estimate its discovery potential in this well-motivated, new physics scenario. We demonstrate that using ML techniques would enable access to most of the parameter space unexplored by other searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Sleptonic SUSY: from UV framework to IR phenomenology

We study an attractive scenario, “Sleptonic SUSY”, which reconciles the 125 GeV Higgs scalar and the non-observation of superpartners thus far with potentially pivotal roles for slepton phenomenology: providing viable ongoing targets for LHC discovery, incorporating a co-annihilation partner for detectable thermal relic dark matter, and capable of mediating the potential muon g – 2 anomaly. This is accomplished by a modestly hierarchical spectrum, with sub-TeV sleptons and electroweakinos and with multi-TeV masses for the other new states. We study new elements in the UV MSSM realization of Sleptonic SUSY based on higher-dimensional sequestering and the synergy between the resulting gaugino-mediation, hypercharge D-term mediation and Higgs-mediation of SUSY-breaking, so as to more fully capture the range of possibilities. This framework stands out by harmoniously solving the flavor, CP and μ – Bμ problems of the supersymmetric paradigm. We discuss its extension to orbifold GUTs, including gauge-coupling and b-tau unification. We also develop a non-minimal model with extra Higgs fields, in which the electroweak vacuum is more readily cosmologically stable against decay to a charge-breaking vacuum, allowing a broader range of sleptonic spectra than in the MSSM alone. We survey the rich set of signals possible at the LHC and future colliders, covering both R-parity conservation and violation, as well as for dark matter detection. While the multi-TeV squarks imply a Little Hierarchy Problem, intriguingly, small changes in parameter space to improve naturalness result in dramatic phase transitions to either electroweak-preservation or charge-breaking. In a Multiverse setting, the modest unnaturalness may then be explained by the “principle of living dangerously”.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

A non-canonical fungal peroxisome PTS-1 signal, SYM, and its evolutionary aspects

Abstract Proteins localized to peroxisomes, particularly those expressed under specific conditions or in low abundance, are often undetected by routine proteomics methods due to detection sensitivity limits. In silico identification and experimental validation of peroxisomal targeting signals (PTSs) offer a reliable alternative. We demonstrate that SYM, a non-canonical plant PTS-1 signal, functions similarly inAspergillus nidulans, as GFP tagged with a SYM C-terminal tripeptide localizes to peroxisomes. One of two nativeA. nidulansproteins with C-terminal SYM tripeptide shows weak peroxisomal localization alongside cytoplasmic presence, indicating that only a subset of proteins with non-canonical signals access peroxisomes.In silicoanalysis of 1,010 fungal genomes identified diverse SYM-proteins with variable functions, suggesting that non-canonical PTS-1 signals may evolve spontaneously. Two-thirds of SYM-proteins are predicted to localize to specific intracellular compartments other than the peroxisome. We propose that despite their predicted localization, these proteins possessing SYM as a non-canonical peroxisomal signal might also have peroxisomal presence. Among SYM-proteins, pectinesterases, known plant pathogen virulence factors, were frequent. Notably, 25% of fungal pectinesterases harbor non-canonical PTS-1 signals, suggesting that partial peroxisomal localization of pectinesterases has evolved convergently. This suggests that partial peroxisomal localization may enhance protein functional flexibility, contributing to the organism’s adaptability.

Science & Technology - Other Topics↗
DOE OSTI2024

Versatile multi-energy hard x-ray camera to study confined and unconfined fast electron dynamics and anisotropies (Invited)

A powerful and flexible hard x-ray (HXR) camera has been recently installed and tested on the WEST tokamak (CEA, France) in collaboration with the Princeton Plasma Physics Laboratory. The diagnostic is a pinhole camera fielded with a 2D pixel detector equipped with a 1 mm thick CdTe sensor. The novelty of this diagnostic technique is the detector’s capability of adjusting the threshold energy at the pixel level. This innovation provides great flexibility in the energy configuration, allowing simultaneous space, energy, and time resolved x-ray measurements. The novel camera has been used to measure the core radiation from non-Maxwellian (fast) electrons accelerated by Lower Hybrid (LH) waves and also the beam–target emission of tungsten in the divertor region produced by fast electron losses interacting with the target. In addition, anisotropic hard x-ray emission has been detected for the first time at the WEST core and edge plasma, with opposite toroidal intensity trends. Finally, experimental vertical and toroidal HXR profiles have been successfully reproduced with the LH code LUKE.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Search for decaying dark matter in the Virgo cluster of galaxies with HAWC

The decay or annihilation of dark matter particles may produce a steady flux of very-high-energy gamma rays detectable above the diffuse background. Nearby clusters of galaxies provide excellent targets to search for the signatures of particle dark matter interactions. In particular, the Virgo cluster spans several degrees across the sky and can be efficiently probed with a wide field-of-view instrument. The High Altitude Water Cherenkov (HAWC) observatory, due to its wide field of view and sensitivity to gamma rays at an energy scale of 300 GeV–100 TeV is well-suited for this search. Using 2141 days of data, we search for γ -ray emission from the Virgo cluster, assuming well-motivated dark matter substructure models. Our results provide some of the strongest constraints on the decay lifetime of dark matter for masses above 10 TeV. Published by the American Physical Society 2024

Albert, A.↗
DOE OSTI2020

PIPER: Performance Insight for Programmers and Exascale Runtimes (Final Technical Report)

This project concentrated on the development of novel performance tools and analysis techniques for large scale parallel systems and applications, eventually targeting exascale platforms. Activities conducted included work to novel root cause detection approaches and an auto-tuning framework for parallel systems. The work has led to several software solutions, which are available as open source.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Mesh Failure Prediction Using Deep Learning Techniques

The goal of this joint effort between SRI and LLNL has been to investigate the use of state-of-the-art deep learning architectures to effectively explore the correlations between a set of mesh zone attributes and manifestations of failure in a given mesh simulation and draw useful conclusions towards a practical failure detection system. Each zone attribute is a scalar feature that is recorded separately for each zone during simulation, resulting in a multivariate time series signal for each zone. Currently, these features are used to manually decide where to apply manual relaxations so that simulations run without any failures. Our long-term vision is to build a machine learning system that is capable of reliably detecting upcoming failures and is able to apply finer-grained targeted relaxations automatically to relevant zones to avoid an expected failure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Development of Machine Learning Algorithm for Pebble Bed Modular Reactor Misuse Detection

The objective of this work was to develop a machine learning ensemble that could assist pebble bed reactor verification by evaluating whether a given pebble circulating through a PBR was normal or anomalous using gamma spectroscopy measurements from a notional PBR burnup measurement system. Using a PBR reference design, data sets of synthetic gamma spectra representative of BUMS measurements of normal and anomalous pebbles that may be used to produce special fissile material were generated to train and test an ML anomaly detection ensemble on two reference scenarios – substitution of normal pebbles with target pebbles for production of Pu or 233 U. The ML ensemble correctly identified all anomalous pebbles in the testing data set, and while perfect ensemble performance is normally indicative of overfitting, it was concluded that significantly lower photon intensity of target pebbles produced distinctly less intense photon spectra to where perfect ensemble performance was expected.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Deep Search for Joint Sources of Gravitational Waves and High-energy Neutrinos with IceCube during the Third Observing Run of LIGO and Virgo

The discovery of joint sources of high-energy neutrinos and gravitational waves has been a primary target for the LIGO, Virgo, KAGRA, and IceCube observatories. The joint detection of high-energy neutrinos and gravitational waves would provide insight into cosmic processes, from the dynamics of compact object mergers and stellar collapses to the mechanisms driving relativistic outflows. The joint detection of multiple cosmic messengers can also elevate the significance of the common observation even when some or all of the constituent messengers are subthreshold, i.e., not significant enough to declare their detection individually. Using data from the LIGO, Virgo, and IceCube observatories, including subthreshold events, we searched for common sources of gravitational waves and high-energy neutrinos during the third observing run of the Advanced LIGO and Advanced Virgo detectors. Our search did not identify significant joint sources. We derive constraints on the rate densities of joint sources. Our results constrain the isotropic neutrino emission from gravitational-wave sources for very high values of the total energy emitted in neutrinos (>10 52 –10 54 erg).

Abbasi, R. [Loyola University Chicago] (ORCID:0000↗
NASA NTRS1978

FM/CW radar system

An FM/CW radar system is presented with improved noise discrimination in which the received signal is multiplied by a sample of the transmitted signal, and the product signal is employed to deflect a laser beam as a function of frequency. The position of the beam is thus indicative of a discrete frequency, and it is detected by the frequency encoded positions of an array of photodiodes. The outputs of the photodiodes are scanned, then threshold detected, and used to obtain the range and velocity of a target.

Brey, H.↗
NASA NTRS1979

Shuttle orbiter Ku-band radar/communications system design evaluation: High gain antenna/widebeam horn

The physical characteristics of the high gain antenna reflector and feed elements are described. Deficiencies in the sum feed are discussed, and lack of atmospheric venting is posed as a potential problem area. The measured RF performance of the high gain antenna is examined and the high sidelobe levels measured are related to the physical characteristics of the antenna. An examination of the attributes of the feed which might be influenced by temperature extremes shows that the antenna should be insensitive to temperature variations. Because the feed support bipod structure is considered a significant contributor to the high sidelobe levels measured in the azimuth plane, pod relocation, material changes, and shaping are suggested as improvements. Alternate feed designs are presented to further improve system performance. The widebeam horn and potential temperature effects due to the polarizer are discussed as well as in the effects of linear polarization on TDRS acquisition, and the effects of circular polarization on radar sidelobe avoidance. The radar detection probability is analyzed as a function of scan overlap and target range.

Iwasaki, R.↗
NASA NTRS1990

Gaseous optical contamination of the spacecraft environment: A review

Interactions between the ambient atmosphere and orbiting spacecraft, sounding rockets, and suborbital vehicles, and with their effluents, give rise to optical (extreme UV to LWIR) foreground radiation which constitutes noise that raises the detection threshold for terrestrial and celestial radiations, as well as military targets. Researchers review the current information on the on-orbit optical contamination. Its source species are created in interaction processes that can be grouped into three categories: (1) Reactions in the gas phase between the ambient atmosphere and desorbates and exhaust; (2) Reactions catalyzed by exposed ram surfaces, which occur spontaneously even in the absence of active material releases from the vehicles; and (3) Erosive excitative reactions with exposed bulk (organic) materials, which have recently been identified in the laboratory though not as yet observed on spacecraft. Researchers also assess the effect of optical pumping by earthshine and sunlight of both reaction products and effluents.

Tran, N. H.↗
NASA NTRS1993

Preliminary analysis of the JAPE ground vehicle test data with an artificial neural network classifier

Remotely sensing and classifying military vehicles in a battlefield environment have been the source of much research over the past 20 years. The ability to know where threat vehicles are located is an obvious advantage to military personnel. In the past active methods of ground vehicle detection such as radar have been used, but with the advancement of technology to locate these active sensors, passive sensors are preferred. Passive sensors detect acoustic emissions, seismic movement, electromagnetic radiation, etc., produced by the target and use this information to describe it. Deriving the mathematical models to classify vehicles in this manner has been, and is, quite complex and not always reliable. However, with the resurgence of artificial neural network (ANN) research in the past few years, developing models for this work may be a thing of the past. Preliminary results from an ANN analysis to the tank signatures recorded at the Joint Acoustic Propagation Experiment (JAPE) at the US Army White Sands Missile Range, NM, in July 1991, are presented.

Larsen, Nathan F.↗
NASA NTRS2007

The EPEC Algorithm for Vision Guided Manipulation: Analysis and Validation

This paper describes the simulated performance and experimental validation of a computationally efficient algorithm for improving positioning accuracy of robot arms using low speed feedback from fixed stereo cameras. The algorithm, called End-Effector Position Error Compensation (EPEC) is robust to visual occlusion of the end-effector and does not require high fidelity calibration of either the arm or stereo camera. The algorithm works by calculating an error vector between the locations of a fiducial on the arm's end-effector as predicted by arm kinematics and detected by a stereo camera triangulation. With this knowledge, the commanded target pose is adjusted to compensate for positioning errors. A simulation environment where arbitrary error can be introduced into arm-camera systems is introduced and used to provide an assessment of the performance of the algorithm under both ideal and degraded conditions.

manipulations↗