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DOE OSTI2016

The ATLAS diboson resonance in non-supersymmetric SO(10)

SO(10) grand uni cation accommodates intermediate gauge symmetries with which gauge coupling uni cation can be realized without supersymmetry. In this paper, we discuss the possibility that a new massive gauge boson associated with an intermediate gauge symmetry explains the excess observed in the diboson resonance search recently reported by the ATLAS experiment. The model we find has two intermediate symmetries, SU(4) C Ⓧ SU(2) L Ⓧ SU(2) R and SU(3) C Ⓧ SU(2) L Ⓧ SU(2)R Ⓧ U(1) B-L , where the latter gauge group is broken at the TeV scale. This model achieves gauge coupling uni cation with a uni cation scale su fficiently high to avoid proton decay. In addition, this model provides a good dark matter candidates, whose stability is guaranteed by a Z 2 symmetry present after the spontaneous breaking of the intermediate gauge symmetries. In addition, we discuss prospects for testing these models in the forthcoming LHC experiments and dark matter detection experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

DECAF Cross-device characterization of tokamak disruptions indicated by abnormalities in plasma vertical position and current

Abnormal (deviating from target) variations in the plasma vertical position Z and current I p (such as vertical displacements, transient I p 'spikes' and quenches) constitute common elements of a disruption, a phenomenon that is to be mitigated, or ultimately avoided in future reactor-relevant tokamaks. While those abnormalities are generally recognized cross-shot and cross-device, details in terms of appearance (or not) and order of those abnormalities in disruption event chains is bound with the plasma state at the time of the chain initiation. Detection of those abnormalities is thus indicative not only of the onset of the plasma collapse itself, but also of the disruption driving cause that is promoted at the particular plasma state. Here, occurrence of disruptions, explored via detection of a Ip quench, and analysis of disruption event chains constituted by Ip and Z abnormalities, is reported for in total 7 full years of operation of 3 devices (KSTAR, MAST-U and NSTX-U) using the DECAFTM code expanded tools and capabilities. It is shown that the disruption occurrence depends not only on details of the plasma state, but also on (device-dependent) technical elements of the shot exit scenario. A year-to-year change in main disruption causes and a reduction of the disruptivity rate, bound with device and operation upgrades, are reported. Particular trigger instances of disruption event chains (and the full chains, when applicable) are shown to occupy different parts of the operation space diagrams, in accordance with prior expectation. Plasma elongation is identified as an important factor influencing details of the chains and its role will be further explored.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2016

SDN Project

The SDN Project completed on time and on budget and successfully accomplished 100% of the scope of work outlined in the original Statement of Project Objective (SOPO). The SDN Project formed an alliance between Ameren Corporation, University of Illinois Urbana- Champaign (UIUC), Pacific Northwest National Laboratories (PNNL), and Schweitzer Engineering Laboratories, Inc. (SEL). The objective of the SDN Project is to address Topic Area of Interest 2: Sustain critical energy delivery functions while responding to a cyber-intrusion under Funding Opportunity Announcement DE-FOA-0000797. The goal of the project is to design and commercially release technology that provides a method to sustain critical energy delivery functions during a cyber intrusion and to do this control system operators need the ability to quickly identify and isolate the affected network areas, and re-route critical information and control flows around. The objective of the SDN Project is to develop a Flow Controller that monitors, configures, and maintains the safe, reliable network traffic flows of all the local area networks (LANs) on a control system in the Energy sector. The SDN team identified the core attributes of a control system and produced an SDN flow controller that has the same core attributes enabling networks to be designed, configured and deployed that maximize the whitelisted, deny-bydefault and purpose built networks. This project researched, developed and commercially released technology that: Enables all field networks be to configured and monitored as if they are a single asset to be protected; Enables greatly improved and even precalculated response actions to reliability and cyber events; Supports pre-configured localized response actions tailored to provide resilience against failures and centralized response to cyber-attacks that improve network reliability and availability; Architecturally enables the right subject matter experts, who are usually the information technology and operational technology engineers, to be the ones centrally administering the technology and responding to events; Simplifies network configuration, improving deterministic Ethernet transport times, and providing instant visualization on where the communication circuits are and how all circuits are impacted when changes (e.g., configuration changes, failures or intrusions) happen, allowing operators to minimize downtime; and Improves the ability to identify deviations in network behavior resulting in detection and analysis of potential cyber intrusions and faster response times Results: This project has forever changed the way critical infrastructure networks are designed, secured, deployed and maintained. The cybersecurity and performance advantages achieved are significant, simply put traditional networking has been obsoleted while the team maintained Ethernet interoperability avoiding any legacy concerns. The team commercially released technology that accomplished all the cybersecurity goals outlined in the SOPO and completed it by executing the project management plan approved in the initial contract. The resulting Energy sector SDN flow controller model number is SEL-5056 and can be freely downloaded from the www.SELinc.com website. This technology not only improves the cybersecurity of control systems but has measured results that it improves the performance and reliability of the control system as well. This means the system owners can confidently apply it to their systems knowing that it will, “first do no harm” but actually improve the system as well. Success of the project is best measured by the sales and deployment of the technology. System owners in industrial, electric, defense, and oil and gas only months after commercial release have approved plans for deployment.

42 ENGINEERING↗

DOE OSTI2026

Data Summarization and Inference at Scale

This is the final report for the DOE ASCR grant SC-0022260, Data Summarization and Inference at Scale, PI: Alex Pothen, Purdue University. The goal of the project was to solve data-intensive and compute-intensive problems in the physical sciences, engineering, information science, data science, etc. by designing and implementing new algorithms that could work with a subset of the data. The four subgoals were: (a) The solution of problems where the data is too large to be stored in the memory of a computer. In this streaming model of computation, the data arrives as a stream of elements to the computer, each element is processed as it arrives, and a decision is made to discard the data or to store it; only a small subset of the data proportional to the size of the output solution is stored, and when all the data has been streamed, a solution to the problem is computed from the stored subset. (b) The use of machine learning methods to compute solutions to data-intensive problems. The use of GPUs is critical to obtain high performance on machine learning tasks, but their memory sizes are smaller relative to that of CPUs. For large-scale problems, the data is sampled many times, and small samples are used with repetition, for robustness, to compute solutions to inference tasks. This sampling reduces the memory required to solve the problem, but attention is needed to avoid slow convergence to the solutions, and reduced accuracy of inference. We propose submodular optimization, Large Language Models, and physics-informed neural networks to enable GPU computations here. (c) Modeling and visualization of high-dimensional data using interpretable features. Clinical proteomic data sets from immunology for the detection of cancer and other diseases are temporal and high-dimensional, and algorithms for visualizing these data sets using clinically interpretable features are lacking. We propose methods that compute distances based on the optimal transportation problem and graph edit distances to address this problem. We also propose the use of optimal transport-based distances, spatial statistics, and network structure to classify image data sets, We apply these algorithms to electron micrographs of the peripheral nervous system in the digestive tract. (d) The design of data-intensive algorithms on emerging architectures, specifically, noisy, intermediate-scale quantum (NISQ) devices. Quantum computers offer the possibility of exploring large solution spaces due to the principle of superposition, but current quantum computers are limited by few qubits, short coherence times due to noise, poor interconections among the qubits, etc. We propose the use of the divide and conquer paradigm to solve large-scale problems, wherein collections of small subproblems are solved on the quantum devices, and the solutions to the subproblems are integrated into a solution for the original problem on a classical computer.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Design, execution, and interpretation of plant RNA-seq analyses

Genomics has transformed our understanding of the genetic architecture of traits and the genetic variation present in plants. Here, we present a review of how RNA-seq can be performed to tackle research challenges addressed by plant sciences. We discuss the importance of experimental design in RNA-seq, including considerations for sampling and replication, to avoid pitfalls and wasted resources. Approaches for processing RNA-seq data include quality control and counting features, and we describe common approaches and variations. Though differential gene expression analysis is the most common analysis of RNA-seq data, we review multiple methods for assessing gene expression, including detecting allele-specific gene expression and building co-expression networks. With the production of more RNA-seq data, strategies for integrating these data into genetic mapping pipelines is of increased interest. Finally, special considerations for RNA-seq analysis and interpretation in plants are needed, due to the high genome complexity common across plants. By incorporating informed decisions throughout an RNA-seq experiment, we can increase the knowledge gained.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

SETI OBSERVATIONS OF EXOPLANETS WITH THE ALLEN TELESCOPE ARRAY

We report radio SETI observations on a large number of known exoplanets and other nearby star systems using the Allen Telescope Array (ATA). Observations were made over about 19000 hr from 2009 May to 2015 December. This search focused on narrowband radio signals from a set totaling 9293 stars, including 2015 exoplanet stars and Kepler objects of interest and an additional 65 whose planets may be close to their habitable zones. The ATA observations were made using multiple synthesized beams and an anticoincidence filter to help identify terrestrial radio interference. Stars were observed over frequencies from 1 to 9 GHz in multiple bands that avoid strong terrestrial communication frequencies. Data were processed in near-real time for narrowband (0.7–100 Hz) continuous and pulsed signals with transmitter/receiver relative accelerations from −0.3 to 0.3 m s{sup −2}. A total of 1.9 × 10{sup 8} unique signals requiring immediate follow-up were detected in observations covering more than 8 × 10{sup 6} star-MHz. We detected no persistent signals from extraterrestrial technology exceeding our frequency-dependent sensitivity threshold of 180–310 × 10{sup −26} W m{sup −2}.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1991

Channel coding for digital HDTV terrestrial broadcasting

The Federal Communications Commission of the United States has ruled that high-definition television (HDTV) will occupy no more than 6 MHz of the VHF and UHF bands now used for conventional TV. In order to transmit the HDTV signal in 6 MHz, the four United States digital HDTV proponents, the DigiCipher, DSC-HDTV, ADTV, and ATVA-P systems, are reducing the video data rate of HDTV to 15-17 Mb/s, a compression ratio of approximately 60-70 times. The high compression dictates that channel coding be used to avoid block errors and multiframe error propagation. High efficiency in channel utilization required by the 6-MHz limitation means that the channel must be properly equalized and that the multipath and interfering signals must be severely limited. The channel coding techniques used for error reduction include data interleaving, error detection and replacement, and error correction at different levels of protection for bits and blocks of unequal importance.

Beakley, Guy W.↗

NASA NTRS2005

Wide Bandwidth Phase-Locked Loop Circuit

A PLL circuit uses a multiple frequency range PLL in order 10 phase lock input signals having a wide range of frequencies. The PLL includes a VCO capable of operating in multiple different frequency ranges and a divider bank independently configurable to divide the output of the VCO. A frequency detector detects a frequency of the input signal and a frequency selector selects an appropriate frequency range for the PLL. The frequency selector automatically switches the PLL to a different frequency range as needed in response to a change in the input signal frequency. Frequency range hysteresis is implemented to avoid operating he PLL near a frequency range boundary.

Robert David Koudelka↗

NASA NTRS2005

Wide bandwidth phase-locked loop circuit

A PLL circuit uses a multiple frequency range PLL in order to phase lock input signals having a wide range of frequencies. The PLL includes a VCO capable of operating in multiple different frequency ranges and a divider bank independently configurable to divide the output of the VCO. A frequency detector detects a frequency of the input signal and a frequency selector selects an appropriate frequency range for the PLL. The frequency selector automatically switches the PLL to a different frequency range as needed in response to a change in the input signal frequency. Frequency range hysteresis is implemented to avoid operating the PLL near a frequency range boundary.

Koudelka, Robert David↗

DOE OSTI2016

An Underlay Communication Channel for 5G Cognitive Mesh Networks: Packet Design, Implementation, Analysis, and Experimental Results

This paper proposes and presents the design and implementation of an underlay communication channel (UCC) for 5G cognitive mesh networks. The UCC builds its waveform based on filter bank multicarrier spread spectrum (FB-MCSS) signaling. The use of this novel spread spectrum signaling allows the device-to-device (D2D) user equipments (UEs) to communicate at a level well below noise temperature and hence, minimize taxation on macro-cell/small-cell base stations and their UEs in 5G wireless systems. Moreover, the use of filter banks allows us to avoid those portions of the spectrum that are in use by macro-cell and small-cell users. Hence, both D2D-to-cellular and cellular-to-D2D interference will be very close to none. We propose a specific packet for UCC and develop algorithms for packet detection, timing acquisition and tracking, as well as channel estimation and equalization. We also present the detail of an implementation of the proposed transceiver on a software radio platform and compare our experimental results with those from a theoretical analysis of our packet detection algorithm.

cognitive networks↗

DOE OSTI2024

Characterization Techniques Investigated for Characterization of Anomalous Materials in Plutonium Oxide – 25666

The DOE has adopted a Dilute and Dispose approach for processing surplus plutonium which consists of blending plutonium oxide with adulterants and packaging it in a form which is acceptable for disposal at the Waste Isolation Pilot Plant. The feed material for the downblend process is intended to be pure plutonium oxide powder, however other objects are occasionally encountered within the oxide, particularly with legacy material. Potential technologies which could assist in the resolution of incidents where such anomalies are encountered have been investigated. Resolution of these incidents requires characterization of the anomalous object so that plutonium oxide processing can resume and so that a disposition pathway can be determined for the anomalous material. Technologies including gamma ray spectroscopy, alpha-gamma coincidence, LiDAR volumetric measurements, and surface conductivity measurements were investigated for this purpose, with a focus on systems which can be easily introduced into the processing environment when an anomaly is encountered, then removed from the environment after resolution to avoid impeding normal processing activities. This places an emphasis on small and portable measurement systems and systems that can operate in a high-background, oxide-processing environment. Gamma ray systems investigated include the GR1™a CZT detector and the MicroGe™a germanium detector, with a focus on detecting characteristic gamma rays from Pu-239 and other actinides. A gamma ray and alpha particle coincidence method was investigated with the goal of identifying actinides in the presence of a gamma ray background produced by adjacent plutonium oxide material. Leica™b BLK360 G1 and Keyence™c LJ-X8300 LiDAR systems were investigated for use in conjunction with mass measurements to gain accurate material density values, and a Foerster Sigmatest™d 2.070 was tested to determine surface conductivity. The combination of these properties would allow improved identification and characterization of a wide variety of potential anomalous material.

Munson, Justin M.↗

DOE OSTI2014

Theoretical UV absorption spectra of hydrodynamically escaping O{sub 2}/CO{sub 2}-rich exoplanetary atmospheres

Characterizing Earth- and Venus-like exoplanets' atmospheres to determine if they are habitable and how they are evolving (e.g., equilibrium or strong erosion) is a challenge. For that endeavor, a key element is the retrieval of the exospheric temperature, which is a marker of some of the processes occurring in the lower layers and controls a large part of the atmospheric escape. We describe a method to determine the exospheric temperature of an O{sub 2}- and/or CO{sub 2}-rich transiting exoplanet, and we simulate the respective spectra of such a planet in hydrostatic equilibrium and hydrodynamic escape. The observation of hydrodynamically escaping atmospheres in young planets may help constrain and improve our understanding of the evolution of the solar system's terrestrial planets' atmospheres. We use the dependency of the absorption spectra of the O{sub 2} and CO{sub 2} molecules on the temperature to estimate the temperature independently of the total absorption of the planet. Combining two observables (two parts of the UV spectra that have a different temperature dependency) with the model, we are able to determine the thermospheric density profile and temperature. If the slope of the density profile is inconsistent with the temperature, then we infer the hydrodynamic escape. We address the question of the possible biases in the application of the method to future observations, and we show that the flare activity should be cautiously monitored to avoid large biases.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

A BAYESIAN ESTIMATE OF THE CMB–LARGE-SCALE STRUCTURE CROSS-CORRELATION

Evidences for late-time acceleration of the universe are provided by multiple probes, such as Type Ia supernovae, the cosmic microwave background (CMB), and large-scale structure (LSS). In this work, we focus on the integrated Sachs–Wolfe (ISW) effect, i.e., secondary CMB fluctuations generated by evolving gravitational potentials due to the transition between, e.g., the matter and dark energy (DE) dominated phases. Therefore, assuming a flat universe, DE properties can be inferred from ISW detections. We present a Bayesian approach to compute the CMB–LSS cross-correlation signal. The method is based on the estimate of the likelihood for measuring a combined set consisting of a CMB temperature and galaxy contrast maps, provided that we have some information on the statistical properties of the fluctuations affecting these maps. The likelihood is estimated by a sampling algorithm, therefore avoiding the computationally demanding techniques of direct evaluation in either pixel or harmonic space. As local tracers of the matter distribution at large scales, we used the Two Micron All Sky Survey galaxy catalog and, for the CMB temperature fluctuations, the ninth-year data release of the Wilkinson Microwave Anisotropy Probe ( WMAP 9). The results show a dominance of cosmic variance over the weak recovered signal, due mainly to the shallowness of the catalog used, with systematics associated with the sampling algorithm playing a secondary role as sources of uncertainty. When combined with other complementary probes, the method presented in this paper is expected to be a useful tool to late-time acceleration studies in cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

Light, alpha, and Fe-peak element abundances in the galactic bulge

We present radial velocities and chemical abundances of O, Na, Mg, Al, Si, Ca, Cr, Fe, Co, Ni, and Cu for a sample of 156 red giant branch stars in two Galactic bulge fields centered near (l, b) = (+5.25,–3.02) and (0,–12). The (+5.25,–3.02) field also includes observations of the bulge globular cluster NGC 6553. The results are based on high-resolution (R ∼ 20,000), high signal-to-noise ration (S/N ≳ 70) FLAMES-GIRAFFE spectra obtained through the European Southern Observatory archive. However, we only selected a subset of the original observations that included spectra with both high S/N and that did not show strong TiO absorption bands. This work extends previous analyses of this data set beyond Fe and the α-elements Mg, Si, Ca, and Ti. While we find reasonable agreement with past work, the data presented here indicate that the bulge may exhibit a different chemical composition than the local thick disk, especially at [Fe/H] ≳ –0.5. In particular, the bulge [α/Fe] ratios may remain enhanced to a slightly higher [Fe/H] than the thick disk, and the Fe-peak elements Co, Ni, and Cu appear enhanced compared to the disk. There is also some evidence that the [Na/Fe] (but not [Al/Fe]) trends between the bulge and local disk may be different at low and high metallicity. We also find that the velocity dispersion decreases as a function of increasing [Fe/H] for both fields, and do not detect any significant cold, high-velocity populations. A comparison with chemical enrichment models indicates that a significant fraction of hypernovae may be required to explain the bulge abundance trends, and that initial mass functions that are steep, top-heavy (and do not include strong outflow), or truncated to avoid including contributions from stars >40 M {sub ☉} are ruled out, in particular because of disagreement with the Fe-peak abundance data. For most elements, the NGC 6553 stars exhibit abundance trends nearly identical to comparable metallicity bulge field stars. However, the star-to-star scatter and mean [Na/Fe] ratios appear higher in the cluster, perhaps indicating additional self-enrichment.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Seamless Wireless Communication Platform for Internet of Things Applications

The rapid growth of the Internet of Things (IoT) devices resulted in the proliferation of wireless technologies to cater to their increasing data rate requirements and support multiple applications. However, such ever-increasing wireless technologies present numerous challenges such as incompatible wireless standards, increased energy consumption, and insecure communication. The traditional gateways proposed in the literature suffers from limitations such as computational complexity, resource requirements, increased cost, and device size. We vision an era of seamless wireless communication to alleviate the aforementioned challenges in IoT applications. through three inter-dependent functionalities namely detection and identification of wireless technologies, energy-efficient transmit power control, and secure end-to-end communication. To prove the concept, a new gateway is proposed to achieve these three functionalities with only physical layer measurements so that the different communication protocols in the higher layers can be avoided. Novel schemes are conceptualized for resource-limited seamless IoT applications. Moreover, the conceptual seamless IoT platform is validated through software-based computer simulation and software-defined radio-based testbed implementation. Finally, the preliminary analysis demonstrates that the proposed platform has great potential in advancing seamless IoT applications.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1996

Measurement of Noise Produced by a Plasma Contactor Operating in Ground Based Facilities

Methods to measure electric field fluctuations accurately in a plasma with an active monopole antenna are described. It is shown that the conductive surfaces of the antenna must be adequately isolated from the ambient plasma and that the monopole must be sufficiently short to avoid antenna amplifier saturation. Experimental results illustrate that the noise produced by plasma contactor operation and sensed by the antenna is due to plasma phenomena and is not induced by laboratory power supplies. A good correlation is shown between the current fluctuations in the contactor electrical circuit and the noise detected by the antenna. A large body of experimental data support the conclusion that the majority of noise sensed by the antenna at frequencies less than 1 MHz is due to current fluctuations (electrostatic waves) in the plasma adjacent to the antenna and not to electromagnetic wave radiation. Caution is suggested when comparing antenna noise measurements to conventional specifications for radiated emissions.

Snyder, Steve↗

NASA NTRS2019

Predicting Satellite Close Approaches Using Statistical Parameters in the Context of Artificial Intelligence

In order to ensure a sustainable use of low earth orbit in particular and near Earth space in general, reliable and effective close approach prediction be-tween space objects is key. Only this allows for efficient and timely colli-sion avoidance. Space Situational Awareness (SSA) for commercial and government missions will be facing the rapidly growing amount of small and potentially less agile satellites as well as debris in the near earth realm, such as the increase in CubeSat launches and upcoming large constellations. At the same time, space object detection capabilities are expected to increase significantly, allowing for the reliable detection of smaller objects, e.g. when the Air Force Space Fence radar becomes operational. In combination, the space object catalog is expected to increase tremendously in size. In this paper, we introduce an investigative approach based on the latest capabili-ties in artificial intelligence in fostering the potential for fast and accurate close approach predictions. We consider the study of statistical and infor-mation theory parameters in contrast and complementary to the classical probability of collision computation alone, in order to determine the feasi-bility of reliably predicting close approaches.

Mashiku, A.↗

NASA NTRS2019

Predicting Satellite Close Approaches Using Statistical Parameters in the Context of Artificial Intelligence

Mashiku, Alinda↗