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NASA NTRS2020

Search and Rescue under the Forest Canopy using Multiple UAS

We consider the problem of multi-robot search and rescue under the forest canopy. Forest is a particularly challenging environment for collaborative mapping and exploration, mainly due to the existence of severe perceptual aliasing, which hinders reliable mutual localization and map fusion. Our proposed system features unmanned aerial vehicles (UAVs) with onboard sensing and autonomy. Each UAV runs a lightweight filtering algorithm for local state estimation, and a dynamic-aware frontier selection algorithm for fast exploration. The essential and computationally intensive task of collaborative simultaneous localization and mapping (CSLAM) is performed at a central ground station. To handle perceptual aliasing, we make use of stable landmarks extracted from trees, which significantly improve precision and recall during place recognition. Furthermore, to recover from incorrect pairwise data associations during loop closure, we propose a novel procedure for global data association based on recently developed techniques on cycle consistent multiway matching. Our algorithm returns a global data association that is guaranteed to be cycle consistent, and is shown to significantly improve precision compared to the input pairwise associations. The overall multi-UAV system is extensively validated during real-world collaborative exploration missions in a forest at NASA Langley Research Center.

Multi-robot systems↗

DOE OSTI2024

Emerging Jets Search, Triton Server Deployment, and Track Quality Development: Machine Learning Applications in High Energy Physics

Machine learning is becoming prevalent in high energy physics, with numerous applications in physics analyses and event reconstruction showing great improvements compared to traditional computing methods. This thesis studies three projects which each propose new avenues for machine learning applications within the high energy physics CMS experiment located at CERN. In the first project, a search for a dark matter signal called “emerging jets” is performed, using graph neural networks to greatly increase sensitivity to the signal’s signature within the data. The result of this dark matter search sets the most stringent exclusion limits to date on theoretical emerging jet models. Motivated by inefficiencies encountered when processing the emerging jet graph neural network at Fermi National Accelerator Laboratory’s computing centers, the second project re-optimizes the computing centers for machine learning inference. This re-optimization uses NVIDIA Triton Inference Servers to process users’ analysis code heterogeneously, therefore achieving high processing throughput and decreasing user time-to-insight. The last project focuses on an upgrade to the CMS experiment’s real-time event selection system which improves physics object reconstruction under harsh processing conditions. A boosted decision tree is used to quickly and efficiently quantify a reconstructed particle’s “track quality” in order to remove particle tracks reconstructed erroneously. In summary, this thesis will not only present examples of how high energy physics can greatly benefit by leveraging machine learning techniques for physics analysis and reconstruction, but will also provide guidance on how the field can prepare for the inevitable increase in machine learning applications.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Multi-objective Bayesian optimization of ferroelectric materials with interfacial control for memory and energy storage applications

Optimization of materials’ performance for specific applications often requires balancing multiple aspects of materials’ functionality. Even for the cases where a generative physical model of material behavior is known and reliable, this often requires search over multidimensional function space to identify low-dimensional manifold corresponding to the required Pareto front. In this work, we introduce the multi-objective Bayesian optimization (MOBO) workflow for the ferroelectric/antiferroelectric performance optimization for memory and energy storage applications based on the numerical solution of the Ginzburg–Landau equation with electrochemical or semiconducting boundary conditions. MOBO is a low computational cost optimization tool for expensive multi-objective functions, where we update posterior surrogate Gaussian process models from prior evaluations and then select future evaluations from maximizing an acquisition function. Using the parameters for a prototype bulk antiferroelectric (PbZrO 3 ), we first develop a physics-driven decision tree of target functions from the loop structures. We further develop a physics-driven MOBO architecture to explore multidimensional parameter space and build Pareto-frontiers by maximizing two target functions jointly—energy storage and loss. This approach allows for rapid initial materials and device parameter selection for a given application and can be further expanded toward the active experiment setting. The associated notebooks provide both the tutorial on MOBO and allow us to reproduce the reported analyses and apply them to other systems (https://github.com/arpanbiswas52/MOBO_AFI_Supplements).

36 MATERIALS SCIENCE↗

DOE OSTI2024

Theoretical underpinnings of CP-violation at the high-energy frontier

We present a general analysis for the discovery potential of CP-violation (CPV) searches in scattering processes at TeV-scale colliders in an effective field theory framework, using the SMEFT basis for higher dimensional operators. In particular, we systematically examine the CP-violating sector of the SMEFT framework in some well motivated limiting cases, based on flavour symmetries of the underlying heavy theory. We show that, under naturality arguments of the underlying new physics (NP) and in the absence of (or suppressed) flavour-changing interactions, there is only a single operator, Q tΦ = Φ † Φ($\overline{q}$ 3 t) $\tilde{\phi}$ which alters the top-Yukawa coupling, that can generate a non-vanishing CP-violating effect from tree-level SM×NP interference terms. We find, however, that CPV from Q tΦ = Φ † Φ($\overline{q}$ 3 t) $\tilde{\phi}$ is expected to be at best of Ο (1%) and, therefore, very challenging if at all measurable at the LHC or other future high-energy colliders. We then conclude that a potentially measurable CP-violating effect of Ο (10%) can arise in high-energy scattering processes only if flavour-changing interactions are present in the underlying NP; in this case a sizable CPV can be generated at the tree-level by pure NP×NP effects and not from SM×NP interference. We provide several examples of CPV at the LHC and at a future e + s - collider to support these statements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

The radiation valley and exotic resonances in $Wγ$ production at the LHC

The tree-level partonic angular distribution of Standard Model $Wγ$ production possesses a feature known as the Radiation Amplitude Zero (RAZ) where destructive interference causes the cross section to vanish. At the proton level the exact cancellation disappears, however, one can find a dip in the central region of the angular distributions, here called the Radiation Valley (RV). In this paper, we show how the sensitivity for $W(ℓv)γ$ resonances can be significantly improved if one focuses on events in the RV region. Using this technique, we find that the LHC could probe a larger range of resonance masses, equivalent to increasing the luminosity by a factor of 2–3 over conventional searches. The exact increase depends on the spin of the $Wγ$ resonance and exactly how it couples to electroweak gauge bosons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Sensitivity of the MicroBooNE experiment to dark trident interactions

This note describes an ongoing search for dark tridents in the MicroBooNE detector. The dark trident interaction is a proposed interaction of sub-GeV dark matter with ordinary matter that would allow an exploration of a hidden dark sector composed of a dark scalar or fermion χ and a dark photon A'. This dark matter candidate can be produced at fixed-target neutrino beams such as the NuMI beam and travel uninterrupted to the MicroBooNE liquid argon detector. The interaction with the liquid argon occurs through the process χ + Ar → χ + Ar + A' where the dark photon promptly decays inside the detector through: A' → e + + e - . Two event selection strategies are explored, one using boosted decision trees and the other one applying a convolutional neural network. For both analyses a projected sensitivity in MicroBooNE after 2 × 10 21 protons on target is presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Custodial symmetry breaking and Higgs boson signatures at the LHC

We discuss the simplest model that predicts a tree-level modification of the ρ parameter from a shift in the W -mass without changing the prediction for the Z mass. This model predicts a new neutral Higgs and two charged Higgses, with very similar masses and suppressed couplings to the Standard Model fermions. We discuss the decay properties of these new scalar bosons, and the main signatures at the Large Hadron Collider. Comparing these signatures for the first time to the latest measurements, we show that while masses around 200 GeV are excluded for some scenarios, over a wide range of model parameter space the new bosons can have a mass close to the electroweak scale without violating existing limits from experimental searches or destroying the agreement with measurements. We investigate the scenario where the new neutral Higgs is fermiophobic and has a large branching ratio into W gauge bosons and/or photons, and show that this could lead to a signal in the diphoton mass spectrum at low Higgs masses. We discuss the different signatures that can motivate new measurements and searches at the Large Hadron Collider. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

DOE OSTI2021

Closing the Gap between FAIR Data Repositories and Hierarchical Data Formats

Many in the scientific community, particularly in publicly funded research, are pushing to adhere to more accessible data standards to maximize the findability, accessibility, interoperability, and reusability (FAIR) of scientific data, especially with the growing prevalence of machine learning augmented research. Online FAIR data repositories, such as the Open Science Framework (OSF), help facilitate the adoption of these standards by providing frameworks for storage, access, search, APIs, and other features that create organized hubs of scientific data. However, the wider acceptance of such repositories is hindered by the lack of support of hierarchical data formats, such as Technical Data Management Streaming (TDMS) and Hierarchical Data Format 5 (HDF5), that many researchers rely on to organize their datasets. Various tools and strategies should be used to allow hierarchical data formats, FAIR data repositories, and scientific organizations to work more seamlessly together. A pilot project at Los Alamos National Laboratory (LANL) addresses the disconnect between them by integrating the OSF FAIR data repository with hierarchical data renderers, extending support for additional file types in their framework. The multifaceted interactive renderer displays a tree of metadata alongside a table and plot of the data channels in the file. This allows users to quickly and efficiently load large and complex data files directly in the OSF webapp. Users who are browsing files can quickly and intuitively see the files in the way they or their colleagues structured the hierarchical form and immediately grasp their contents. This solution helps bridge the gap between hierarchical data storage techniques and FAIR data repositories, making both of them more viable options for scientific institutions like LANL which have been put off by the lack of integration between them.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Color-octet scalars in Dirac gaugino models with broken R symmetry

In this work we study the collider phenomenology of color-octet scalars ( sgluons ) in supersymmetric models with Dirac gaugino masses that feature an explicitly broken R symmetry ( R - broken models ). We construct such models by augmenting minimal R -symmetric models with a fairly general set of supersymmetric and softly supersymmetry-breaking operators that explicitly break R symmetry. We then compute the rates of all significant two-body decays and highlight new features that appear as a result of R symmetry breaking, including enhancements to extant decay rates, novel tree- and loop-level decays, and improved cross sections of single sgluon production. We demonstrate in some detail how the familiar results from minimal R -symmetric models can be obtained by restoring R symmetry. In parallel to this discussion, we explore constraints on these models from the Large Hadron Collider. We find that, in general, R symmetry breaking quantitatively affects existing limits on color-octet scalars, perhaps closing loopholes for light CP-odd (pseudoscalar) sgluons while opening one for a light CP-even (scalar) particle. Qualitatively, however, we find that — much as for minimal R -symmetric models, despite stark differences in phenomenology — scenarios with broken R symmetry and two sgluons below the TeV scale can be accommodated by existing searches.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Minimal realizations of Dirac neutrino mass from generic one-loop and two-loop topologies at d =5

We carry out a systematic investigation for the minimal Dirac neutrino mass models emerging from generic one-loop and two-loop topologies that arise from d = 5 effective operator with a singlet scalar, σ. To ensure that the tree-level Dirac mass, as well as Majorana mass terms at all orders, are absent for the neutrinos, we work in the framework where the Standard Model is supplemented by the well-motivated U(1)B-L gauge symmetry. At the one-loop level, we analyze six possible topologies, out of which two of them have the potential to generate desired Dirac neutrino mass. Adopting a systematic approach to select minimal models, we construct seventeen viable one-loop Dirac neutrino mass models. By embracing a similar methodical approach at the two-loop, we work out twenty-three minimal candidates. Among the forty selected economical models, the majority of the models proposed in this work are new. In our search, we also include the scenarios where the particles in the loop carry charges under the color group. Furthermore, we discuss the possible dark matter candidates within a given model, if any, without extending the minimal particle content.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1994

Maximum-likelihood soft-decision decoding of block codes using the A* algorithm

The A* algorithm finds the path in a finite depth binary tree that optimizes a function. Here, it is applied to maximum-likelihood soft-decision decoding of block codes where the function optimized over the codewords is the likelihood function of the received sequence given each codeword. The algorithm considers codewords one bit at a time, making use of the most reliable received symbols first and pursuing only the partially expanded codewords that might be maximally likely. A version of the A* algorithm for maximum-likelihood decoding of block codes has been implemented for block codes up to 64 bits in length. The efficiency of this algorithm makes simulations of codes up to length 64 feasible. This article details the implementation currently in use, compares the decoding complexity with that of exhaustive search and Viterbi decoding algorithms, and presents performance curves obtained with this implementation of the A* algorithm for several codes.

Ekroot, L.↗

DOE OSTI2020

Anatomy of $tthh$ physics at the HL-LHC

The t t h h production at colliders contains rich information on the nature of the Higgs boson. In this article, we systematically studied its physics at the high-luminosity Large Hadron Collider (HL-LHC), using exclusive channels with multiple ( ≥ 5 ) b -jets and one lepton ( 5 b 1 ℓ ), multiple ( ≥ 5 ) b -jets and opposite-sign dilepton ( 5 b 2 ℓ ), same-sign dilepton ( SS 2 ℓ ), multiple leptons (multi- ℓ ), and ditau resonance ( τ τ ). The scenarios analyzed include: (1) the t t h h production in Standard Model; (2) the t t h h production mediated by anomalous cubic Higgs self-coupling and t t h h contact interaction; (3) heavy Higgs ( H ) production with t t H → t t h h ; and (4) pair production of fermionic top partners ( T ) with T T → t t h h . To address the complication of event topologies and the mess of combinatorial backgrounds, a tool of boosted-decision-tree was applied in the analyses. The 5 b 1 ℓ and SS 2 ℓ analyses define the two most promising channels. For the nonresonant t t h h production, a combination of these exclusive analyses allows for its measurement in the SM with a statistical significance ~ 0.9 σ (with S / B > 1 % ), and may partially break the sensitivity degeneracy with respect to a varying cubic Higgs self-coupling, a difficulty usually thought to exist in gluon fusion di-Higgs analysis at HL-LHC. These sensitivities were also projected to future hadron colliders at 27 TeV and 100 TeV. For the resonant t t h h productions, the heavy Higgs boson in type II two-Higgs-doublet-model could be efficiently searched for between the mass thresholds 2 m h < m H < 2 m t and even beyond that, for relatively small tan β (vacuum alignment), while the fermionic top partners in composite Higgs models could be probed up to ~ 1.5 TeV and ~ 1.7 TeV , for Br ( T → t h ) = 25 % and 50%, respectively.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1994

Multivariate statistical analysis software technologies for astrophysical research involving large data bases

We developed a package to process and analyze the data from the digital version of the Second Palomar Sky Survey. This system, called SKICAT, incorporates the latest in machine learning and expert systems software technology, in order to classify the detected objects objectively and uniformly, and facilitate handling of the enormous data sets from digital sky surveys and other sources. The system provides a powerful, integrated environment for the manipulation and scientific investigation of catalogs from virtually any source. It serves three principal functions: image catalog construction, catalog management, and catalog analysis. Through use of the GID3* Decision Tree artificial induction software, SKICAT automates the process of classifying objects within CCD and digitized plate images. To exploit these catalogs, the system also provides tools to merge them into a large, complete database which may be easily queried and modified when new data or better methods of calibrating or classifying become available. The most innovative feature of SKICAT is the facility it provides to experiment with and apply the latest in machine learning technology to the tasks of catalog construction and analysis. SKICAT provides a unique environment for implementing these tools for any number of future scientific purposes. Initial scientific verification and performance tests have been made using galaxy counts and measurements of galaxy clustering from small subsets of the survey data, and a search for very high redshift quasars. All of the tests were successful, and produced new and interesting scientific results. Attachments to this report give detailed accounts of the technical aspects for multivariate statistical analysis of small and moderate-size data sets, called STATPROG. The package was tested extensively on a number of real scientific applications, and has produced real, published results.

Djorgovski, S. George↗

NASA NTRS1994

Multivariate Statistical Analysis Software Technologies for Astrophysical Research Involving Large Data Bases

We developed a package to process and analyze the data from the digital version of the Second Palomar Sky Survey. This system, called SKICAT, incorporates the latest in machine learning and expert systems software technology, in order to classify the detected objects objectively and uniformly, and facilitate handling of the enormous data sets from digital sky surveys and other sources. The system provides a powerful, integrated environment for the manipulation and scientific investigation of catalogs from virtually any source. It serves three principal functions: image catalog construction, catalog management, and catalog analysis. Through use of the GID3* Decision Tree artificial induction software, SKICAT automates the process of classifying objects within CCD and digitized plate images. To exploit these catalogs, the system also provides tools to merge them into a large, complex database which may be easily queried and modified when new data or better methods of calibrating or classifying become available. The most innovative feature of SKICAT is the facility it provides to experiment with and apply the latest in machine learning technology to the tasks of catalog construction and analysis. SKICAT provides a unique environment for implementing these tools for any number of future scientific purposes. Initial scientific verification and performance tests have been made using galaxy counts and measurements of galaxy clustering from small subsets of the survey data, and a search for very high redshift quasars. All of the tests were successful and produced new and interesting scientific results. Attachments to this report give detailed accounts of the technical aspects of the SKICAT system, and of some of the scientific results achieved to date. We also developed a user-friendly package for multivariate statistical analysis of small and moderate-size data sets, called STATPROG. The package was tested extensively on a number of real scientific applications and has produced real, published results.

Djorgovski, S. G.↗

NASA NTRS1993

The US Geological Survey, digital spectral reflectance library: version 1: 0.2 to 3.0 microns

We have developed a digital reflectance spectral library, with management and spectral analysis software. The library includes 500 spectra of 447 samples (some samples include a series of grain sizes) measured from approximately 0.2 to 3.0 microns. The spectral resolution (Full Width Half Maximum) of the reflectance data is less than or equal to 4 nm in the visible (0.2-0.8 microns) and less than or equal 10 nm in the NIR (0.8-2.35 microns). All spectra were corrected to absolute reflectance using an NBS Halon standard. Library management software lets users search on parameters (e.g. chemical formulae, chemical analyses, purity of samples, mineral groups, etc.) as well as spectral features. Minerals from sulfide, oxide, hydroxide, halide, carbonate, nitrate, borate, phosphate, and silicate groups are represented. X-ray and chemical analyses are tabulated for many of the entries, and all samples have been evaluated for spectral purity. The library also contains end and intermediate members for the olivine, garnet, scapolite, montmorillonite, muscovite, jarosite, and alunite solid-solution series. We have included representative spectra of H2O ice, kerogen, ammonium-bearing minerals, rare-earth oxides, desert varnish coatings, kaolinite crystallinity series, kaolinite-smectite series, zeolite series, and an extensive evaporite series. Because of the importance of vegetation to climate-change studies we have include 17 spectra of tree leaves, bushes, and grasses.

Clark, Roger N.↗

DOE OSTI2022

Generalizations of the double-copy: the KLT bootstrap

We formulate a new program to generalize the double-copy of tree amplitudes. The approach exploits the link between the identity element of the “KLT algebra” and the KLT kernel, and we demonstrate how this leads to a set of KLT bootstrap equations that the double-copy kernel has to satisfy in addition to locality constraints. We solve the KLT bootstrap equations perturbatively to find the most general higher-derivative corrections to the 4- and 5-point field theory KLT kernel. The new kernel generalizes the string KLT kernel and its associated monodromy relations. It admits new color-structures in the effective theories it double-copies. It provides distinct generalized KK and BCJ relations for the left and right single-color theories and is in that sense a ‘heterotic’-type double-copy. We illustrate the generalized double-copy in detail for 4d Yang-Mills theory with higher-derivative corrections that produce dilaton-axion-gravity with local operators up order ∇ 10 R 4 . Finally, we initiate a search for new double-copy kernels.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2019

Hazards Analysis and Failure Modes and Effects Criticality Analysis (FMECA) of Four Concept Vehicle Propulsion Systems

The primary objective of this research effort is to identify failure modes and hazards associated with the concept vehicles and to perform functional hazard analyses (FHA) and failure modes and effects criticality analyses (FMECA) for each. Boeing also created a Fault Tree Analysis (FTA) for each of the concept vehicles, as the FTA contains the connectivity between systems and is an accepted, top-down method to analyze the safety of an air-vehicle. Conceptual design of notional powertrain configuration for each of four (4) NASA RVLT (Revolutionary Vertical Lift Technology) Concept Vehicles were developed in as much detail as was necessary to support the reliability and safety analysis for this project. Functional block diagrams from each of the conceptual powertrain configurations were created and used to order the FHA, FMECA, and FTA. Hazards were identified and the severity of each were categorized in the FHA for use in a follow-up FMECA. The FTA took inputs from the FMECA and the functional block diagrams to develop the connectivity and develop a quantitative architecture that could be used to perform sensitivity studies, as related to vehicle safety.Guidelines for reliability targets for both the air vehicle and the operation in the UAM (Urban Air Mobility) mission are discussed. An industry literature search was performed in order to assess gaps in existing government regulations and industry specifications. The industry literature search led to air-vehicle and operational reliability discussions, as related to Distributed Electric/Hybrid-Electric Propulsion (DE/HEP) system operating in the UAM role. A discussion of results and recommendations for future work is also provided.

Hazards Analysis↗

NASA NTRS2004

Hexagonal Pixels and Indexing Scheme for Binary Images

A scheme for resampling binaryimage data from a rectangular grid to a regular hexagonal grid and an associated tree-structured pixel-indexing scheme keyed to the level of resolution have been devised. This scheme could be utilized in conjunction with appropriate image-data-processing algorithms to enable automated retrieval and/or recognition of images. For some purposes, this scheme is superior to a prior scheme that relies on rectangular pixels: one example of such a purpose is recognition of fingerprints, which can be approximated more closely by use of line segments along hexagonal axes than by line segments along rectangular axes. This scheme could also be combined with algorithms for query-image-based retrieval of images via the Internet. A binary image on a rectangular grid is generated by raster scanning or by sampling on a stationary grid of rectangular pixels. In either case, each pixel (each cell in the rectangular grid) is denoted as either bright or dark, depending on whether the light level in the pixel is above or below a prescribed threshold. The binary data on such an image are stored in a matrix form that lends itself readily to searches of line segments aligned with either or both of the perpendicular coordinate axes. The first step in resampling onto a regular hexagonal grid is to make the resolution of the hexagonal grid fine enough to capture all the binaryimage detail from the rectangular grid. In practice, this amounts to choosing a hexagonal-cell width equal to or less than a third of the rectangular- cell width. Once the data have been resampled onto the hexagonal grid, the image can readily be checked for line segments aligned with the hexagonal coordinate axes, which typically lie at angles of 30deg, 90deg, and 150deg with respect to say, the horizontal rectangular coordinate axis. Optionally, one can then rotate the rectangular image by 90deg, then again sample onto the hexagonal grid and check for line segments at angles of 0deg, 60deg, and 120deg to the original horizontal coordinate axis. The net result is that one has checked for line segments at angular intervals of 30deg. For even finer angular resolution, one could, for example, then rotate the rectangular-grid image +/-45deg before sampling to perform checking for line segments at angular intervals of 15deg.

Johnson, Gordon G.↗