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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15

CSBCOO SPMM: Compressed Sparse Block Coordinate format sparse matrix dense vector multiply benchmark (CSBCOO SPMM) v1.0

The purpose of this microbenchmark is to provide a means to explore different programming methodologies using a simple, but not trivial, mathematical kernel. The kernel is based on the matrix vector product in the MFDn nuclear configuration interaction code's LOBPCG eigensolver. This particular mathematical operation is a key element in the solution of systems of equations and block eigensolvers.

Cook, Brandon↗

Mode-multiplexed photonic integrated vector dot-product core from inverse design

Photonic computing has the potential to harness the full degrees of freedom (DOFs) of the light field, including the wavelength, spatial mode, spatial location, phase quadrature, and polarization, to achieve a higher level of computing parallelism and scalability than digital electronic processors. While multiplexing using the wavelength and other DOFs can be readily integrated on silicon photonics platforms with compact footprints, conventional mode-division multiplexed (MDM) photonic designs occupy areas exceeding tens to hundreds of microns for a few spatial modes, significantly limiting their scalability. Here, we utilize inverse design to demonstrate an ultracompact photonic computing core that calculates vector dot products based on MDM coherent mixing. Our dot-product core integrates the functionalities of two-mode multiplexers and one multimode coherent mixer within a nominal footprint of 5 μm x 3 μm . We have experimentally demonstrated computing examples on the fabricated dot-product core, including complex number multiplication and motion estimation using optical flow. The compact dot-product core design enables large-scale on-chip integration in a parallel photonic computing primitive cluster for high-throughput scientific computing and computer vision tasks.

97 MATHEMATICS AND COMPUTING↗

An ecological niche model to predict the geographic distribution of Haemagogus janthinomys, Dyar, 1921 a yellow fever and Mayaro virus vector, in South America

Yellow fever virus (YFV) has a long history of impacting human health in South America. Mayaro virus (MAYV) is an emerging arbovirus of public health concern in the Neotropics and its full impact is yet unknown. Both YFV and MAYV are primarily maintained via a sylvatic transmission cycle but can be opportunistically transmitted to humans by the bites of infected forest dwelling Haemagogus janthinomys Dyar, 1921. To better understand the potential risk of YFV and MAYV transmission to humans, a more detailed understanding of this vector species’ distribution is critical. This study compiled a comprehensive database of 177 unique Hg . janthinomys collection sites retrieved from the published literature, digitized museum specimens and publicly accessible mosquito surveillance data. Covariate analysis was performed to optimize a selection of environmental (topographic and bioclimatic) variables associated with predicting habitat suitability, and species distributions modelled across South America using a maximum entropy (MaxEnt) approach. Our results indicate that suitable habitat for Hg . janthinomys can be found across forested regions of South America including the Atlantic forests and interior Amazon.

60 APPLIED LIFE SCIENCES↗

Constraining Absolute Higgs Couplings using Vector Boson Fusion H to WW with FCC-hh

The absolute normalisation scale of Higgs couplings is difficult to determine in hadron colliders. An experimentally and theoretically clean way to establish the coupling scale is to measure the ratio of resonant Vector Boson Fusion $H \rightarrow WW^{*}$ production to non-resonant $qq \rightarrow qqWW$ because both the theoretical and detector response systematics all cancel to first order in the ratio. To set the scale of the sensitivity, a simple selection and fit is presented with gives a 1.8\% (1.9\%) statistical uncertainty on the ratio for a 100 (84) TeV FCC-hh at 30\,ab$^{-1}$, which would give a corresponding uncertainty on the $\kappa$ scale of 0.5-1\% depending on systematic effects and potential impacts of more sophisticated analysis.

Lipeles, Elliot [University of Pennsylvania] (ORCI↗

Wildfires identification: Semantic segmentation using support vector machine classifier

This paper deals with wildfire identification in the Alaska regions as a semantic segmentation task using support vector machine classifiers. Instead of colour information represented by means of BGR channels, we proceed with a normalized reflectance over 152 days so that such time series is assigned to each pixel. We compare models associated with $\mathcal{l}1$-loss and $\mathcal{l}2$-loss functions and stopping criteria based on a projected gradient and duality gap in the presented benchmarks.

Pecha, Marek↗

Field theories with a vector global symmetry

Motivated by recent discussions of fractons, we explore nonrelativistic field theories with a continuous global symmetry, whose charge is a spatial vector. We present several such symmetries and demonstrate them in concrete examples. They differ by the equations their Noether currents satisfy. Simple cases, other than the translation symmetry, are an ordinary (relativistic) one-form global symmetry and its nonrelativistic generalization. In the latter case the conserved charge is associated with a codimension-one spatial manifold, but it is not topological. More general examples involve charges that are integrated over the entire space. We also discuss the coupling of these systems to gauge fields for these symmetries. We relate our examples to known continuum and lattice constructions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Higgs production via vector-boson fusion at the LHC

In this article, we summarise the recent experimental measurements and theoretical work on Higgs boson production via vector-boson fusion at the LHC. Along with this, we provide state-of-the-art predictions at fixed order as well as with parton-shower corrections within the Standard Model at 13.6 TeV. The results are presented in the form of multi-differential distributions as well as in the Simplified Template Cross Section bins. All materials and outputs of this study are available on public repositories. Finally, following findings in the literature, recommendations are made to estimate theoretical uncertainties related to parton-shower corrections.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Large-Scale Trajectory Analysis via Feature Vectors

The explosion of both sensors and GPS-enabled devices has resulted in position/time data being the next big frontier for data analytics. However, many of the problems associated with large numbers of trajectories do not necessarily have an analog with many of the historic big-data applications such as text and image analysis. Modern trajectory analytics exploits much of the cutting-edge research in machine-learning, statistics, computational geometry and other disciplines. We will show that for doing trajectory analytics at scale, it is necessary to fundamentally change the way the information is represented through a feature-vector approach. We then demonstrate the ability to solve large trajectory analytics problems using this representation.

58 GEOSCIENCES↗

AEVmod – Atomic Environment Vector Module Documentation

This report outlines the mathematical formulation for the atomic environment vector (AEV) construction used in the aevmod software package. The AEV provides a summary of the geometry of a molecule or atomic configuration. We also present the formulation for the analytical Jacobian of the AEV with respect to the atomic Cartesian coordinates. The software provides functionality for both the AEV and AEV-Jacobian, as well as the AEV-Hessian which is available via reliance on the third party library Sacado.

97 MATHEMATICS AND COMPUTING↗

Vector-Matrix Multiplication Engine for Neuromorphic Computation with a CBRAM Crossbar Array [Slides]

The core function of many neural network algorithms is the dot product, or vector matrix multiply (VMM) operation. Crossbar arrays utilizing resistive memory elements can reduce computational energy in neural algorithms by up to five orders of magnitude compared to conventional CPUs. Moving data between a processor, SRAM, and DRAM dominates energy consumption. By utilizing analog operations to reduce data movement, resistive memory crossbars can enable processing of large amounts of data at lower energy than conventional memory architectures.

97 MATHEMATICS AND COMPUTING↗

Support Vector Machines for Estimating Decision Boundaries with Numerical Simulations

Many engineering design problems can be formulated as decisions between two possible options. This is the case, for example, when a quantity of interest must be maintained below or above some threshold. The threshold thereby determines which input parameters lead to which option, and creates a boundary between the two options known as the decision boundary. This report details a machine learning approach for estimating decision boundaries, based on support vector machines (SVMs), that is amenable to large scale computational simulations. Because it is computationally expensive to evaluate each training sample, the approach iteratively estimates the decision boundary in a manner that requires relatively few training samples to glean useful estimates. The approach is then demonstrated on three example problems from structural mechanics and heat transport.

25 ENERGY STORAGE↗

Expanding the Scope of Genomic Security: Targeted Genome Editing within Microbiomes through Designer Bacteriophage Vectors

The ability to engineer the genome of a bacterial strain, not as an isolate, but while present among other microbes in a microbiome, would open new technological possibilities in the areas of medicine, energy and biomanufacturing. Our approach is to develop sets of phages (bacterial viruses) active on the target strain and themselves engineered to act not as killers but as vectors for gene delivery. This approach is rooted in our bioinformatic tools that map prophages accurately within bacterial genomes. We present new bioinformatic results in cross-contig search, design of phage genome assemblies, satellites that embed within prophages, alignment of large numbers of biological sequences, and improvement of reference databases for prophage discovery. We targeted a Pseudomonas putida strain within a lignin-degrading microbiome, but were unable to obtain active phages, and turned toward a defined microbiome of the mouse gut.

59 BASIC BIOLOGICAL SCIENCES↗

Classification Using Support Vector Machines with Uncertainty Quantification

Binary classification using machine learning is needed to address engineering problems such as identifying passing/failing parts based on measured features from aging hardware. In these classifications, providing the uncertainty of each prediction is essential to support engineering decision making. One popular classifier is the support vector machine (SVM). There are many variations, with the simplest being a linear division between two classes with a hyperplane. Kernel methods can be implement

Taylor, Sofia Nitsche↗

EFT validity issues in Vector Boson Scattering processes

Vector Boson Scattering (VBS) processes are regarded as the best lab to study the $VVVV$ quartic couplings, where $V = W, Z$. Such studies are carried in the framework of Effective Field Theories (EFT), but the EFT formalism is often not used in a fully consistent way. We discuss the limitations of the EFT approach to describe New Physics effects in VBS data. We argue that the "clipping" technique is the most theory-motivated way to do data analysis in the EFT language and discuss first results from an analysis of CMS Run 2 data on the $WZ$ and same-sign $WW$ process, with and without "clipping" implemented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Vectors of Efficiency in Hybrid Poplar Genotype Testing

Abstract The Natural Resources Research Institute Hybrid Poplar Program breeds and tests genetically improved clones for bio-mass production and environmental services. The testing process progresses from Nursery Progeny Tests (NPT) to Family Field Trials (FFT) to Clone Trials (CT) to Yield Blocks (YB), with limited replication of many clones in FFT and CT and a limited number of highly selected clones set out in monoclonal blocks (YB) to approximate the conditions of commercial plantations. We used correlation vectors, R 2 (coefficient of determination) and r s (Spearman’s Coefficient) for growth (DBH 2 ) and McFadden’s Pseudo R 2 for canker severity score, to determine where testing times could be altered (age – age correlations) and whole testing steps eliminated. FFT can be shortened from 5 years to 4 years. In CT, rank correlations between age 5 (half-rotation) and age 9/10 (full rotation) were significant (R 2 = 0.39 – 0.72), but age 5 selection missed 44 % of the top ten clones at age 9/10. Clone rank in CT at full, but not half, rotation was correlated with rank at full rotation in YB. Choosing clones at 9 years in CT adds 4 years but allows possible elimination of YB for clone selection. Both FFT and CT are necessary. Canker abundance and severity in CT at full rotation cannot be determined at earlier ages. An aggressive strategy saves 6 years of testing.

Forestry↗