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At least 163 records · Page 9

Tetrahedral Trees: A Family of Hierarchical Spatial Indexes for Tetrahedral Meshes

In this work, we address the problem of performing efficient spatial and topological queries on large tetrahedral meshes with arbitrary topology and complex boundaries. Such meshes arise in several application domains, such as 3D Geographic Information Systems (GISs), scientific visualization, and finite element analysis. To this aim, we propose Tetrahedral trees, a family of spatial indexes based on a nested space subdivision (an octree or a kD-tree) and defined by several different subdivision criteria. We provide efficient algorithms for spatial and topological queries on Tetrahedral trees and compare to state-of-the-art approaches. Our results indicate that Tetrahedral trees are an improvement over R*-trees for querying tetrahedral meshes; they are more compact, faster in many queries, and stable at variations of construction thresholds. They also support spatial queries on more general domains than topological data structures, which explicitly encode adjacency information for efficient navigation but have difficulties with domains with a non-trivial geometric or topological shape.

97 MATHEMATICS AND COMPUTING↗

AdS maps and diagrams of bi-local holography

We present in detail the basic ingredients contained in bi-local holography, representing a constructive scheme for reconstructing AdS bulk theories in Vectorial/AdS duality. Explicit Mapping to bulk AdS and higher spin fields is seen to be given by a double Fourier transform. All order interactions are explicitly specified through the collective action. This generates bulk Feynman (Witten) diagrams (at tree and loop level). We give details of the four-point case evaluation. It is noted that the bi-local construction goes beyond the assumptions in various discussions of non-locality.

1/N Expansion↗

Hidden zeros of the cosmological wavefunction

Motivated by the recent discovery of hidden zeros in particle and string amplitudes, we characterize zeros of individual graph contributions to the cosmological wavefunction of a scalar field theory. We demonstrate that these contributions factorize near these zeros for all tree graphs and provide evidence that this extends to loop graphs as well. We explicitly construct polytopal realizations of the relevant graph associahedra and show that the cosmological zeros have natural geometric and physical interpretations. As a byproduct, we establish an equivalence between the wavefunction coefficients of chain graphs and flat-space Tr(ϕ 3 ) amplitudes, enabling us to leverage the cosmological zeros to uncover the recently discovered hidden zeros of colored amplitudes.

Cosmological models↗

Representations of the language recognition problem for a theorem prover

Two representations of the language recognition problem for a theorem prover in first order logic are presented and contrasted. One of the representations is based on the familiar method of generating sentential forms of the language, and the other is based on the Cocke parsing algorithm. An augmented theorem prover is described which permits recognition of recursive languages. The state-transformation method developed by Cordell Green to construct problem solutions in resolution-based systems can be used to obtain the parse tree. In particular, the end-order traversal of the parse tree is derived in one of the representations. An inference system, termed the cycle inference system, is defined which makes it possible for the theorem prover to model the method on which the representation is based. The general applicability of the cycle inference system to state space problems is discussed. Given an unsatisfiable set S, where each clause has at most one positive literal, it is shown that there exists an input proof. The clauses for the two representations satisfy these conditions, as do many state space problems.

Minker, J.↗

Small UAV Flight Planning in Urban Environments

This work proposes a fast algorithm for generating obstacle-free and wind-efficient flight paths at a constant above-ground-level altitude in urban environments because a fast flight path planning algorithm is an essential function or service needed for enabling small unmanned aerial vehicle (sUAV) to operate in urban environments within Class G airspace. The proposed method first converts the 3D path planning problem to a 2D problem by constructing an obstacle map at a given above-ground-level altitude. A quad-tree decomposition is then used to build a search space in terms of obstacle occupancy and wind difference. The wind cost of traveling through each cell is defined based on energy consumption under various wind conditions. A repulsive potential is also adopted to make sure that the flight plans stay away from obstacles. The Theta* search algorithm, a variant of A* algorithm, is applied to mitigate the path angle change constraints introduced by grid-based graphs. With the Theta* and postsmoothing techniques, an obstacle-free, wind efficient, and constant above-ground-level flight plan can be quickly generated for sUAV operations in urban environments while meeting the lateral path angle constraints. The results showed that the path planning algorithm is efficient and can be finished within several seconds. With a proper choice of wind coefficient, the proposed path planning algorithm outperforms the multiple-shooting trajectory optimization method even in an obstacle-free environment. With the flexibility of incorporating other geo-related costs and computation efficiency, the proposed algorithm shows the potential for real-time flight path planning in complex urban environments.

Path planning↗

Inflationary spectral tilts as a result of the dilatation symmetry breaking

We derive the spectral indices and their runnings of single inflation models by a new approach. We perform a dilatation transformation to the linear cosmological perturbations and derive a current (non)conservation law. Using it, we construct a dilatation charge and a Ward-Takahashi identity for the two-point correlators, and derive two exact expressions for the tree-level spectral indices. First, we apply the slow roll expansion to one of the exact expressions. We calculate the spectral indices and their runnings up to the second and the third order of slow roll parameters, respectively, with use of the “horizon crossing formalism.” By construction, our results are more rigorous and generic than the previous works. Then, we analyze another exact expression to understand how the perturbations and the slow roll parameters contribute to the spectral indices. By a numerical calculation, we confirm that only the behaviors of the slow roll parameters during a few e-folds around the horizon crossing affect significantly to the values of spectral indices. The analysis in this article indicates that if one cannot use the slow roll parameters, regardless of their values, as the expansion parameters around the horizon crossing, then one can no longer apply the slow roll expansion to the spectral indices, and it is thus necessary to apply the more generic method introduced here.

79 ASTRONOMY AND ASTROPHYSICS↗

The ARES High-level Intermediate Representation

The LLVM intermediate representation (IR) lacks semantic constructs for depicting common high-performance operations such as parallel and concurrent execution, communication and synchronization. Currently, representing such semantics in LLVM requires either extending the intermediate form (a signi cant undertaking) or the use of ad hoc indirect means such as encoding them as intrinsics and/or the use of metadata constructs. In this paper we discuss a work in progress to explore the design and implementation of a new compilation stage and associated high-level intermediate form that is placed between the abstract syntax tree and when it is lowered to LLVM's IR. This highlevel representation is a superset of LLVM IR and supports the direct representation of these common parallel computing constructs along with the infrastructure for supporting analysis and transformation passes on this representation.

97 MATHEMATICS AND COMPUTING↗

Twofold symmetries of the pure gravity action

Here, we recast the action of pure gravity into a form that is invariant under a twofold Lorentz symmetry. To derive this representation, we construct a general parameterization of all theories equivalent to the Einstein-Hilbert action up to a local field redefinition and gauge fixing. We then exploit this freedom to eliminate all interactions except those exhibiting two sets of independently contracted Lorentz indices. The resulting action is local, remarkably simple, and naturally expressed in a field basis analogous to the exponential parameterization of the nonlinear sigma model. The space of twofold Lorentz invariant field redefinitions then generates an infinite class of equivalent representations. By construction, all off-shell Feynman diagrams are twofold Lorentz invariant while all on-shell tree amplitudes are automatically twofold gauge invariant. We extend our results to curved spacetime and calculate the analogue of the Einstein equations. Finally, while these twofold invariances are hidden in the canonical approach of graviton perturbation theory, they are naturally expected given the double copy relations for scattering amplitudes in gauge theory and gravity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

SNPeffect: identifying functional roles of SNPs using metabolic networks

Genetic sources of phenotypic variation have been a focus of plant studies aimed at improving agricultural yield and understanding adaptive processes. Genome-wide association studies identify the genetic background behind a trait by examining associations between phenotypes and single-nucleotide polymorphisms (SNPs). Although such studies are common, biological interpretation of the results remains a challenge; especially due to the confounding nature of population structure and the systematic biases thus introduced. Here, we propose a complementary analysis (SNPeffect) that offers putative genotype-to-phenotype mechanistic interpretations by integrating biochemical knowledge encoded in metabolic models. SNPeffect is used to explain differential growth rate and metabolite accumulation in A. thaliana and P. trichocarpa accessions as the outcome of SNPs in enzyme-coding genes. To this end, we also constructed a genome-scale metabolic model for Populus trichocarpa, the first for a perennial woody tree. As expected, our results indicate that growth is a complex polygenic trait governed by carbon and energy partitioning. The predicted set of functional SNPs in both species are associated with experimentally characterized growth-determining genes and also suggest putative ones. Functional SNPs were found in pathways such as amino acid metabolism, nucleotide biosynthesis, and cellulose and lignin biosynthesis, in line with breeding strategies that target pathways governing carbon and energy partition.

54 ENVIRONMENTAL SCIENCES↗

Developing Large-Scale Bayesian Networks by Composition: Fault Diagnosis of Electrical Power Systems in Aircraft and Spacecraft

This CD contains files that support the talk (see CASI ID 20100021404). There are 24 models that relate to the ADAPT system and 1 Excel worksheet. In the paper an investigation into the use of Bayesian networks to construct large-scale diagnostic systems is described. The high-level specifications, Bayesian networks, clique trees, and arithmetic circuits representing 24 different electrical power systems are described in the talk. The data in the CD are the models of the 24 different power systems.

Mengshoel, Ole Jakob↗

Distinct xylem responses to acute vs prolonged drought in pine trees

Increasing dryness challenges trees’ ability to maintain water transport to the leaves. Most plant hydraulics models use a static xylem response to water stress. Yet, in reality, lower soil moisture and warmer temperatures during growing seasons feed back onto xylem development. In turn, adjustments to water stress in the newly built xylem influence future physiological responses to droughts. In this study, we investigate the annual variation of anatomical traits in branch xylem in response to different soil and atmospheric moisture conditions and tree stress levels, as indicated by seasonal predawn leaf water potential (??L,pd). We used a 6-year field experiment in southwestern USA with three soil water treatments applied to Pinus edulis Engelm trees—ambient, drought (45% rain reduction) and irrigation (15–35% annual water addition). All trees were also subject to a natural 1-year acute drought (soil and atmospheric) that occurred during the experiment. The irrigated trees showed only moderate changes in anatomy-derived hydraulic traits compared with the ambient trees, suggesting a generally stable, well-balanced xylem structure under unstressed conditions. The artificial prolonged soil drought increased hydraulic efficiency but lowered xylem construction costs and decreased tracheid implosion safety ((t/b)2), suggesting that annual adjustments of xylem structure follow a safety–efficiency trade-off. The acute drought plunged hydraulic efficiency across all treatments. The combination of acute and prolonged drought resulted in vulnerable and inefficient new xylem, disrupting the stability of the anatomical trade-off observed in the rest of the years. The xylem hydraulic traits showed no consistent direct link to ??L,pd. In the future, changes in seasonality of soil and atmospheric moisture are likely to have a critical impact on the ability of P. edulis to acclimate its xylem to warmer climate. Furthermore, the increasing frequency of acute droughts might reduce hydraulic resilience of P. edulis by repeatedly creating vulnerable and less efficient anatomical structure.

Guerin, Marceau↗

Integrating Embodied Carbon Knowledge for Design Decisions: Preprint

Measuring energy consumption of buildings is well established, and techniques to evaluate the carbon associated with operating buildings are improving. Embodied carbon of buildings is more complex as it considers the release of carbon throughout the building material supply chain and building material end of life fate. Decisions made early during the design and construction of the building can influence and potentially reduce the embodied carbon of buildings. The design and construction communities are uniquely positioned to make decisions that reduce embodied carbon. The objective of this project is to understand barriers to low carbon design and delivery and to point the design and construction communities to useful resources that will result in decisions that reduce embodied carbon. The outcomes of this work include educational resources that familiarize designers and contractors with embodied carbon and life cycle assessments (LCA), case studies that focus on design changes from LCA results, an overview of LCA tools, and examples of readily available, cost-effective design and construction steps to lower embodied carbon. We present an evaluation of existing resources, organized in a decision tree guidance, and identify gaps for further resource development. Through this evaluation process we investigated ways to streamline the process of identifying barriers to implementing solutions quickly.

design professional decisions↗

Characterizing the Benefits of Seismic Isolation of Nuclear Structures in Terms of Reduced Risk and Cost

Seismic isolation is a mature technology that has been implemented in many civil structures, including buildings, bridges, liquid natural gas tanks, and off shore oil platforms, both in the United States and other countries, to mitigate the damaging effects of earthquakes. Seismic isolation has also been used in nuclear structures in France and South Africa, but not yet in the United States: neither in the Department of Energy facilities nor in commercial nuclear power plants (NPPs). This is primarily due to a lack of guidelines, codes and standards for the analysis, design and construction specific to seismically isolated nuclear structures. However, seismic isolation of nuclear structures has seen increased research interest in the recent years and the recently published national consensus standard, America Society of Civil Engineers (ASCE) Standard 4-16 'Seismic analysis of safety related nuclear structures', now incorporates language and commentary (Chapter 12) for seismically isolating surface or near-surface-mounted nuclear facilities, including NPPs. Seismic isolation substantially reduces horizontal seismic loads (demands) on structures, systems, and components. Reduction in demand results in four potential benefits: (1) economic: reduction in capital cost, (2) increased safety: reduction in the mean annual frequency of unacceptable performance, (3) insurance: protection against increases in the known seismic hazard after construction by minimizing the effort to re-qualify and re-certify structures, systems and components, and (4) recertification: the opportunity to certify an existing NPP design for a region of higher seismic hazard. Item (2) above, an increase in safety (reduction of seismic risk), was explored in Huang et al., wherein it was demonstrated that the implementation of seismic isolation reduced seismic risk in nuclear power plant structures. Studies that assess item (1) have not been performed although the use of isolation may lead to large reductions in the capital cost of safety-related nuclear facilities. Funding provided by Nuclear Safety Research and Development in the Department of Energy (DOE) allowed the authors to develop a framework for assessing the economic benefits and reductions in seismic risk afforded by the use of seismic (base) isolation. The framework includes probabilistic risk assessment and estimation of overnight capital costs (OCC's) of a sample generic DOE nuclear facility (GDNF). The project is documented in detail in Bolisetti et al. and Yu et al., and key results are presented here. The GDNF considered in this study is based on a facility constructed at the Idaho National Laboratory. The GDNF is a two-story reinforced concrete building with an embedded basemat and is founded on soft rock at the boundary of Site Class B and Site Class C (B/C boundary) as characterized by ASCE/SEI Standard 7. The GDNF is assumed to handle radiological materials, and its structure, systems and components (SSC's) are designed to effectively confine these materials in the event of an internal failure. The GDNF is populated with components that are generic to safety-related nuclear structures. A single system, which is intended to confine a loss of materials-at-risk (MAR) to the interior of the structure, is chosen for this study. Accordingly, a hypothetical event tree and fault tree are assumed for risk assessment. The isolation system for the GDNF is designed per Chapter 12 of ASCE/SEI 4-16 but is not optimized. The isolation system consists of 38 lead rubber bearings installed in one horizontal plane below the basemat. Details of the GDNF, including the SSC's, event tree and fault tree, and isolation system, are presented in the project report and Yu et al.. This study includes seismic risk assessment and cost estimation for four cases: (1) the GDNF is located at a site of low to moderate seismic hazard and is constructed on a conventional (non-isolated) foundation; (2) the GDNF is located at the same site as case 1, but is seismically isolated; (3) the GDNF is located at a site of high seismic hazard and is constructed on a conventional foundation; and (4) the GDNF is located at the same site of high seismic hazard as case 3, but is seismically isolated. In this study, the DOE site at Idaho National Laboratory (INL) is chosen as the low to moderate seismic hazard site for cases 1 and 2, and the Los Alamos National Laboratory (LANL) is chosen as the high seismic hazard site for cases 3 and 4.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Identification of hadronically decaying W bosons and top quarks using multivariate techniques at ATLAS

By colliding protons and examining particles emitted from the collisions, the Large Hadron Collider aims to study the interactions of quarks and gluons at the highest energy accessible in a controlled experimental way. In such collisions, W bosons or top quarks which have TeV scale momentum can be accessible. Reconstructing such boosted jets are becoming important. In particular, the ability to identify original particle that decays to quarks against normal QCD jets plays a central role in various searches at high energy scale. This is typically done by the use of a single physically motivated observable constructed from the constituents of the jet. In this contribution, multiple complementary observables are combined using boosted decision trees and neural networks to increase the ability to distinguish W bosons and top quarks from light quark jets in the ATLAS experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Spatio-Temporal Modeling of Field Surveyed Backsheet Degradation

Assessing photovoltaic module backsheet durability is critical to increasing module lifetime. Lab based accelerating testing has recently failed to predict large scale failures of widely adopted polymeric materials. Field surveyed data is critical to assess the performance of component lifetime. Using a documented field survey protocol, 13 field surveys where conducted. Each measurement is encoded with it's spatial location in respect to the other modules. By combining field survey data on degradation predictors with real time satellite weather data, data-driven predictive models of backsheet degradation were trained. LOESS models were constructed to investigate the spatial dependence of measurements. It was found that micro-climatic effects like tree-lines, ground surface changes, and elevation changes effected the magnitude and variance of the measurements. A GAM model was created to predict the value of degradation based on measured predictors. The model includes variables on the climate of the system and the location of each measurement in the PV mounting structure. The model performed well with an adj.R 2 of 0.95 for yellowness index prediction. The model was cross-validated using k-folds.

backsheet↗

PySIDT: Subgraph Isomorphic Decision Trees for Molecular Property Prediction

Accurate molecular property prediction is important across all fields of chemistry. Deep neural networks (DNNs) have become increasingly popular due to their ability to train automatically, avoiding the incredibly tedious process of constructing and extending traditional property estimation schemes. However, DNNs require large amounts of training data, are challenging to interpret, require large amounts of memory to load even during inference, and have severe difficulties incorporating qualitative chemical knowledge, which are often desired for molecular property prediction tasks. Here, in this study, we present PySIDT (https://github.com/zadorlab/PySIDT), a software for training and running inference on Subgraph Isomorphic Decision Trees (SIDTs). SIDTs are graph-based decision trees made of nodes associated with molecular substructures. Inference is done by descending target molecular structures down the decision tree to nodes with matching subgraph isomorphic substructures and making predictions based on the final (most specific) nodes matched. SIDTs scale down well to dataset sizes much smaller than is feasible for DNNs. As trees of molecular substructures, SIDTs are inherently readable and easy to visualize, making them easy to analyze. They are also straightforward to extend and retrain, facilitate uncertainty estimation, and enable easy integration of expert knowledge. We demonstrate the SIDT approach discussing its application to a diverse range of molecular prediction tasks: rate coefficient estimation, diffusion coefficient estimation, thermochemistry estimation, transition state bond stretch prediction, p K a prediction, stability of molecular structures, stability of surface structures, and prediction of surface lateral interaction energetics. Additionally, we demonstrate the power of the SIDT algorithms in two direct learning curve vanilla comparisons with the popular DNN-based software Chemprop and the popular gradient boosted trees-based software XGBoost on enthalpy of formation and rate coefficient prediction tasks. In particular, in the enthalpy of formation case, vanilla PySIDT is able to outperform vanilla Chemprop and XGBoost across the full range of training/validation set sizes out to 11,560 data points.

Johnson, Matthew Sean [Sandia National Laboratorie↗

One-loop matrix elements of effective superstring interactions: α' -expanding loop integrands

In the low-energy effective action of string theories, non-abelian gauge interactions and supergravity are augmented by infinite towers of higher-mass-dimension operators. We propose a new method to construct one-loop matrix elements with insertions of operators D 2k F n and D 2k R n in the tree-level effective action of type-I and type-II superstrings. Inspired by ambitwistor string theories, our method is based on forward limits of moduli-space integrals using string tree-level amplitudes with two extra points, expanded in powers of the inverse string tension α'. Similar to one-loop ambitwistor computations, intermediate steps feature non-standard linearized Feynman propagators which eventually recombine to conventional quadratic propagators. With linearized propagators the loop integrand of the matrix elements obey one-loop versions of the monodromy and KLT relations. We express a variety of four- and five-point examples in terms of quadratic propagators and formulate a criterion on the underlying genus-one correlation functions that should make this recombination possible at all orders in α'. The ultraviolet divergences of the one-loop matrix elements are crosschecked against the non-separating degeneration of genus-one integrals in string amplitudes. Conversely, our results can be used as a constructive method to determine degenerations of elliptic multiple zeta values and modular graph forms at arbitrary weight.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Scattering amplitudes and N -body post-Minkowskian Hamiltonians in general relativity and beyond

We present a general framework for calculating post-Minskowskian, classical, conservative Hamiltonians for N non-spinning bodies in general relativity from relativistic scattering amplitudes. Novel features for N > 2 are described including the subtraction of tree-like iteration contributions and the calculation of non-trivial many-body Fourier transform integrals needed to construct position space potentials. A new approach to calculating these integrals as an expansion in the hierarchical limit is described based on the method of regions. As an explicit example, we present the O(G 2 ) 3-body momentum space potential in general relativity as well as for charged bodies in Einstein-Maxwell. The result is shown to be in perfect agreement with previous post-Newtonian calculations in general relativity up to O(G 2 v 4 ). Furthermore, in appropriate limits the result is shown to agree perfectly with relativistic probe scattering in multi-center extremal black hole backgrounds and with the scattering of slowly-moving extremal black holes in the moduli space approximation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗