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At least 19 records

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DOE OSTI2024

Centrality definition in e + A collisions at the electron–ion collider

Here, in this work, we investigate the feasibility of defining centrality in electron–ion collisions at the electron–ion collider (EIC) by examining the correlation between the impact parameter and several observables, including total energy, total transverse momentum, and total number of particles. Using the BeAGLE Monte Carlo generator, we simulate e + Au and e + Ru collisions at different energies and analyze the correlation between the impact parameter and these observables across different kinematic regions. Our findings indicate that the correlation is weak in the central rapidity region but becomes stronger in the forward and far-forward rapidity regions. However, the correlation is not sufficiently robust to allow for precise centrality determination. We conclude that defining centrality in electron–ion collisions is more challenging than in ion–ion collisions, necessitating further studies to develop a robust centrality definition for the EIC.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

(U) MIT Capstone Project (Final Report)

This capstone project focuses on modernizing the design development processes, production development processes, and communication between design agencies (DAs) and production agencies (PAs) to decrease the timeline from conceptual study to first production unit. To focus the scope, the researchers looked only at interactions between the DA, Lawrence Livermore National Lab (LLNL), and the PA, Kansas City National Security Campus (KCNSC). The project’s system problem statement (SPS) is: TO decrease the time from conceptual study to first production unit BY reducing the DA to-PA engineering interface complexity USING digital engineering software that centralizes product definition and information exchange protocols.

42 ENGINEERING↗

DOE OSTI2021

Exploring the Value of Nodes with Multicommunity Membership for Classification with Graph Convolutional Neural Networks

Sampling is an important step in the machine learning process because it prioritizes samples that help the model best summarize the important concepts required for the task at hand. The process of determining the best sampling method has been rarely studied in the context of graph neural networks. In this paper, we evaluate multiple sampling methods (i.e., ascending and descending) that sample based off different definitions of centrality (i.e., Voterank, Pagerank, degree) to observe its relation with network topology. We find that no sampling method is superior across all network topologies. Additionally, we find situations where ascending sampling provides better classification scores, showing the strength of weak ties. Two strategies are then created to predict the best sampling method, one that observes the homogeneous connectivity of the nodes, and one that observes the network topology. In both methods, we are able to evaluate the best sampling direction consistently.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Causal structure of interacting Weyl fermions in condensed matter systems

Abstract The spacetime light cone is central to the definition of causality in the theory of relativity. Recently, links between relativistic and condensed matter physics have been uncovered, where relativistic particles can emerge as quasiparticles in the energy-momentum space of matter. Here, we unveil an energy-momentum analogue of the spacetime light cone by mapping time to energy, space to momentum, and the light cone to the Weyl cone. We show that two Weyl quasiparticles can only interact to open a global energy gap if they lie in each other’s energy-momentum dispersion cones–analogous to two events that can only have a causal connection if they lie in each other’s light cones. Moreover, we demonstrate that the causality of surface chiral modes in quantum matter is entangled with the causality of bulk Weyl fermions. Furthermore, we identify a unique quantum horizon region and an associated ‘thick horizon’ in the emergent causal structure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Selection-bias effects on high-𝑝 𝑇 yield and correlation measurements in oxygen + oxygen collisions

Oxygen + oxygen (O+O) collisions at the BNL Relativistic Heavy Ion Collider (RHIC) and the CERN Large Hadron Collider (LHC) offer a unique experimental opportunity to observe the onset of jet quenching in intermediate relativistic collision systems. As with the smaller proton-nucleus or larger nucleus-nucleus systems, measurements of centrality-selected high-𝑝 T processes in O+O collisions are expected to be sensitive to selection bias effects, which will be necessary to quantify or mitigate before a definitive conclusion on the presence of jet quenching. Using two Monte Carlo heavy-ion event generators, we provide a survey of centrality bias effects on high-𝑝 T yield and correlation measurements. Some highlights of our findings include that (1) bias factors for the accessible kinematic range at RHIC show a nontrivial 𝑝 T dependence, compared to a negligible one at the LHC given the smaller accessible Bjorken-𝑥 range, (2) centrality definitions based on multiplicity are less sensitive to bias effects than those based on the transverse energy, (3) the Angantyr generator gives qualitatively similar but larger-magnitude bias factors than Hijing, and (4) correlation measurements have a much smaller sensitivity to bias effects than do yield measurements. Furthermore, the findings here are intended to guide the experimental design and interpretation of O+O jet quenching and other hard-process measurements.

Hard scattering↗

DOE OSTI2021

Model investigation of the longitudinal broadening of the transverse momentum two-particle correlator

Here, the multiphase transport model is used to investigate the longitudinal broadening of the transverse momentum two-particle correlator C 2 (Δη,Δφ), and its utility to extract the specific shear viscosity, η/s, of the quark-gluon plasma formed in ultrarelativistic heavy ion collisions. The results from these model studies indicate that the longitudinal broadening of C 2 (Δη,Δφ) is sensitive to the value of η/s. However, reliable extraction of the longitudinal broadening of the correlator requires the suppression of possible self-correlations associated with the definition of the collision centrality.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

PERLE: A novel facility for ERL development and applications in multi-turn configuration and high-power regime

The development of ERLs has been recognized as one of the five main pillars of accelerators R&D in support of the European Strategy for Particle Physics (ESPP). The international panel in charge of the ERL Roadmap definition recognized PERLE project as “a central part of the roadmap for the development of energy-recovery linacs”, with milestones to be achieved by the next ESPP in 2026. PERLE project is aiming at the construction of a novel ERL facility for the development and application of the energy recovery technique in multi-turn configuration, high current and large energy regime. It will operate in a 3-turns mode, first at 250 MeV, then upgraded to 500 MeV with 20mA beam current. Such challenging parameters make PERLE a unique multi-turn ERL facility operating at an unexplored operational power regime (10MW), studying and validating a broad range of accelerator phenomena, paving the way for the future larger scale ERLs. PERLE will be the necessary demonstrator for the future HEP machine (LHeC / FCC-eh), with which it shares the same technological choices and beam parameters. Furthermore, PERLE opens a new frontier for the physics of “the electromagnetic probe”. It will be the first ERL dedicated to Nuclear Physics for studying the eN interaction with radioactive nuclei. Here we will report on the project status, introduce the main ongoing achievements and describe the staged strategy we will adopt toward the construction of PERLE machine at its nominal performances.

Kaabi, Walid↗

DOE OSTI2022

SDSS J1058+5443: A Blue Quasar without Optical/NUV Broad Emission Lines

In this paper, the blue quasar SDSS J105816.19+544310.2 (=SDSS J1058+5443) at redshift 0.479 has been reported as the best true type 2 quasar candidate with the disappearance of central broad-line regions. There are no definite conclusions on the very existence of true type 2 active galactic nuclei (AGN), mainly due to detected optical broad emission lines in high-quality spectra of some previously classified true type 2 AGN candidates. Here, unlike previously reported true type 2 AGN candidates among narrow emission-line galaxies with weak AGN activities but strong stellar lights, the definitely blue quasar SDSS J1058+5443 can be well confirmed as a true type 2 quasar due to apparent quasar-shape blue continuum emissions but an apparent loss of both the optical broad Balmer emission lines and the near-UV (NUV) broad Mg II emission line. Based on different model functions and the F-test statistical technique, after considering blueshifted optical and UV Fe II emissions, there are no apparent broad optical Balmer emission lines and/or broad NUV Mg II lines, and the confidence level is smaller than 1σ in support of broad optical and NUV emission lines. Moreover, assuming the virialization assumption to broad-line emission clouds, the reconstructed broad emission lines strongly indicate that the probable intrinsic broad emission lines, if they exist, cannot be hidden or overwhelmed in the noise of the Sloan Digital Sky Survey spectrum of SDSS J1058+5443. Therefore, SDSS J1058+5443 is so far the best and most robust true type 2 quasar candidate, leading to the clear conclusion of the very existence of true type 2 AGN.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Blockchain Enabled Intelligence of Federated Systems (BELIEFS): An attack-tolerant trustable distributed intelligence paradigm

In this article, a Blockchain Enabled Intelligence of Federated Systems (BELIEFS) is proposed to conduct cooperative control for the multi-regional large-scale power system with a multi-agents system (MAS). By establishing a two levels blockchain, each regional AI agent can simultaneously manage intra-regional controllers and cooperate with other AI agents. Under the consensus mechanism, the agents, which respectively conducted distributed deep reinforcement learning (DDRL) algorithm in multi-regions, can have the tolerant capability of malicious attacks in their training process. The demonstration of the proposed approach is within a multi-regional large-scale interconnected power system. Under the mode of "centralized dispatching and hierarchical management", this article aims to definite a mathematical model to deal with the control problem of the power systems. With the comparison experiments, the effectiveness and efficiency of our proposed method in the training process are verified. In addition, malicious attacks are set on the main chain and shard chains to verify the attack-tolerant capability. We expect that such approach and results can suggest a new paradigm of attack-tolerant trustable distributed AI deployment.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Framework for a Digital Documented Safety Analysis

This framework is developed to progress the digital implementation of digital tools applied to the DOE authorization process, with future applications to NRC SAR development/review, to accelerate the design and review processes of advanced nuclear reactors. The engineering design and licensing process for nuclear reactors is currently burdened by a document-based approach that leads to duplications and errors due to a lack of traceability among numerous static documents. Changes to design information require labor-intensive manual tracing through these documents, creating a high potential for human error. The adoption of a digital ecosystem, utilizing a digital thread to link various aspects of project design and analysis, promises dynamic documentation generation, automatic updates, and error reduction. Model Based Definition (MBD) and Product Lifecycle Management (PLM) tools are central to this digital transformation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Centralized Interactive Phenomics Resource: an integrated online phenomics knowledgebase for health data users

Development of clinical phenotypes from electronic health records (EHRs) can be resource intensive. Several phenotype libraries have been created to facilitate reuse of definitions. However, these platforms vary in target audience and utility. Here, we describe the development of the Centralized Interactive Phenomics Resource (CIPHER) knowledgebase, a comprehensive public-facing phenotype library, which aims to facilitate clinical and health services research. The platform was designed to collect and catalog EHR-based computable phenotype algorithms from any healthcare system, scale metadata management, facilitate phenotype discovery, and allow for integration of tools and user workflows. Phenomics experts were engaged in the development and testing of the site. The knowledgebase stores phenotype metadata using the CIPHER standard, and definitions are accessible through complex searching. Phenotypes are contributed to the knowledgebase via webform, allowing metadata validation. Data visualization tools linking to the knowledgebase enhance user interaction with content and accelerate phenotype development. The CIPHER knowledgebase was developed in the largest healthcare system in the United States and piloted with external partners. The design of the CIPHER website supports a variety of front-end tools and features to facilitate phenotype development and reuse. Health data users are encouraged to contribute their algorithms to the knowledgebase for wider dissemination to the research community, and to use the platform as a springboard for phenotyping. CIPHER is a public resource for all health data users available at https://phenomics.va.ornl.gov/ which facilitates phenotype reuse, development, and dissemination of phenotyping knowledge.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2026

Alchemy: A Model-Based Approach for 2D to 3D Autonomous Nuclear System Design

Engineering design of nuclear power plant (NPP) piping and equipment systems frequently bypasses crucial 2D system planning, instead moving straight to 3D modeling. This often leads to designs that exceed building envelope constraints, forcing expensive and time-consuming redesigns. When 2D modeling is employed, it typically involves labor-intensive manual workflows that convert 2D drawings into 3D models, resulting in inefficiencies and errors across design iterations. These workflows further suffer from poor software interoperability and dependence on proprietary software ecosystems, thereby contributing to schedule delays and cost overruns. This paper presents Alchemy, an autonomous framework that transforms 2D system definitions into Industry Foundation Classes (IFC)-compliant 3D building information models (BIMs) for expediting nuclear facility design at the conceptual preliminary phase. Using a model-based approach, the framework treats the 2D system diagram as the central reference model employed to automatically generate all subsequent outputs, ensuring consistency between the system definition and the resulting physical design. A web-based interface enables engineers to define hierarchical system topologies including associated equipment, geometric properties, and connectivity requirements. A two-phase equipment layout optimization algorithm automatically computes collision-free spatial configurations within predefined building envelopes. An artificial intelligence (AI)-assisted pipe routing module then generates orthogonal, collision-free routing paths, allowing the user to select either an A* search-based method or an Ant Colony Optimization (ACO)-based method. All outputs are authored natively in IFC format, relying on open-source technologies and standardized formats in order to ensure extensibility and eliminate proprietary software dependencies. The proposed framework is validated on two representative pressurized-water reactor (PWR)-based case studies, for which it autonomously generates IFC-compliant 3D models in minutes, drastically reducing workflows that typically require hours of manual effort. The generated model demonstrates topologically correct equipment placement, physically plausible spatial relationships, and collision-free pipe routing consistent with known PWR loop configurations. This work represents a foundational step toward digital engineering for nuclear facility preliminary design, with future ongoing development targeting design code compliance and expanded system complexity.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2021

General relativity’s energy and positivity: a brief history

I give a brief review of the search for a proper definition of energy in General Relativity (GR), a far from trivial quest, which was only completed after four and a half decades. The equally (or perhaps more) difficult task of establishing its positivity—it was to take another 15 plus years—will then be summarized. Extension to cosmological GR is included. Mention is made of some recent offshoots. An invitation to submit a review to the Proceedings of the Royal Society prompts revisiting a subject of central importance both to GR and to my own past research—its energy definition and positivity. While there are no loose ends left, a summary may be of some use to students and non-experts. Exposure to introductory GR is useful. So, we will divide this survey into two unequal parts: first, the original GR without a cosmological constant, then extend it to the rather different two cases of A ≠ 0

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Tracking cropland transitions: A comparative analysis of U.S. land cover change data

There are a growing number of land cover data available for the conterminous United States, supporting various applications ranging from biofuel regulatory decisions to habitat conservation assessments. These datasets vary in their source information, frequency of data collection and reporting, land class definitions, categorical detail, and spatial scale and time intervals of representation. These differences limit direct comparison, contribute to disagreements among studies, confuse stakeholders, and hamper our ability to confidently report key land cover trends in the U.S. Here we assess changes in cropland derived from the Land Change Monitoring, Assessment, and Projection (LCMAP) dataset from the U.S. Geological Survey and compare them with analyses of three established land cover datasets across the coterminous U.S. from 2008-2017: (1) the National Resources Inventory (NRI), (2) a dataset Lark et al. 2020 derived from the Cropland Data Layer (CDL), and (3) a dataset from Potapov et al. 2022. LCMAP reports more stable cropland and less stable noncropland in all comparisons, likely due to its more expansive definition of cropland which includes managed grasslands (pasture and hay). Despite these differences, net cropland expansion from all four datasets was comparable (5.18-6.33 million acres), although the geographic extent and type of conversion differed. LCMAP projected the largest cropland expansion in the southern Great Plains, whereas other datasets projected the largest expansion in the northwestern and central Midwest. Most of the pixel-level disagreements (86%) between LCMAP and Lark et al. 2020 were due to definitional differences among datasets, whereas the remainder (14%) were from a variety of causes. Cropland expansion in the LCMAP likely reflects conversions of more natural areas, whereas cropland expansion in other data sources also captures conversion of managed pasture to cropland. The particular research question considered (e.g., habitat versus soil carbon) should influence which data source is more appropriate.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Small- x factorization from effective field theory

We derive a factorization theorem that allows for resummation of small-x logarithms by exploiting Glauber operators in the soft collinear effective field theory. Our analysis is carried out for the hadronic tensor W μν in deep inelastic scattering, and leads to the definition of a new gauge invariant soft function S μν that describes quark and gluon emission in the central region. This soft function provides a new framework for extending resummed calculations for coefficient functions to higher logarithmic orders. Our factorization also defines impact factors by universal collinear functions that are process independent, for instance being identical in small-x DIS and Drell-Yan.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

The mechanics of nucleation and growth and the surface tensions of active matter

Homogeneous nucleation, a textbook transition path for phase transitions, is typically understood on thermodynamic grounds through the prism of classical nucleation theory. However, recent studies have suggested the applicability of classical nucleation theory to systems far from equilibrium. Here, in this article, we formulate a purely mechanical perspective of homogeneous nucleation and growth, elucidating the criteria for the properties of a critical nucleus without appealing to equilibrium notions. Applying this theory to active fluids undergoing motility-induced phase separation, we find that nucleation proceeds in a qualitatively similar fashion to equilibrium systems, with concepts such as the Gibbs–Thomson effect and nucleation barriers remaining valid. We further demonstrate that the recovery of such concepts allows us to extend classical theories of nucleation rates and coarsening dynamics to active systems upon using the mechanically derived definitions of the nucleation barrier and surface tensions. Three distinct surface tensions—the mechanical, capillary, and Ostwald tensions—play a central role in our theory. While these three surface tensions are identical in equilibrium, our work highlights the distinctive role of each tension in the stability of active interfaces and the nucleation and growth of motility-induced phases.

Capillary waves↗

DOE OSTI2021

Elucidation of Aromatic Catabolic Pathways in White-Rot Fungi

This project aims to investigate the hypothesis that white-rot fungi can simultaneously depolymerize lignin extracellularly and catabolize depolymerization products intracellularly as carbon and energy sources. Evaluating this hypothesis will provide deeper understanding of the role of white-rot fungi in facilitating carbon sequestration in Nature. Additionally, identifying the most promising fungal strains for lignin turnover and catabolism will catalyze future efforts in genetic tool development to enable metabolic engineering in white-rot fungi for lignin bioconversion to bioproducts. Lignin is the second most abundant plant-based biopolymer on Earth and represents up to 40% of the energy density of lignocellulosic biomass. Even though lignin is a massive natural carbon and energy reservoir, only a small group of basidiomycete fungi, namely white-rot fungi (WRF), have evolved the ability to efficiently depolymerize and mineralize lignin to CO2 and H2O. Considerable research efforts have been undertaken to understand how WRF depolymerize lignin but the biochemical reactions that convert lignin into CO2 have been largely neglected. In fact, it is unclear if WRF intracellularly catabolize lignin-derived aromatic compounds to utilize them as a carbon and energy source, or rather if lignin is depolymerized and mineralized extracellularly merely to facilitate access to cellulose and hemicellulose for use as a primary carbon source. To date, we have employed 13C-isotope labeling, systems biology approaches, and in vitro enzyme assays to definitively demonstrate that two WRF, Trametes versicolor and Gelatoporia (Ceriporiopsis) subvermispora, funnel carbon from lignin-derived aromatic compounds into central carbon metabolism via intracellular catabolic pathways [1]. Specifically, 13C-isotopic labeling approaches showed that these WRF utilize poplar-derived aromatic compounds (e.g. 4-hydroxybenzoic acid (4-HBA)) as a carbon source. In silico genome analysis led us to hypothesize a complete catabolic pathway for 4-HBA and identify multiple homologous sequences for enzymes with putative oxidative decarboxylase, hydroxylase, and ring-opening dioxygenase activities, which are among the main biochemical reactions acting on aromatic compounds. Spatial and differential proteomic and metabolomic analyses supported the proposed catabolic pathways and showed alternative catabolic steps in T. versicolor that were not present in G. subvermispora. Based on the in silico, proteomics, and transcriptomics results, we down-selected enzymes for further in vitro characterization, and we have assigned a function to six fungal enzymes (including oxidative decarboxylases, hydroxylases, and ring-opening dioxygenases). Interestingly, even though we selected homologous enzyme pairs from both WRF with similar -omics trends, in a few cases only one of the studied fungi showed activity for the proposed substrate. Based on all the observations from this study [1], we hypothesized that 4-HBA preferentially undergoes oxidative decarboxylation to hydroquinone and subsequent hydroxylation to 1,2,4-benzenetriol in G. subvermispora before ring cleavage, whereas 4-HBA would preferentially undergo hydroxylation to protocatechuate and further oxidative decarboxylation to 1,2,4-benzenetriol in T. versicolor. Examining additional decarboxylases and hydroxylases as well as enzymes from other protein families that can perform the same or similar oxidative reactions, such as cytochromes P450 with aromatic hydroxylation activity, will also be key for elucidating enzyme preferences for specific substrates. Overall, this work forms the foundation of a new research area based on lignin catabolism by WRF, which could be further exploited to convert the undervalued biopolymer lignin into value-added compounds.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Distribution of centrality measures on undirected random networks via the cavity method

The Katz centrality of a node in a complex network is a measure of the node’s importance as far as the flow of information across the network is concerned. For ensembles of locally tree-like undirected random graphs, this observable is a random variable. Its full probability distribution is of interest but difficult to handle analytically because of its “global” character and its definition in terms of a matrix inverse. Leveraging a fast Gaussian Belief Propagation-Cavity algorithm to solve linear systems on tree-like structures, we show that i) the Katz centrality of a single instance can be computed recursively in a very fast way, and ii) the probability P ( K ) that a random node in the ensemble of undirected random graphs has centrality K satisfies a set of recursive distributional equations, which can be analytically characterized and efficiently solved using a population dynamics algorithm. We test our solution on ensembles of Erdős-Rényi and Scale Free networks in the locally tree-like regime, with excellent agreement. The analytical distribution of centrality for the configuration model conditioned on the degree of each node can be employed as a benchmark to identify nodes of empirical networks with over- and underexpressed centrality relative to a null baseline. We also provide an approximate formula based on a rank- 1 projection that works well if the network is not too sparse, and we argue that an extension of our method could be efficiently extended to tackle analytical distributions of other centrality measures such as PageRank for directed networks in a transparent and user-friendly way.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗