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At least 397 records · Page 22

Probing gluon saturation with forward di-hadron correlations in proton-nucleus collisions

We present a detailed numerical investigation of semi-inclusive forward di-hadron production in proton–nucleus collisions employing the Color Glass Condensate effective theory. We focus on the regime where di-hadrons are produced nearly back-to-back in the transverse plane, thereby justifying a transverse-momentum-dependent factorization approach in terms of small-x gluon distributions. Our computation integrates several key elements: i) non-linear rapidity evolution via the Balitsky–Kovchegov equation with running coupling, ii) both perturbative and non-perturbative Sudakov resummation, and iii) a phenomenologically constrained model for the initial conditions for small-x gluon distributions. We compare this phenomenological framework to experimental data from the STAR Collaboration on azimuthal correlations in forward di-pion production in both proton–proton and proton–gold collisions. We analyze the systematic theoretical uncertainties associated with the saturation scales of nuclei at the initial scale for rapidity evolution and with those associated with the hadronization process. Finally, we make predictions for the kinematics anticipated to be covered by the ALICE Forward Calorimeter (FoCal) upgrade at the Large Hadron Collider.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Anomalous Transport in Three-Dimensional Discrete Fracture Networks: Interplay Between Aperture Heterogeneity and Injection Modes

In this work, we study how the interplay between fracture aperture heterogeneity and tracer injection mode controls fluid flow and tracer transport in three-dimensional (3D) discrete fracture networks (DFNs). The direct 3-D DFN simulations show that tracer injection mode has substantial effects on tracer spreading across all levels of aperture heterogeneity. The key controlling factor for effective transport is the initial Lagrangian velocity distribution, which is determined by the interplay between injection mode and aperture heterogeneity. The fundamental difference between initial Lagrangian velocity distribution and domain-scale Eulerian velocity distribution plays a vital role in determining anomalous transport. We effectively capture the observed anomalous transport using an upscaled transport model that incorporates initial velocity distribution, stationary velocity distribution, velocity correlation length, and average advective tortuosity. With the upscaled transport model, we accurately capture the evolution of Lagrangian velocity distribution and predict longitudinal spreading in 3-D DFN.

58 GEOSCIENCES↗

Scaling whole-chip QAOA for higher-order ising spin glass models on heavy-hex graphs

Abstract We show that the quantum approximate optimization algorithm (QAOA) for higher-order, random coefficient, heavy-hex compatible spin glass Ising models has strong parameter concentration across problem sizes from 16 up to 127 qubits for p = 1 up to p = 5, which allows for computationally efficient parameter transfer of QAOA angles. Matrix product state (MPS) simulation is used to compute noise-free QAOA performance. Hardware-compatible short-depth QAOA circuits are executed on ensembles of 100 higher-order Ising models on noisy IBM quantum superconducting processors with 16, 27, and 127 qubits using QAOA angles learned from a single 16-qubit instance using the JuliQAOA tool. We show that the best quantum processors find lower energy solutions up to p = 2 or p = 3, and find mean energies that are about a factor of two off from the noise-free distribution. We show that p = 1 QAOA energy landscapes remain very similar as the problem size increases using NISQ hardware gridsearches with up to a 414 qubit processor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Extreme drought impacts have been underestimated in grasslands and shrublands globally

Climate change is increasing the frequency and severity of short-term (~1 y) drought events—the most common duration of drought—globally. Yet the impact of this intensification of drought on ecosystem functioning remains poorly resolved. This is due in part to the widely disparate approaches ecologists have employed to study drought, variation in the severity and duration of drought studied, and differences among ecosystems in vegetation, edaphic and climatic attributes that can mediate drought impacts. To overcome these problems and better identify the factors that modulate drought responses, we used a coordinated distributed experiment to quantify the impact of short-term drought on grassland and shrubland ecosystems. With a standardized approach, we imposed ~a single year of drought at 100 sites on six continents. Here we show that loss of a foundational ecosystem function—aboveground net primary production (ANPP)—was 60% greater at sites that experienced statistically extreme drought (1-in-100-y event) vs. those sites where drought was nominal (historically more common) in magnitude (35% vs. 21%, respectively). This reduction in a key carbon cycle process with a single year of extreme drought greatly exceeds previously reported losses for grasslands and shrublands. Our global experiment also revealed high variability in drought response but that relative reductions in ANPP were greater in drier ecosystems and those with fewer plant species. Overall, our results demonstrate with unprecedented rigor that the global impacts of projected increases in drought severity have been significantly underestimated and that drier and less diverse sites are likely to be most vulnerable to extreme drought.

54 ENVIRONMENTAL SCIENCES↗

Probabilistic simulation of quantum circuits using a deep-learning architecture

The fundamental question of how to best simulate quantum systems using conventional computational resources lies at the forefront of condensed matter and quantum computation. It impacts both our understanding of quantum materials and our ability to emulate quantum circuits. Here we present an exact formulation of quantum dynamics via factorized generalized measurements which maps quantum states to probability distributions with the advantage that local unitary dynamics and quantum channels map to local quasistochastic matrices. This representation provides a general framework for using state-of-the-art probabilistic models in machine learning for the simulation of quantum many-body dynamics. Using this framework, we have developed a practical algorithm to simulate quantum circuits using an attention network based on a powerful neural network ansatz responsible for the most recent breakthroughs in natural language processing. We demonstrate our approach by simulating circuits that build Greenberger-Horne-Zeilinger and linear graph states of up to 60 qubits, as well as a variational quantum eigensolver circuit for preparing the ground state of the transverse field Ising model on several system sizes. Our methodology constitutes a modern machine learning approach to the simulation of quantum physics with applicability both to quantum circuits as well as other quantum many-body systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Spatial imaging of proton via leading-twist nonskewed GPDs with basis light-front quantization

The internal image of the proton is unveiled by examining the generalized parton distributions (GPDs) at zero skewness, within the basis light-front quantized environment. Several distributions emerge when a quark is sampled with different currents depending upon the helicity arrangements of the active quark and the proton target. We investigate six of the eight leading-twist proton GPDs of the valence quarks, the helicity conserving distributions ( H , E , H ˜ ) and the helicity nonconserving ( H T , E T , H ˜ T ) distributions at skewness set to zero ( ζ = 0 ). We consider purely transverse momentum transfer and, hence, obtain results describe only the proton’s two-dimensional structure in the transverse plane. We present the Mellin moments of these distribution functions, where the first moment produces a form factor and the second Mellin moments help extract the information on partonic contributions to the hadronic angular momentum. We compare our results for the Mellin moments with those from lattice QCD and other approaches where available. We also present the GPDs in transverse position space. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

A New Configuration of Paralleled Modular ANPC Multilevel Converter Controlled by an Improved Modulation Method for 1 MHz, 1 MW EV Charger

In this work, a new configuration of the modular multilevel converter (MLC) based on the parallel connection of three-level active-neutral-point-clamped (3L-ANPC) cells as well as its improved modulation method is proposed for 1 MHz, 1 MW electric vehicle (EV) megacharger. In the proposed paralleled modular ANPC-MLC, only six high-frequency silicon carbide (SiC) power switches operating at 333 kHz are required to generate 1 MHz switching frequency spectrum. Moreover, the operating voltage of all power devices is halved, the magnitude of the first switching frequency harmonic cluster is decreased by the factor of five, and the load current is equally distributed between the 3L-ANPC legs by employing the proposed improved modulation method. Hence, the modularity, efficiency, and power density of the proposed converter are notably increased, whereas the value of passive components and the overall switching loss are remarkably decreased. In addition, an optimized design of the one 3L-ANPC cell of the proposed paralleled modular ANPC-MLC for 1 MHz, 1MW EV megacharger using Ansys SIwave, Icepak, and Q3D finite element method platforms is presented and analyzed in detail. The provided experimental results of the down-scaled setup verify the feasibility and viability of the proposed configuration as well as its improved switching pattern.

42 ENGINEERING↗

Characterization of Nanoscale Pores in Tight Gas Sandstones Using Complex Techniques: A Case Study of a Linxing Tight Gas Sandstone Reservoir

Pore structures with rich nanopores and permeability in tight gas reservoirs are poorly understood up to date. Advanced techniques are needed to be employed to accurately characterize pore structures, especially tiny pores which include micron and nanopores. In this study, various experimental techniques such as scanning electron microscopy (SEM), nuclear magnetic resonance (NMR) T 2 , nitrogen adsorption method, and NMR cryoporometry (NMRC) are combined to interrogate the complex pore systems of the tight gas reservoir in the Linxing formation, Ordos Basin, China. Results show that tight gas sandstones are primarily comprised of residual interparticle and clay-dominated pores. Clay and quartz are two dominate minerals while pyrite occupies a nontrivial amount as well. The permeability of tight gas sandstones is very low, exhibiting an extremely poor positive correlation with porosity. While pore types and relative pore contents are more influential factors on the permeability, accurate characterization of pore size distribution is critical for the permeability of tight gas sandstones. Therefore, complementary characterization methods are carried out, indicating that neither small pores with radii < 100 nm (around peak 1 in NMR T 2 distribution) nor large pores with radii > 5 μ m (around peak 3 in NMR T 2 distribution) control the permeability by analyzing the connectivity of the pores in various size ranges, but rather pores averaging approximately 350 ± X nm (around peak 2 in NMR T 2 distribution) have sufficient connectivity to host and transmit hydrocarbons. The pore size of tight gas sandstones is dominated by the clay-rich mineral assemblage. The study shows that the NMRC technique can be a very promising method, especially when referred to as a promising “roadmap” on how to interrogate tight formations such as the tight gas sands or even shale especially for the nanopore characterization.

15 GEOTHERMAL ENERGY↗

Toward Human-Centric Transportation and Energy Metrics: Influence of Mode, Vehicle Occupancy, Trip Distance, and Fuel Economy

Traditional metrics measuring transportation and energy outcomes can be augmented to better represent impacts on people's lives and systems-level performance. In this context, this study introduces two novel metrics: road capacity (as number of people traveling and accessing services) and energy intensity (as energy use for people traveling and accessing services). Current national-level distributions of available data in the United States for factors contributing to the two new integrated metrics are used as context to evaluate potential outcomes. These factors include vehicle occupancy, mode share, fuel economy, and trip distance. Variations in input values provide insights on how these factors shape efficiencies in road capacity and energy intensity. Parametric sensitivity analysis indicates that the impact of each input depends upon the metric being evaluated. For the human-centered road capacity mobility metric, increasing vehicle occupancy has the largest effect &ndash; twice that of increasing mode share for bike, walk, and transit. For the energy intensity mobility metric, the effect of improving fuel economy is the largest. However, when the focus is on accessibility (instead of mobility), for both metrics the effect of lowering average trip distance is the largest. Additionally, a novel interactive tool to visualize the results for various parameter combinations makes the metrics practitioner ready. The findings suggest that the diffusion of new human-centric metrics that benchmark outcomes associated with road capacity and energy may be significant in motivating new sustainable transportation investments and efficient utilization of infrastructure, mobility assets, and services.

ADVANCED PROPULSION SYSTEMS↗

Independent and cumulative thermal neutron-induced fission yields of 241 Pu for ENDF/B-VIII.1

In this work we document changes proposed to the Evaluated Nuclear Data File (ENDF/B) thermal neutron-induced fission yields of 241Pu. The issue, which consists in a nonphysical discontinuity in the yields of fission products in thirteen mass chains, was introduced in ENDF/B-VI.2 and was left unchanged in all releases up until the current release one, ENDF/B-VIII.0. After analyzing the possible origin of the problem, we implemented correction factors that restore the yields to the intended mass distributions. Both independent and cumulative yields files were corrected, and the new values included in this report have been proposed for inclusion in the upcoming ENDF/B-VIII.1 release.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Defining a Platform Approach and Market Participation: Data Driven Business Models for Solid State Transformer-Based Synthetic Inertia and Voltage Stability Controls (CRADA Final Report, Project 1, Mod 1)

The primary objective of this project is to determine the incremental value created with the medium voltage solid-state transformer (MV SST) technology to different stakeholders in view of the updated DER grid regulations. This includes studying the benefits of the MV SST technology in a range of use cases for EV and DER penetration including (1) “corridor charging” for EVs and (2) solar plus storage (FERC 2222). The potential customers of this technology include utilities for EV charging, DER installers who must meet utility interconnection requirements, balancing authorities, and DER aggregators. The traditional transformers on the grid could be a limiting factor for the EV-grid integration as the distribution transformers were not designed to handle the dynamic and fluctuating EV charging loads. Thus, the issues such as voltage fluctuations, increased losses and reduced efficiency [1] can negatively impact the grid operation. To address these challenges, transformers with flexibility and adaptability become imperative to meet the evolving energy demands. In this regard, the concept of Medium Voltage Solid-State Transformers.

14 SOLAR ENERGY↗

Integrated Security-Safety Consequence Study of a Heat Pipe Reactor

This report presents a preliminary demonstration of integrated security/safety consequence modeling to support potential physical security exemption justifications under the new Title 10 Code of Federal Regulations Part 53 licensing pathway, which allows exemptions if sabotage-induced radiological consequences do not exceed 25 rem at the site boundary two hours after release without mitigative actions. A hypothetical heat pipe microreactor subjected to direct sabotage by a 150 lbs. TNT-equivalent high-explosive device was analyzed using a simplified radionuclide release estimate based on DOE-HDBK-3010-94, implemented in the MELCOR severe accident analysis code to model release transport and attenuation through reactor/building compartments, with MELCOR outputs coupled to MACCS to compute offsite doses and the distance-to-threshold metric D 25rem . Six scenarios were evaluated to examine sensitivities to release pathway/building configuration and radionuclide form (vapor versus aerosols with different size distributions). Results show a positive correlation between leak path factor and D 25rem and indicate that reactor building compartmentalization can substantially reduce consequences (a single-story configuration reduced D 25rem by roughly an order of magnitude relative to a cavity-only configuration), while vapor versus aerosol assumptions had limited impact for the modeled two-story case on the spatial grid used.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Lattice Observables for Parton Distributions

In recent years there has been a momentous surge of interest in the determination of the parton content of nucleons using lattice QCD. Scalar field theory is a convenient toy model to understand the relation between Euclidean correlators and Parton Distribution Functions (PDFs). In this talk we review the factorization formulae that allow the extraction of PDFs from the pseudo-PDFs and quasi-PDFs computed on the lattice. The scalar theory provides a simplified setting where the main physical properties are easily analysed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Spatiotemporal Pattern Recognition in the PMU Signals in the WECC system

Phasor measurement unit (PMU) data has been used by multiple power system applications, including state estimation, post event analysis, oscillation detection, model validation, and many others. Still, due to its big data nature and availability to general research institutions, comprehensive understanding of the spatiotemporal patterns and underlying mechanisms are incomplete. This study applies a set of signal processing and machine learning approaches aiming at deciphering the characteristic behaviors of multiple phasor measurement units (PMUs) attributes (e.g., voltage, frequency, rate of change of frequency, phase angle), including their auto-correlation, cross-dependence, similarities and discrepancies across units and temporal scales, and distributions of anomalies and their linkages to potential external factors such as weather events. Data analytics are applied to PMUs from the U.S. Western Electricity Coordinating Council (WECC) system. The PMU measurements, recorded events, outages, and weather extremes are all from real world datasets. The findings from the study and mechanistic understanding of the PMU dynamics help provide guidance on system control or preventing blackouts. The derived metrics can be directly used for adjusting or filtering simulated PMU data used for advanced algorithm development.

Hou, Zhangshuan↗

Cybersecurity assessment and risk management tool

Techniques and apparatuses are described for a cybersecurity risk management tool to assess cybersecurity risk and prioritize cybersecurity correction plans. The cybersecurity risk management tool categorizes cybersecurity framework security controls into maturity indicator levels, identifies implementation states achieved by an entity with respect to the cybersecurity framework security controls, and determines which of the maturity indicator levels represents the implementation state achieved by the entity with respect to each of the cybersecurity framework security controls. A cost-benefit analysis for modifying from the implementation state achieved by the entity to a next implementation state to be achieved by the entity with respect to the cybersecurity framework security controls is also enabled. The cost-benefit analysis leverages factored weights including aspects indicative of security perspectives, Gaussian distributions, and the maturity indicator levels.

Gourisetti, Sri Nikhil Gupta↗

Multiarea Distribution System State Estimation via Distributed Tensor Completion

Here, this paper proposes a model-free distribution system state estimation method based on tensor completion using canonical polyadic decomposition. In particular, we consider a setting where the network is divided into multiple areas. The measured physical quantities at buses located in the same area are processed by an area controller. A three-way tensor is constructed to collect these measured quantities. The measurements are analyzed locally to recover the full state information of the network. A distributed closed-form iterative algorithm based on the alternating direction method of multipliers is developed to obtain the low-rank factors of the whole network state tensor where information exchange happens only between neighboring areas. The convergence properties of the distributed algorithm and the sufficient conditions on the number of samples for each smaller network that guarantee the identifiability of the factors of the state tensor are presented. To demonstrate the efficacy of the proposed algorithm and to check the identifiability conditions, numerical simulations are carried out using the IEEE 123-bus system and a large-scale real utility feeder.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Nonlocal Effective Field Theory and Its Applications

We review recent applications of nonlocal effective field theory, particularly focusing on nonlocal chiral effective theory and nonlocal quantum electrodynamics (QED), as well as an extension of nonlocal effective theory to curved spacetime. For the chiral effective theory, we discuss the calculation of generalized parton distributions (GPDs) of the nucleon at nonzero skewness, along with the corresponding gravitational (or mechanical) form factors, within the convolution framework. In the QED application, we extend the nonlocal formulation to construct the most general nonlocal QED interaction, in which both the propagator and fundamental QED vertex are modified due to the nonlocal Lagrangian, while preserving the Ward–Green–Takahashi identities. For consistency with the modified propagator, a solid quantization is proposed, and the nonlocal QED is applied to explain the lepton g−2 anomalies without the introduction of new particles beyond the standard model. Finally, with an extension of the chiral effective action to curved spacetime, we investigate the nonlocal energy–momentum tensor and gravitational form factors of the nucleon with a nonlocal pion–nucleon interaction.

chiral effective field theory↗

Spin cutoff factor and level density for Ni 59 from an analysis of compound nuclear reactions

The spin cutoff parameter for 59 Ni has been studied from different types of experimental data, including neutron angular distributions from the 56 Fe(α,n) 59 Ni reaction, spin of discrete levels, the level density from the proton evaporation spectrum of the 54 Fe( 6 Li,p) 59 Ni reaction and neutron resonance spacing. Experimental data points were compared with calculations using models widely used in literature. It was found that the available empirical models overestimate data points in the energy region below the neutron separation energy, while microscopic calculations which take into account pairing correlations within Hartree-Fock +Bardeen-Cooper-Schrieffer approach are consistent with data. As a result, it confirmed earlier findings that pairing correlations play an important role and need to be taken into account when the spin cutoff parameter is calculated below the neutron separation energy.

(a,n) reaction↗