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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Extracting Topological Orders of Generalized Pauli Stabilizer Codes in Two Dimensions

In this paper, we introduce an algorithm for extracting topological data from translation invariant generalized Pauli stabilizer codes in two-dimensional systems, focusing on the analysis of anyon excitations and string operators. The algorithm applies to Z d qudits, including instances where d is a nonprime number. This capability allows the identification of topological orders that differ from the Z d toric codes. It extends our understanding beyond the established theorem that Pauli stabilizer codes for Z p qudits (with p being a prime) are equivalent to finite copies of Z p toric codes and trivial stabilizers. The algorithm is designed to determine all anyons and their string operators, enabling the computation of their fusion rules, topological spins, and braiding statistics. The method converts the identification of topological orders into computational tasks, including Gaussian elimination, the Hermite normal form, and the Smith normal form of truncated Laurent polynomials. Furthermore, the algorithm provides a systematic approach for studying quantum error-correcting codes. We apply it to various codes, such as self-dual CSS quantum codes modified from the two-dimensional honeycomb color code and non-CSS quantum codes that contain the double semion topological order or the six-semion topological order. Published by the American Physical Society 2024

Physics↗
DOE OSTI2026

Probing quantum entanglement with generalized parton distributions at the Electron-Ion Collider

Within the collinear factorization framework based on generalized parton distributions, we calculate the spin density matrix of exclusively produced quark and antiquark pairs $𝑢\bar{𝑢}$, $𝑑⁢\bar{d}$, $𝑠⁢\bar{𝑠}$, $𝑐\bar{⁢𝑐}$, $𝑏\bar{𝑏}$ in electron-proton scattering. The presence of both real and imaginary parts in the scattering amplitudes leads to a rich pattern of entanglement between the quark and the antiquark. We map out kinematical regions where the pairs exhibit entanglement, Bell nonlocality, and nonstabilizerness. We also predict that massive quarks and antiquarks are transversely polarized, similar to the well-known transverse hyperon polarization in unpolarized collisions. In strangeness, charm, and bottom productions, the polarization can reach 50%–80% in certain kinematic regions in the low-energy runs of the Electron-Ion Collider.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Generalized parton distributions from lattice QCD with asymmetric momentum transfer: Tensor case

The calculation of generalized parton distributions (GPDs) in lattice QCD was traditionally done by calculating matrix elements in the symmetric frame. Recent advancements have significantly reduced computational costs by calculating these matrix elements in the asymmetric frame, allowing us to choose the momentum transfer to be in either the initial or final states only. The theoretical methodology requires a new parametrization of the matrix element to obtain Lorentz-invariant amplitudes, which are then related to the GPDs. The formulation and implementation of this approachaveh already been established for the unpolarized and helicity GPDs. Building upon this idea, we extend this formulation to the four leading-twist quark transversity GPDs ($𝐻_𝑇$, $𝐸_𝑇$, $\tilde{𝐻}_𝑇$, $\tilde{𝐸}_𝑇$). We also present numerical results for zero skewness using an 𝑁 𝑓 = 2 +1 +1 ensemble of twisted mass fermions with a clover improvement. The light quark masses employed in these calculations correspond to a pion mass of about 260 MeV. Furthermore, we include a comparison between the symmetric and asymmetric frame calculations to demonstrate frame independence of the Lorentz-invariant amplitudes. Analysis of the matrix elements in the asymmetric frame is performed at several values of the momentum transfer squared, −𝑡, ranging from 0.17 to 2.29 GeV 2 .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Generalized susceptibilities and the properties of charm degrees of freedom across the QCD crossover temperature

We study the generalized charm susceptibilities in 2+1 flavor QCD on the lattice at several lattice spacings. We show that, below the chiral crossover, these susceptibilities are well described by the hadron resonance gas (HRG) model if charmed hadrons not listed in tables of the Particle Data Group are included. However, the HRG description abruptly breaks down just above the chiral crossover. To understand this, we use a model for the charm pressure in which it is expressed as the sum of partial pressures from charmed baryons, charmed mesons, and charm quarks. We present continuum estimates of these partial pressures and find that, while the partial pressures of charmed mesons and baryons drop below their respective HRG predictions, the charm quark pressure becomes nonzero above the chiral crossover.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Quantifying molecular deformation in polymer melts by a generalized Zimm plot approach

The Zimm plot has been widely used to characterize the molecular dimensions of polymers from small-angle scattering experiments, where the reciprocal intensity is analyzed as a function of the square of the magnitude of the scattering wavevector Q. Here, this work explores the benefits of analyzing the reciprocal scattering intensity from deformed polymers, extending the original Zimm plot to anisotropic materials. In the small-angle limit, a tensorial extension of the Guinier law is found for the gyration tensor and the reciprocal single-chain structure factor. In the high-Q limit, application of the spherical harmonic expansion technique to the reciprocal structure factor permits direct model-independent analysis of spatially dependent molecular deformation of polymers. Additionally, the contributions from high-order spherical harmonics become insignificant in the reciprocal-intensity representation. The proposed generalized Zimm plot approach is demonstrated computationally with the affine deformation model and the Rouse model, and experimentally with small-angle neutron scattering measurements of deformed polystyrene melts.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A general Bayesian algorithm for the autonomous alignment of beamlines

Autonomous methods to align beamlines can decrease the amount of time spent on diagnostics, and also uncover better global optima leading to better beam quality. The alignment of these beamlines is a high-dimensional expensive-to-sample optimization problem involving the simultaneous treatment of many optical elements with correlated and nonlinear dynamics. Bayesian optimization is a strategy of efficient global optimization that has proved successful in similar regimes in a wide variety of beamline alignment applications, though it has typically been implemented for particular beamlines and optimization tasks. In this paper, we present a basic formulation of Bayesian inference and Gaussian process models as they relate to multi-objective Bayesian optimization, as well as the practical challenges presented by beamline alignment. We show that the same general implementation of Bayesian optimization with special consideration for beamline alignment can quickly learn the dynamics of particular beamlines in an online fashion through hyperparameter fitting with no prior information. We present the implementation of a concise software framework for beamline alignment and test it on four different optimization problems for experiments on X-ray beamlines at the National Synchrotron Light Source II and the Advanced Light Source, and an electron beam at the Accelerator Test Facility, along with benchmarking on a simulated digital twin. We discuss new applications of the framework, and the potential for a unified approach to beamline alignment at synchrotron facilities.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Denial of Service Attack Detection via Differential Analysis of Generalized Entropy Progressions

Denial-of-Service (DoS) attacks are one the most common and consequential cyber attacks in computer networks. While existing research offers a plethora of detection methods, the issue of achieving scalability, a low false positive rate, and high detection accuracy remains open. In this work, we address this problem by developing a differential method based on generalized entropy progression. In this method, named as DoDGE, we continuously fit the line of best fit to the entropy progression of destination addresses and check if the derivative, that is, the slope of this line is less than the negative of the dynamically computed standard deviation of the derivatives. Furthermore, to distinguish from flash events, we leverage the symmetry that when a flash event occurs, the derivative of the entropy progression of source addresses is positive. With this design, we omit the usage of the thresholds and the results with five real-world network traffic datasets confirm that DoDGE outperforms threshold-based DoS attack detection by two orders of magnitude in terms of false positives on average. When compared to ten machine learning (ML) models, DoDGE achieves a balanced accuracy of 99%, while the average balanced accuracy for the ML models is 52%. Moreover, the results show that DoDGE successfully differentiates between a flash event and a DoS attack. Furthermore, since the main computation cost of DoDGE is the entropy computation, which is linear in the volume of the unit-time network flow, uses integer only operations, and works on a small fraction of the total flow, it is lightweight and scalable.

Cybersecurity, wireless communication↗
DOE OSTI2024

A General Framework for Error-controlled Unstructured Scientific Data Compression

Data compression plays a key role in reducing storage and I/O costs. Traditional lossy methods primarily target data on rectilinear grids and cannot leverage the spatial coherence in unstructured mesh data, leading to suboptimal compression ratios. We present a multi-component, error-bounded compression framework designed to enhance the compression of floating-point unstructured mesh data, which is common in scientific applications. Our approach involves interpolating mesh data onto a rectilinear grid and then separately compressing the grid interpolation and the interpolation residuals. This method is general, independent of mesh types and typologies, and can be seamlessly integrated with existing lossy compressors for improved performance. We evaluated our framework across twelve variables from two synthetic datasets and two real-world simulation datasets. The results indicate that the multi-component framework consistently outperforms state-of-the-art lossy compressors on unstructured data, achieving, on average, a 2.3 − 3.5× improvement in compression ratios, with error bounds ranging from 1 × 10 the −6 to 1×10−2. We further investigate impact of hyperparameters, such as grid spacing and error allocation, to deliver optimal compression ratios in diverse datasets.

Gong, Qian↗
DOE OSTI2020

A General Framework for Bounding Approximate Dynamic Programming Schemes

For years, there has been interest in approximation methods for solving dynamic programming problems, because of the inherent complexity in computing optimal solutions characterized by Bellman’s principle of optimality. A wide range of approximate dynamic programming (ADP) methods now exists. It is of great interest to guarantee that the performance of an ADP scheme be at least some known fraction, say ß , of optimal. This letter introduces a general approach to bounding the performance of ADP methods, in this sense, in the stochastic setting. The approach is based on new results for bounding greedy solutions in string optimization problems, where one has to choose a string (ordered set) of actions to maximize an objective function. This bounding technique is inspired by submodularity theory, but submodularity is not required for establishing bounds. Instead, the bounding is based on quantifying certain notions of curvature of string functions; the smaller the curvatures the better the bound. The key insight is that any ADP scheme is a greedy scheme for some surrogate string objective function that coincides in its optimal solution and value with those of the original optimal control problem. The ADP scheme then yields to the bounding technique mentioned above, and the curvatures of the surrogate objective determine the value ß of the bound. The surrogate objective and its curvatures depend on the specific ADP.

discrete event systems↗
DOE OSTI2025

Control-Affine Schrödinger Bridge and Generalized Bohm Potential

From a stochastic control perspective, the Schrödinger bridge is a density-valued continuous curve parameterized by time that connects a given pair of initial and terminal probability densities via minimum effort controlled Brownian motion. The control-affine Schrödinger bridge extends this idea to a generic control-affine Itô diffusion, possibly with an additive state cost. Here, in this letter, we recast the necessary conditions of optimality for the control-affine Schrödinger bridge problem as a two point boundary value problem for a quantum mechanical Schrödinger PDE with complex potential. This complex-valued potential is a generalization of the real-valued Bohm potential in quantum mechanics. Our derived potential is akin to the optical potential in nuclear physics where the real part of the potential encodes elastic scattering (transmission of wave function), and the imaginary part encodes inelastic scattering (absorption of wave function). The key takeaway is that the process noise that drives the evolution of probability densities induces an absorbing medium in the evolution of wave function. These results make new connections between control theory and non-equilibrium statistical mechanics through the lens of quantum mechanics.

Markov processes↗
DOE OSTI2020

Energy Storage Control Capability Expansion: Achieving Better Technoeconomic Benefits at Portland General Electric's Salem Smart Power Center

This article reports a transformative project aimed at enhancing the control capabilities of a Portland General Electric (PGE) owned 5 MW/1.25 MWh ESS located at Salem Smart Power Center (SSPC), Salem, Oregon, USA toward achieving better techno-economic benefit. Steps for developing a value-driven control capability is illustrated starting from evaluation of economic opportunities that drive the coordination of multiple services to be delivered by an ESS to implementation and testing. Lessons learned during critical processes are identified for the benefit of the ESS industry.

Alam, Md Jan E.↗
DOE OSTI2021

A Generalized Copula-Polynomial Chaos Expansion for Probabilistic Power Flow Considering Nonlinear Correlations of PV Injections

This paper develops a generalized Copula-polynomial chaos expansion (PCE) framework for power system probabilistic power flow that can handle both linear and nonlinear correlations of uncertain power injections, such as wind and PVs. A data-driven Copula statistical model is used to capture the correlations of uncertain power injections. This allows us to resort to the Rosenblatt transformation to transform correlated variables into independent ones while preserving the dependence structure. This paves the way of leveraging the PCE for surrogate modeling and uncertainty quantification of power flow results, i.e., achieving the probabilistic distributions of power flows. Simulations carried out on the IEEE 57-bus system show that the proposed framework can get much more accurate results than other alternatives with different linear and nonlinear power injection correlations.

copula↗
DOE OSTI2025

Linear Solver for Electromagnetic Simulation of General Distribution Feeders

High-fidelity electromagnetic transient (EMT) modeling is required for accurate simulation and analysis of power system dynamics in modern distribution feeders. However, the high-fidelity of EMT models often leads to significant computational challenges, particularly in terms of computational resources and simulation time. This paper investigates the development and application of a detailed EMT model for general distribution feeders, with a focus on improving computational efficiency. A direct linear solver is proposed for a bordered block diagonal (BBD) matrix structure commonly encountered in a EMT model of distribution feeders. The solver integrates the Schur complement method with the block tridiagonal matrix algorithm to enhance the computational performance. The proposed solver is validated using the primary feeder of the IEEE 342-node test system, demonstrating its accuracy and efficiency in EMT simulations. Furthermore, the solver’s performance is benchmarked against MATLAB’s built-in linear solvers, showing significant improvements in computation time while maintaining high fidelity and accuracy in simulation results.

Choi, Jongchan [ORNL] (ORCID:000000025952455X)↗
DOE OSTI2022

Spatiotemporal Modeling of Real World Backsheets Field Survey Data: Hierarchical (Multilevel) Generalized Additive Models

Assessing photovoltaic module backsheet durability is critical to increasing module lifetime. Laboratory-based accelerating testing has recently failed to predict large scale failures of widely adopted polymeric materials. Additionally, there is a growing concern on characterizing the non-uniformity of field exposure. Therefore, data from field surveys are critical to assess the performance of component lifetimes. Using a documented field survey protocol, 19 field surveys were conducted. The focus of this survey strategy is to investigate spatial continuity in degradation modes. By combining field survey data with real-time satellite weather data, stressor / response models have been trained. Generalized additive Models (GAM) model was created to predict the value of degradation based on measured predictors. Two different GAM constructions were testing using different implementations of basis splines. The model includes variables on the environmental stressors of the system and the location of each measurement in the PV mounting structure. The incorporation of hierarchical structure into the models allowed for material specific degradation rates, while maintaining the assumption of a global trend. The model performed well with an adjusted R2 of 0.975 for yellowness index prediction.

backsheet↗
DOE OSTI2023

Generalized Circuit Representation for a Synchronous Machine

In this letter, a generalized circuit representation for a synchronous machine is presented. This circuit represents voltage and current relationship and can be used for dynamic and harmonic analysis. A distinct feature of the circuit is the use of Laplace transform variable s , which simplifies both calculus and frame conversion. Two derivation approaches are presented. Here, the first approach starts from a steady-state circuit representation, while the second approach starts from the dq-frame dynamic model of a synchronous generator. Both arrive at the same representation.

42 ENGINEERING↗
DOE OSTI2024

Maximizing the Radar Generalized Image Quality Equation for Bistatic SAR Using Waveform Frequency Agility

The radar generalized image quality equation (RGIQE) is a metric used to measure both monostatic and bistatic synthetic aperture radar (BSAR) image quality, it is a function of signal-to-noise ratio (SNR) and 2-D bandwidth. The 2-D bandwidth is equal to the area of the transfer function’s (TF) passband region. With the exception of side-looking monostatic geometries, almost all monostatic and bistatic geometries have skewed passband shapes when waveform frequency parameters remain unchanged from pulse to pulse. Most synthetic aperture radar (SAR) applications require a rectangular-shaped passband region, this is achieved by inscribing a rectangular region within the skewed intrinsic passband region. Increasing skewness results in less inscription area reducing 2-D bandwidth, image SNR, and thus RGIQE capacity. In this article, a waveform with frequency agility is used to rectify the skewness that degrades RGIQE capacity. By changing the waveform’s center frequency and instantaneous bandwidth from pulse to pulse in a particular manner, the intrinsic passband region can be de-skewed. The de-skewed shape maximizes the inscription area thus maximizing 2-D bandwidth, image SNR, and RGIQE capacity. Here, three examples are given in this article, one monostatic geometry, and two bistatic geometries. RGIQE capacity is increased by 52.02%, 44.42%, and 79.09% for the three examples.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

A General Decentralized Dynamic State Estimation With Synchronous Generator Magnetic Saturation

We report the saturation of the nonlinear magnetic circuit of synchronous generators is often neglected when performing Kalman filter-based dynamic state estimation (DSE), yielding significant estimation bias. This letter addresses this problem and proposes a generalized DSE framework to handle magnetic saturation. Moreover, this letter derives a state initialization procedure that improves the Kalman filter tracking speed. The framework is flexible in dealing with different saturation functions and generator models. Numerical results on the Texas 2000-bus system verify the effectiveness of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

A general theory of avian migratory connectivity

Birds exhibit a remarkable array of seasonal migrations. Despite much research describing migratory behaviour, the underlying forces driving how a species’ breeding and wintering populations redistribute each year, that is, migratory connectivity, remain largely unknown. Here, we test the hypothesis that birds migrate in a way that minimises energy expenditure while considering intraspecific competition for energy acquisition, by developing a modelling framework that simulates an optimal redistribution of individuals between breeding and wintering areas. Using 25 species across the Americas, we find that the model accurately predicts empirical migration patterns, and thus offers a general explanation for migratory connectivity based on first ecological and energetic principles. Our model provides a strong basis for exploring additional processes underlying the ecology and evolution of migration, but also a framework for predicting how migration impacts local adaptation across seasons and how environmental change may affect population dynamics in migratory species.

60 APPLIED LIFE SCIENCES↗