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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Generalized Quantum Signal Processing

Quantum signal processing (QSP) and quantum singular value transformation (QSVT) currently stand as the most efficient techniques for implementing functions of block-encoded matrices, a central task that lies at the heart of most prominent quantum algorithms. However, current QSP approaches face several challenges, such as the restrictions imposed on the family of achievable polynomials and the difficulty of calculating the required phase angles for specific transformations. In this paper, we present a generalized quantum signal processing (GQSP) approach, employing general SU(2) rotations as our signal-processing operators, rather than relying solely on rotations in a single basis. Our approach lifts all practical restrictions on the family of achievable transformations, with the sole remaining condition being that | P | ≤ 1 , a restriction necessary due to the unitary nature of quantum computation. Furthermore, GQSP provides a straightforward recursive formula for determining the rotation angles needed to construct the polynomials in cases where P and Q are known. In cases where only P is known, we provide an efficient optimization algorithm capable of identifying in under a minute of GPU time, a corresponding Q for polynomials of degree on the order of 10 7 . We further illustrate GQSP simplifies QSP-based strategies for Hamiltonian simulation, offer an optimal solution to the ϵ -approximate fractional query problem that requires O ( ( 1 / δ ) + log ( 1 / ϵ ) ) queries to perform where O ( 1 / δ ) is a proved lower bound, and introduces novel approaches for implementing bosonic operators. Moreover, we propose a novel framework for the implementation of normal matrices, demonstrating its applicability through synthesis of diagonal matrices, as well as the development of a new algorithm for convolution through synthesis of circulant matrices using only O ( d log N + log 2 N ) 1 and 2-qubit gates for a filter of lengths d . Published by the American Physical Society 2024

Motlagh, Danial↗
DOE OSTI2025

Distributed Stochastic Optimization of a Neural Representation Network for Time-Space Tomography Reconstruction

4D time-space reconstruction of dynamic events or deforming objects using X-ray computed tomography (CT) is an important inverse problem in non-destructive evaluation. Conventional back-projection based reconstruction methods assume that the object remains static for the duration of several tens or hundreds of X-ray projection measurement images (reconstruction of consecutive limited-angle CT scans). However, this is an unrealistic assumption for many in-situ experiments that causes spurious artifacts and inaccurate morphological reconstructions of the object. To solve this problem, we propose to perform a 4D time-space reconstruction using a distributed implicit neural representation (DINR) network that is trained using a novel distributed stochastic training algorithm. Our DINR network learns to reconstruct the object at its output by iterative optimization of its network parameters such that the measured projection images best match the output of the CT forward measurement model. Here, we use a forward measurement model that is a function of the DINR outputs at a sparsely sampled set of continuous valued 4D object coordinates. Unlike previous neural representation architectures that forward and back propagate through dense voxel grids that sample the object's entire time-space coordinates, we only propagate through the DINR at a small subset of object coordinates in each iteration resulting in an order-of-magnitude reduction in memory and compute for training. DINR leverages distributed computation across several compute nodes and GPUs to produce high-fidelity 4D time-space reconstructions. We use both simulated parallel-beam and experimental cone-beam X-ray CT datasets to demonstrate the superior performance of our approach.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Nearly quantized conductance plateau of vortex zero mode in an iron-based superconductor

Majorana zero modes (MZMs) are spatially-localized zero-energy fractional quasiparticles with non-Abelian braiding statistics that hold promise for topological quantum computing. Owing to the particle-antiparticle equivalence, MZMs reflect quantized conductance at low temperature. By utilizing variable-tunnel-coupled scanning tunneling spectroscopy, we study tunneling conductance of vortex bound states on FeTe 0.55 Se 0.45 superconductors. Here, we report observations of conductance plateaus as a function of tunnel coupling for zero-energy vortex bound states with values close to or even reaching the 2 e 2 / h quantum conductance (here e is the electron charge and h is Planck’s constant). In contrast, no plateaus were observed on either finite energy vortex bound states or in the continuum of electronic states outside the superconducting gap. This behavior of the zero-mode conductance confirms the existence of MZMs in FeTe 0.55 Se 0.45 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Measurement of the ${\mathrm {t}\overline{\mathrm {t}}}$ production cross section, the top quark mass, and the strong coupling constant using dilepton events in pp collisions at $\sqrt{s}=13\,\text {Te}\text {V} $

A measurement of the top quark-antiquark pair production cross section $\sigma_{\mathrm{t\overline{t}}}$ in proton-proton collisions at a centre-of-mass energy of 13 TeV is presented. The data correspond to an integrated luminosity of 35.9 fb$^{-1}$, recorded by the CMS experiment at the CERN LHC in 2016. Dilepton events (e$^\pm\mu^\mp$, $\mu^+\mu^-$, e$^+$e$^-$) are selected and the cross section is measured from a likelihood fit. For a top quark mass parameter in the simulation of $m^{\mathrm{MC}}_{\mathrm{t}} =$ 172.5 GeV the fit yields a measured cross section $\sigma_{\mathrm{t\overline{t}}} =$ 803 $\pm$ 2 (stat) $\pm$ 25 (syst) $\pm$ 20 (lumi) pb, in agreement with the expectation from the standard model calculation at next-to-next-to-leading order. A simultaneous fit of the cross section and the top quark mass parameter in the POWHEG simulation is performed. The measured value of $m^{\mathrm{MC}}_{\mathrm{t}} =$ 172.33 $\pm$ 0.14 (stat) $^{+0.66}_{-0.72}$ (syst) GeV is in good agreement with previous measurements. The resulting cross section is used, together with the theoretical prediction, to determine the top quark mass and to extract a value of the strong coupling constant with different sets of parton distribution functions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Hyper Spectral Anomaly Detection

The HSA is a statistics based anomaly detection model. The model performs unsupervised anomaly detection, based on a datapoint's density and similarity within a dataset. Density and similarity data are encoded into an affinity matrix. The affinity matrix is evolved to summarize the data's structure on greater topographical scales within the data's function space. The set of evolved affinity matrices and an anomaly score vector are passed to a user defined penalized objective function. The penalized objective function of anomaly scores is then minimized. Data points where the absolute value of the z-scores of anomaly scores greater than a specified threshold are predicted as anomalies. A novel multi-filter feature has also been implemented. To reduce false positive rates, the multi-filter records the indexes of the HSA predictions. A new dataset and data loader are instantiated consisting of all the initial HSA predictions and non-anomalous data points in a 10% and 90% split respectively. The HSA is then run through this data set and a count of number of times a data point is predicted is kept. In this way the initial predictions may be compared with data spanning the entire dataset. After the multi-filter is complete, all datapoints will have an associated anomaly score, as well as a multi-filter prediction count to further filter the anomalous predictions.

Rogers, DempseyD [Idaho National Laboratory (INL),↗
DOE OSTI2018

Strong correlation between stress drop and peak ground acceleration for recent M1–4 earthquakes in the San Francisco Bay Area

Theoretical and observational studies suggest that between-event variability in the median ground motions of larger ( M≥5 ) earthquakes is controlled primarily by the dynamic properties of the earthquake source, such as Brune-type stress drop. Analogous results remain equivocal for smaller events due to the lack of comprehensive and overlapping ground-motion and source-parameter datasets in this regime. Here in this paper, we investigate the relationship between peak ground acceleration (PGA) and dynamic stress drop for a new dataset of 5297 earthquakes that occurred in the San Francisco Bay area from 2002 through 2016. For each event, we measure PGA on horizontal-component channels of stations within 100 km and estimate stress drop from P-wave spectra recorded on vertical-component channels of the same stations. We then develop a nonparametric ground-motion prediction equation (GMPE) applicable for the moderate (M 1–4) earthquakes in our study region, using a mixed-effects generalization of the Random Forest algorithm. We use the Random Forest GMPE to model the joint influence of magnitude, distance, and near-site effects on observed PGA. We observe a strong correlation between dynamic stress drop and the residual PGA of each event, with the events with higher-than-expected PGA associated with higher values of stress drop. The strength of this correlation increases as a function of magnitude but remains significant even for smaller magnitude events with corner frequencies that approach the observable bandwidth of the acceleration records. Mainshock events are characterized by systematically higher stress drop and PGA than aftershocks of equivalent magnitude. Coherent local variations in the distribution of dynamic stress drop provide observational constraints to support the future development of nonergodic GMPEs that account for variations in median stress drop at different source locations.

58 GEOSCIENCES↗
DOE OSTI2017

Impurity Content Optimization to Maximize Q-Factors of Superconducting Resonators

Quality factor of superconducting radio-frequency (SRF) cavities is degraded whenever magnetic flux is trapped in the cavity walls during the cooldown. In this contribution we study how the trapped flux sensitivity, defined as the trapped flux surface resistance normalized for the amount of trapped flux, depends on the mean free path. A systematic study of a variety of 1.3 GHz cavities with different surface treatments (EP, 120 C bake and different N-doping) is carried out. A bell shaped trend appears for the range of mean free path studied. Over-doped cavities fall at the maximum of this curve defining the largest values of sensitivity. In addition, we have studied the trend of the BCS surface resistance contribution as a function of mean free path, showing that N-doped cavities follow close to the theoretical minimum. Adding these results together we show that the 2/6 N-doping treatment gives the highest Q-factor values at 2 K and 16 MV/m, as long as the magnetic field fully trapped during the cavity cooldown is lower than 10 mG.

43 PARTICLE ACCELERATORS↗
DOE OSTI2017

The Future of Centrally-Organized Wholesale Electricity Markets

The electricity grid in the United States is organized around a network of large, centralized power plants and high voltage transmission lines that transport electricity, sometimes over large distances, before it is delivered to the customer through a local distribution grid. This network of centralized generation and high voltage transmission lines is called the “bulk power system.” Costs relating to bulk power generation typically account for more than half of a customer’s electric bill.1 For this reason, the structure and functioning of wholesale electricity markets have major impacts on costs and economic value for consumers, as well as energy security and national security. Diverse arrangements for bulk power wholesale markets have evolved over the last several decades. The Southeast and Western United States outside of California have a “bilateral-based” bulk power system where market participants enter into long-term bilateral agreements — using competitive procurements through power marketers, direct arrangements among utilities or with other generation owners, and auctions and exchanges.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Potential for Transactive Energy to Improve the Provisioning of Grid Services from Batteries

This study assessed the degree to which transactive energy systems could help reduce or remove barriers to the deployment of battery energy storage, and realize the full potential of battery resources to supply needed services to the grid and fairly compensate various types of battery owners. To enable this assessment, typical battery deployments were characterized, along with energy markets, Federal Energy Regulatory Commission Order rulings and implementations, grid services, and current deployment barriers. Finally, this study analyzed the value that accrues to batteries supplying today’s grid services as a function of the participation models associated with three primary types of battery ownership: merchant-owned transmission-connected batteries; utility-owned distribution-connected batteries; and customer-owned behind-the-meter batteries. This provided both quantitative and qualitative assessments comparing opportunities for battery storage in business-as-usual and transactive energy scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Discerning Deception: An Empirically-Driven Agent-Based Model of Expert Evaluation of Scientific Content

Both human subject experiments and computational, modeling and simulations have been used to study detection of deception. This work aims to combine these two methods by integrating empirically-derived information (from human subject experiments) into agent-based models to generate novel insights into the complex problems of detection of disinformation content. Computational experiments are used to simulate across multiple scenarios for evaluation and decision-making regarding the validity of potentially deceptive scientific documents. Factors influencing the human agent behaviors in the model were identified through a human subject experiment that was conducted to evaluate and characterize decision making related to disinformation discernment. Correlation and regression analyses were used to translate insights from the human subjects experiment to inform the parameterization of agent features and scenario development. Three scenarios were evaluated with the agent-based models to help evaluate the replicability of the simulations (validation analysis) and assess the influence of human agent and document features (sensitivity analyses). A replication of the human participant experiment demonstrated that the agent-based simulations compare favorably to empirical findings. The agent-based modeling was then used to conduct sensitivity analysis on the accuracy of deception detection as a function of document proportions and human agent features. Results indicate that precision values are adversely impacted when the proportion of deceptive documents is lower in the overall sample, whereas recall values are more sensitive to changes in human agent features. These findings indicate important nuances in accuracy evaluations that should be further considered (including consideration of potential alternate metrics) in future agent-based models of disinformation. Additional areas for future exploration include extension of simulations to consider other ways to align the agent-based model design with psychological theory and inclusion of agent-agent interactions, especially as it pertains to sharing of scientific information within an organizational context.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Optimization of the artificial viscosity in Lagrangian staggered discretization codes. Modeling 1D stand-alone shock - case study

We have developed new measures of errors for numerical shock. The new approach is based on analysis of the structure function, and separation of the errors related to oscillations and shock width, which also include error in the position of the ”center” of the numerical shock. We have demonstrated that those measures correctly characterize the numerical solution. We introduced an objective function in, which both types of errors are weighted, and presented optimal values of the coefficients of the linear and quadratic viscosity for different weights and different Mach numbers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Criteria for Retention of 3013 S1 Containers Based on Relative Risk and Expert Judgment

An evaluation was performed to assess the suitability of thirty-three 3013 containers proposed for retention. These containers have moisture levels greater than 0.08 wt.% – the S1 population. The remainder of the S1 population stored at SRS will be down blended and disposed of by the end of 2028. Based on field surveillance and shelf-life data available to date as well as informed technical judgment, no container is currently expected to fail in its 50-year storage period. However, corrosion risk varies across the S1 population. Relative risks were evaluated using predicted Consensus Scores and their 95% Upper Prediction Limits (UPLs). The predicted values are based on a statistical model of Consensus Score as a function of moisture, chloride, and whether the packaged material was electrorefining scrap packaged at Hanford. Consensus Score has been shown to be a useful indicator of corrosion potential, and the UPL captures uncertainty in the model predictions, providing a conservative indicator of corrosion potential. Using UPLs to determine relative risks, together with expert review, three containers were identified as not suitable for retention, and the remainder were determined to be suitable.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

X-Ray Bolometric Corrections for Compton-thick Active Galactic Nuclei

We present X-ray bolometric correction factors, κ{sub Bol} (≡L{sub Bol}/L{sub X}), for Compton-thick (CT) active galactic nuclei (AGNs) with the aim of testing AGN torus models, probing orientation effects, and estimating the bolometric output of the most obscured AGNs. We adopt bolometric luminosities, L{sub Bol}, from literature infrared (IR) torus modeling and compile published intrinsic 2–10 keV X-ray luminosities, L{sub X}, from X-ray torus modeling of NuSTAR data. Our sample consists of 10 local CT AGNs, where both of these estimates are available. We test for systematic differences in κ{sub Bol} values produced when using two widely used IR torus models and two widely used X-ray torus models, finding consistency within the uncertainties. We find that the mean κ{sub Bol} of our sample in the range of L{sub Bol}≈10{sup 42}--10{sup 45} erg s{sup −1} is log{sub 10} κ{sub Bol} = 1.44 ± 0.12 with an intrinsic scatter of ∼0.2 dex, and that our derived κ{sub Bol} values are consistent with previously established relationships between κ{sub Bol} and L{sub Bol} and κ{sub Bol} and Eddington ratio (λ{sub Edd}). We investigate if κ{sub Bol} is dependent on N{sub H} by comparing our results on CT AGNs to published results on less-obscured AGNs, finding no significant dependence. Since many of our sample are megamaser AGNs, known to be viewed edge-on, and furthermore under the assumptions of AGN unification whereby unobscured AGNs are viewed face-on, our result implies that the X-ray emitting corona is not strongly anisotropic. Finally, we present κ{sub Bol} values for CT AGNs identified in X-ray surveys as a function of their observed L{sub X}, where an estimate of their intrinsic L{sub X} is not available, and redshift, useful for estimating the bolometric output of the most obscured AGNs across cosmic time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

The impact of kidney function on Alzheimer’s disease blood biomarkers: implications for predicting amyloid-β positivity

Impaired kidney function has a potential confounding effect on blood biomarker levels, including biomarkers for Alzheimer’s disease (AD). Given the imminent use of certain blood biomarkers in the routine diagnostic work-up of patients with suspected AD, knowledge on the potential impact of comorbidities on the utility of blood biomarkers is important. We aimed to evaluate the association between kidney function, assessed through estimated glomerular filtration rate (eGFR) calculated from plasma creatinine and AD blood biomarkers, as well as their influence over predicting Aβ-positivity. We included 242 participants from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort, comprising cognitively unimpaired individuals (CU; n = 124), mild cognitive impairment (MCI; n = 58), AD dementia (n = 34), and non-AD dementia (n = 26) patients all characterized by [ 18 F] AZD-4694. Plasma samples were analyzed for Aβ42, Aβ40, glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), tau phosphorylated at threonine 181 (p-tau181), 217 (p-tau217), 231 (p-tau231) and N-terminal containing tau fragments (NTA-tau) using Simoa technology. Kidney function was assessed by eGFR in mL/min/1.73 m 2 , based on plasma creatinine levels, age, and sex. Participants were also stratified according to their eGFR-indexed stages of chronic kidney disease (CKD). We evaluated the association between eGFR and blood biomarker levels with linear models and assessed whether eGFR provided added predictive value to determine Aβ-positivity with logistic regression models. Biomarker concentrations were highest in individuals with CKD stage 3, followed by stages 2 and 1, but differences were only significant for NfL, Aβ42, and Aβ40 (not Aβ42/Aβ40). All investigated biomarkers showed significant associations with eGFR except plasma NTA-tau, with stronger relationships observed for Aβ40 and NfL. However, after adjusting for either age, sex or Aβ-PET SUVr, the association with eGFR was no longer significant for all biomarkers except Aβ40, Aβ42, NfL, and GFAP. When evaluating whether accounting for kidney function could lead to improved prediction of Aβ-positivity, we observed no improvements in model fit (Akaike Information Criterion, AIC) or in discriminative performance (AUC) by adding eGFR to a base model including each plasma biomarker, age, and sex. While covariates like age and sex improved model fit, eGFR contributed minimally, and there were no significant differences in clinical discrimination based on AUC values. We found that kidney function seems to be associated with AD blood biomarker concentrations. However, these associations did not remain significant after adjusting for age and sex, except for Aβ40, Aβ42, NfL, and GFAP. While covariates such as age and sex improved prediction of Aβ-positivity, including eGFR in the models did not lead to improved prediction for any biomarker. Our findings indicate that renal function, within the normal to mild impairment range, does not seem to have a clinically relevant impact when using highly accurate blood biomarkers, such as p-tau217, in a biomarker-supported diagnosis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Achieving accurate energetics beyond (semi-)local density functional theory: Illustrated with transition metal disulfides, Cu 2 ZnSnS 4 , and Na 3 PS 4 related semiconductors

Understanding, designing, and processing functional metal sulfides are significant challenges partially because of the high temperatures and pressures and the number of secondary phases encountered in these complex systems. In particular, the underlying thermochemical properties are not well understood that would allow prediction of equilibrium conditions and driving forces. In addition, obtaining accurate values for the energetics of metal sulfide systems is far from complete, suggesting application of density functional theory (DFT) calculations. Here, the results of an examination of 69 phases by DFT using 12 exchange-correlation (X-C) functionals indicate that (i) the key source of error in predicting the Gibbs energy of a phase is the enthalpy calculated at 0 K rather than entropy at finite temperatures from phonon calculations and (ii) an improved prediction of the thermodynamic properties at 0 K relies on the selected nonlocal X-C functional such as the hybrid potential. Regarding metal sulfides, we conclude from the present DFT results that (1) the secondary phase Cu 2 ZnSn 3 S 8 , associated with the desired photovoltaic material Cu 2 ZnSnS 4 , is not stable at 0 K, but it becomes slightly stable with increasing temperature (i.e., >800 K), primarily due to the vibrational entropy, which makes it difficult to be detected in a typical thin-film growth process; (2) the hybrid X-C functional improves the predicted energetics for most of the layered transition-metal disulfides such as TiS 2 , MoS 2 , and WS 2 , but not for the nonlayered RuS 2 , OsS 2 , and IrS 2 as well as the layered PdS 2 ; and (3) the formation of the solid-state electrolyte Na3PS4 is thermodynamically favored. We further conclude that accurate energetics as a function of temperature for the materials of interest is feasible to be achieved beyond the semilocal DFT calculations with the key being enthalpy predicted at 0 K.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Fundamental Solutions for Two-Point Boundary Value Problems in Orbital Mechanics

We consider a two-point boundary value problem (TPBVP) in orbital mechanics involving a small body (e.g., a spacecraft or asteroid) and N larger bodies. The least action principle TPBVP formulation is converted into an initial value problem via the addition of an appropriate terminal cost to the action functional. The latter formulation is used to obtain a fundamental solution, which may be used to solve the TPBVP for a variety of boundary conditions within a certain class. In particular, the method of convex duality allows one to interpret the least action principle as a differential game, where an opposing player maximizes over an indexed set of quadratics to yield the gravitational potential. In the case where the time duration is less than a specific bound, there exists a unique critical point for the resulting differential game, which yields the fundamental solution given in terms of the solutions of associated Riccati equations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Analysis of the Spectral Stability of the Generalized Runge–Kutta Methods Applied to Initial-Boundary-Value Problems for Equations of the Parabolic Type. I. Explicit Methods

We develop a general algorithm for the analysis the spectral stability of generalized multistage Runge–Kutta methods of various orders of accuracy as applied to the numerical integration with respect to time of an initial-boundary-value problem for the second-order parabolic equation. The expression for the function of spectral stability is obtained in two alternative forms: on the basis of matrix relations and in the determinant form. We study specific realizations of various generalized explicit Runge–Kutta methods and their spectral stability. It is shown that all explicit generalized Runge–Kutta methods possess the property of conditional spectral stability and the property of conditional monotonicity of the numerical solution in time whose violation leads to the appearance of false oscillations of the approximate solution. The stability function for these methods is polynomial. It is shown that the application of two-stage generalized explicit Runge–Kutta methods leads to the appearance of predictor-corrector-type schemes. In the case of nonstationary one-dimensional heat-conduction problem, on the basis of a one-stage generalized Runge–Kutta method, we obtain the classical two-layer conditionally stable explicit finite-difference scheme on a four-point template. It is demonstrated that the five-stage generalized Runge–Kutta–Merson method is characterized by the weakest condition of spectral stability as compared with all investigated explicit generalized Runge–Kutta methods.

42 ENGINEERING↗
DOE OSTI2026

Characterization of nuclear breakup as a function of hard-scattering kinematics using dijets measured by ATLAS in p+Pb collisions

This Letter analyzes the sensitivity of event geometry estimators to the initial-state kinematics of hard scattering in proton–lead collisions. This analysis uses dijets as a proxy for the parton–parton scattering configuration, correlating it with event geometry estimators, namely the energy deposited in the Zero-Degree Calorimeter and the transverse energy recorded in the Forward Calorimeter in the Pb-going direction. The analysis uses data recorded by the ATLAS detector at the Large Hadron Collider with a nucleon–nucleon center-of-mass energy of 8.16 TeV, corresponding to an integrated luminosity of 56 nb − 1 . The jets are measured within the pseudorapidity interval −2.8 < η < 4.5, where positive η values correspond to the direction of the proton beam. Results are presented as a function of the Bjorken-x of the parton originating from the proton, xp . Both event geometry estimators are found to be dependent on xp , with the energy deposited in the Zero-Degree Calorimeter about six times less sensitive to xp compared with the transverse energy deposited in the Forward Calorimeter.

Aad, G↗