Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “ambiguities”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11

A Bayesian interpretation of inconsistency measures in cosmology

Abstract Measures of inconsistency and tension between datasets have become an essential part of cosmological analyses. It is important to accurately evaluate the significance of such tensions when present. We propose here a Bayesian interpretation of inconsistency measures that can extract information about physical inconsistencies in the presence of data scatter. This new framework is based on the conditional probability distribution of the level of physical inconsistency given the obtained value of the measure. We use the index of inconsistency as a case study to illustrate the new interpretation framework, but this can be generalized to other metrics. Importantly, there are two aspects in the quantification of inconsistency that behave differently as the number of model parameters increases. The first is the probability for the level of physical inconsistency to reach a threshold which drops with the increase of the number of parameters under consideration. The second is the actual level of physical inconsistency which remains rather insensitive to such an increase in parameters. The difference between these two aspects is often overlooked, which leads to a long-standing ambiguity: when a given inconsistency is found between two constraints, its “significance” seems to be lower when considered in a higher-dimensional parameter space. This ambiguity is resolved by the Bayesian interpretation we introduce in this work because the conditional probability distribution includes all the statistical information of the level of physical inconsistency. Finally, we apply the Bayesian interpretation to examine the (in)consistency between Planck versus the Cepheid-based local measurement, the Dark Energy Survey (DES), the Atacama Cosmology Telescope (ACT) and WMAP. We confirm and revisit the degrees of previous physical inconsistencies and show the stability of the new interpretation with respect to the number of cosmological parameters compared to the commonly used n-σ interpretation when applied to cosmological tensions in multi-parameter spaces.

Astronomy & Astrophysics↗

Reanalysis of the top-quark pair hadroproduction and a precise determination of the top-quark pole mass at the LHC *

In this study, we calculate the $t\bar{t}$ pQCD production cross-section at the NNLO and determine the top-quark pole mass from recent measurements at the LHC at the center-of-mass energy $\sqrt{S}=13$ TeV to a high precision by applying the principle of maximum conformality (PMC). The PMC provides a systematic method that rigorously eliminates QCD renormalization scale ambiguities by summing the nonconformal $\beta$ contributions into the QCD coupling constant. The PMC predictions satisfy the requirements of renormalization group invariance, including renormalization scheme independence, and the PMC scales accurately reflect the virtuality of the underlying production subprocesses. By using the PMC, an improved prediction for the $t\bar{t}$ production cross-section is obtained without scale ambiguities, which in turn provides a precise value for the top-quark pole mass. Moreover, the prediction of PMC calculations that the magnitudes of higher-order PMC predictions are well within the error bars predicted from the known lower-order has been demonstrated for the top-quark pair production. The resulting determination of the top-quark pole mass, $m_t^{\rm{pole}}=172.5\pm1.4$ GeV, from the LHC measurement at $\sqrt{S}=13$ TeV agrees with the current world average cited by the Particle Data Group (PDG). The PMC prediction provides an important high-precision test of the consistency of pQCD and the SM at $\sqrt{S}=13$ TeV with previous LHC measurements at lower CM energies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The Lick Observatory Supernova Search follow-up program: photometry data release of 70 SESNe

We present BVRI and unfiltered (Clear) light curves of 70 stripped-envelope supernovae (SESNe), observed between 2003 and 2020, from the Lick Observatory Supernova Search follow-up program. Our SESN sample consists of 19 spectroscopically normal SNe Ib, 2 peculiar SNe Ib, six SNe Ibn, 14 normal SNe Ic, 1 peculiar SN Ic, 10 SNe Ic-BL, 15 SNe IIb, 1 ambiguous SN IIb/Ib/c, and 2 superluminous SNe. Our follow-up photometry has (on a per-SN basis) a mean coverage of 81 photometric points (median of 58 points) and a mean cadence of 3.6 d (median of 1.2 d). From our full sample, a subset of 38 SNe have pre-maximum coverage in at least one passband, allowing for the peak brightness of each SN in this subset to be quantitatively determined. We describe our data collection and processing techniques, with emphasis toward our automated photometry pipeline, from which we derive publicly available data products to enable and encourage further study by the community. Using these data products, we derive host-galaxy extinction values through the empirical colour evolution relationship and, for the first time, produce accurate rise-time measurements for a large sample of SESNe in both optical and infrared passbands. By modelling multiband light curves, we find that SNe Ic tend to have lower ejecta masses and lower ejecta velocities than SNe Ib and IIb, but higher 56Ni masses.

Lick Observatory↗

Isomers and hindrances in No254: A touchstone for theories of superheavy nuclei

We report on a new spectroscopic study of the decay of high-K isomers in No152102254, a touchstone nucleus for testing models to understand the structure of superheavy nuclei. The experiment, performed using the Argonne gas-filled analyzer (AGFA), was geared toward resolving long-standing ambiguities in spin-parity and configuration assignments for the two- and four-quasiparticle (qp) intrinsic excitations identified in this nucleus. The isomer decay schemes are firmly established with the help of the highest-statistics γ-γ coincidence data collected to date, providing anchor points for competing theories. A newly measured half-life in the nanosecond range establishes a second 2-qp isomer in No254. The preferred decay pathways for the 2- and 4-qp isomers are discussed, providing new insights into the underlying hindrance mechanisms at play in these heavy nuclei. With firm configuration assignments, the intrinsic excitations in this deformed mass region provide stringent constraints and challenge the different theoretical approaches at play in understanding the structure of superheavy nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Solid-Density Ion Temperature from Redshifted and Double-Peaked Stark Line Shapes

Heβ spectral line shapes are important for diagnosing temperature and density in many dense plasmas. This work presents Heβ line shapes measured with high spectral resolution from solid-density plasmas with minimized gradients. The line shapes show hallmark features of Stark broadening, including quantifiable redshifts and double-peaked structure with a significant dip between the peaks; these features are compared to models through a Markov chain Monte Carlo framework. Line shape theory using the dipole approximation can fit the width and peak separation of measured line shapes, but it cannot resolve an ambiguity between electron density n e and ion temperature T i , since both parameters influence the strength of quasistatic ion microfields. Here a line shape model employing a full Coulomb interaction for the electron broadening computes self-consistent line widths and redshifts through the monopole term; redshifts have different dependence on plasma parameters and thus resolve the n e – T i ambiguity. The measured line shapes indicate densities that are 80–100% of solid, identifying a regime of highly ionized but well-tamped plasma. This analysis also provides the first strong evidence that dense ions and electrons are not in thermal equilibrium, despite equilibration times much shorter than the duration of x-ray emission; cooler ions may arise from nonclassical thermalization rates or anomalous energy transport. Furthermore, the experimental platform and diagnostic technique constitute a promising new approach for studying ion-electron equilibration in dense plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Emergent Canonical Spin Tensor in the Chiral-Symmetric Hot QCD

The spin tensor is fundamental to relativistic spin hydrodynamics, but its definition is ambiguous due to the pseudogauge symmetry. We show that this ambiguity can be solved in interacting field theories. We prove that the mean-field limit of a modified Nambu-Jona-Lasinio model with spin-spin interactions is equivalent to nondissipative spin hydrodynamics with a canonical spin tensor. Published by the American Physical Society 2024

Buzzegoli, Matteo (ORCID:0000000221145431)↗

Development of a machine-learning-based ionic-force correction model for quantum molecular dynamic simulations of warm dense matter

In this work Δ learning is used to map orbital-free density functional theory (OF-DFT) ionic forces to the corresponding Kohn-Sham (KS) DFT ionic forces. The development of the approximate force difference in terms of the ion positions is constructed and serves as a stand in for the ground truth force difference. Descriptor vectors for ion configurations are constructed using all distance between ions in conjunction with an indexing based on a nearest neighbor ranking. It is demonstrated that such a scheme of descriptors can uniquely describe an ionic configuration up to a rotation and reflection when no ambiguity in the nearest neighbor ranking exists. How to handle the case when an ambiguity exists in the nearest neighbor ranking is discussed. As a proof of principle, the model is trained and tested on warm dense hydrogen at temperatures between 1 and 15 eV. Once tested, the model was used to perform molecular dynamic simulations of warm dense hydrogen. Furthermore, the resulting energies and pressures are within 1% and 2% of their respective target KS values.

36 MATERIALS SCIENCE↗

Regularization prescription for the mixing between nonlocal gluon and quark operators

It is well known that in the study of mixing between nonlocal gluon and quark bilinear operators there exists an ambiguity when relating coordinate space and momentum space results. In this work, we show that this ambiguity is due to the lack of a proper regularization prescription of the singularity that arises when the separation between the gluon/quark fields approaches zero. We then demonstrate that dimensional regularization resolves this issue and yields consistent results in both coordinate and momentum space. This prescription is also compatible with lattice extractions of parton distributions from nonlocal operators.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Distributionally Robust Decision Making Leveraging Conditional Distributions

Distributionally robust optimization (DRO) is a powerful tool for decision making under uncertainty. It is particularly appealing because of its ability to leverage existing data. However, many practical problems call for decision-making with some auxiliary information, and DRO in the context of conditional distributions is not straightforward. We propose a conditional kernel distributionally robust optimization (CKDRO) method that enables robust decision making under conditional distributions through kernel DRO and the conditional mean operator in the reproducing kernel Hilbert space (RKHS). In particular, we consider problems where there is a correlation between the unknown variable y and an auxiliary observable variable x. Given past data of the two variables and a queried auxiliary variable, CKDRO represents the conditional distribution P(y|x) as the conditional mean operator in the RKHS space and quantifies the ambiguity set in the RKHS as well, which depends on the size of the dataset as well as the query point. To justify the use of RKHS, we demonstrate that the ambiguity set defined in RKHS can be viewed as a ball under a metric that is similar to the Wasserstein metric. The DRO is then dualized and solved via a finite dimensional convex program. The proposed CKDRO approach is applied to a generation scheduling problem and shows that the result of CKDRO is superior to common benchmarks in terms of quality and robustness.

Chen, Yuxiao↗

Global Explainability of A Deep Abstaining Classifier for Cancer Pathology Reports

We present a global explainability method to characterize sources of errors in a real-world multitask deep abstaining classifier (DAC), in the context of cancer histology prediction. Our multitask classifier, currently deployed for automated annotation of cancer pathology reports from NCI-SEER registries, was trained and evaluated on 1.04 million hand-annotated samples and makes simultaneous predictions of cancer site, subsite, histology, laterality, and behavior for each report. The DAC framework enables the model to abstain on ambiguous reports and confusing classes to achieve the target accuracy on the retained (non-abstained) samples, but at the cost of decreased coverage. Requiring 97% accuracy on the histology task caused our model to retain only 22% of all samples, mostly the less ambiguous and common classes. Local explainability with the GradInp technique provided a computationally efficient way of obtaining contextual reasoning for hundreds of thousands of individual predictions. Our method, involving dimensionality reduction of approximately 13000 aggregated local explanations (ALE), offers a tractable path to true global explainability. It enabled identification of sources of errors in histology classification, globally, as hierarchical complexity among classes, label noise, insufficient information, and conflicting evidence. This suggests several strategies for iterative improvement of our DAC, including well-designed exclusion criteria, focused annotation, and reduced penalties for errors involving hierarchically related classes.

59 BASIC BIOLOGICAL SCIENCES↗

Deciphering spin-parity assignments of nuclear levels

Spin-parity assignments of nuclear levels are critical for understanding nuclear structure and reactions. However, inconsistent notation conventions and ambiguous reporting in research papers often lead to confusion and misinterpretations. Here, this paper examines the policies of the Evaluated Nuclear Structure Data File (ENSDF) and the evaluations by Endt and collaborators, highlighting key differences in their approaches to spin-parity notation. Sources of confusion are identified, including ambiguous use of strong and weak arguments and the conflation of new experimental results with prior constraints. Recommendations are provided to improve clarity and consistency in reporting spin-parity assignments, emphasizing the need for explicit notation conventions, clear differentiation of argument strengths, community education, and separate reporting of new findings. These steps aim to enhance the accuracy and utility of nuclear data for both researchers and evaluators.

Experimental Nuclear Physics↗

Frontal Maintenance in Submesoscale Flows

Classic deformation theory includes parameters—divergence, total strain, and vorticity—that are invariant to changes in the coordinate system. However, these parameters are sometimes ambiguous with respect to characterizing how fronts are formed and maintained because the presence of a front imposes a reference coordinate system. To help remedy this ambiguity, we propose a framework in frontal coordinates based on along- and cross-front velocity gradients to better characterize frontal maintenance, which can also be used to define divergence and normal strain in frontal coordinates. The framework with these four parameters (along-, cross-front velocity gradients, divergence, and normal strain in frontal coordinate) defines eight characteristic flow types at a front, providing a complete characterization of the flow that strengthens or weakens a front. This framework highlights the importance of the “strain efficiency” concept, which unambiguously defines the contribution of total strain to frontogenesis. Two examples, one based on a realistic simulation of submesoscales in the northern Gulf of Mexico and the other based on an idealized model with similar flow characteristics, are provided to demonstrate how this framework can be used to enhance our understanding of frontal dynamics in submesoscale flows.

frontogenesis↗

PMC$_\infty$: Infinite-Order Scale-Setting method using the Principle of Maximum Conformality and preserving the Intrinsic Conformality

We show results for Thrust and C-parameter in e^+ e^- e + e − annihilation to 3 jets obtained using the recently developed new method for eliminating the scale ambiguity and the scheme dependence in pQCD namely the Infinite-Order Scale-Setting method using the Principle of Maximum Conformality (PMC _\infty ∞ ). This method preserves an important underlying property of gauge theories: intrinsic Conformality (iCF). It leads to a remarkably efficient method to eliminate the conventional renormalization scale ambiguity at any order in pQCD. A comparison with Conventional Scale Setting method (CSS) is also shown.

Di Giustino, Leonardo↗

High-Reliability Systems and the Control of National Security Data and Information

High-reliability systems are characterized by catastrophic implications in the event of failure. These implications can include substantive damage to the environment, social order, and loss of life. Examples of high-reliability systems include nuclear submarines, nuclear reactors, the electric grid, and nuclear weapons. Due to the catastrophic implications of failure, there are heightened awareness and control mechanisms surrounding related data and information. However, defining the difference between data and information is often ambiguous across scholarly disciplines and in United States policy and legislation. For high-reliability systems, the implications of ambiguity between data and information may affect the security of United States interests and even cost lives. For security, data are raw facts or figures without context, while information is the compilation or articulation of data that forms context. Security depends on clarity in the differences between data and information and how to control them. Control is necessary to ensure that data and information are not unintentionally released to foreign governments, the public, or those without need-to-know. A primary concern in the practice of security is the control of data to avoid the unintended conversion to information. Intra-institutionally, this control is highly complex given the amalgam of legacy data systems and the numerous and constantly evolving nature of modern data systems that were not necessarily designed to be integrated. The complexity of this concern is augmented when institutions are part of interinstitutional collaborations or networks of public-private partnerships that share data and information. Additionally, institutions that share data as a function of policy and legislative action— particularly formally integrated data and information system infrastructures—may be at higher security risk. This paper will present an intra-institutional paradigm that utilizes and integrates concepts from numerous disciplines to frame a critical and underspecified practical issue in security—controlling for the unintended conversion of data to information.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

High-Reliability Systems and the Control of National Security Data and Information

High-reliability systems are characterized by catastrophic implications in the event of failure. These implications can include substantive damage to the environment, social order, and loss of life. Examples of high-reliability systems include nuclear submarines, nuclear reactors, the electric grid, and nuclear weapons. Due to the catastrophic implications of failure, there are heightened awareness and control mechanisms surrounding related data and information. However, defining the difference between data and information is often ambiguous across scholarly disciplines and in United States policy and legislation. For high-reliability systems, the implications of ambiguity between data and information may affect the security of United States interests and even cost lives. For security, data are raw facts or figures without context, while information is the compilation or articulation of data that forms context. Security depends on clarity in the differences between data and information and how to control them. Control is necessary to ensure that data and information are not unintentionally released to foreign governments, the public, or those without need-to-know. A primary concern in the practice of security is the control of data to avoid the unintended conversion to information. Intra-institutionally, this control is highly complex given the amalgam of legacy data systems and the numerous and constantly evolving nature of modern data systems that were not necessarily designed to be integrated. The complexity of this concern is augmented when institutions are part of inter-institutional collaborations or networks of public-private partnerships that share data and information. Additionally, institutions that share data as a function of policy and legislative action—particularly formally integrated data and information system infrastructures—may be at higher security risk. This paper will present an intra-institutional paradigm that utilizes and integrates concepts from numerous disciplines to frame a critical and underspecified practical issue in security—controlling for the unintended conversion of data to information.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Outlier classification using autoencoders: application for fluctuation driven flows in fusion plasmas

Understanding the statistics of fluctuation driven flows in the boundary layer of magnetically confined plasmas is desired to accurately model the lifetime of the vacuum vessel components. Mirror Langmuir probes (MLPs) are a novel diagnostic that uniquely allow us to sample the plasma parameters on a time scale shorter than the characteristic time scale of their fluctuations. Sudden large-amplitude fluctuations in the plasma degrade the precision and accuracy of the plasma parameters reported by MLPs for cases in which the probe bias range is of insufficient amplitude. While some data samples can readily be classified as valid and invalid, we find that such a classification may be ambiguous for up to 40% of data sampled for the plasma parameters and bias voltages considered in this study. In this contribution, we employ an autoencoder (AE) to learn a low-dimensional representation of valid data samples. By definition, the coordinates in this space are the features that mostly characterize valid data. Ambiguous data samples are classified in this space using standard classifiers for vectorial data. In this way, we avoid defining complicated threshold rules to identify outliers, which require strong assumptions and introduce biases in the analysis. By removing the outliers that are identified in the latent low-dimensional space of the AE, we find that the average conductive and convective radial heat fluxes are between approximately 5% and 15% lower as when removing outliers identified by threshold values. For contributions to the radial heat flux due to triple correlations, the difference is up to 40%.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

On the detection of differentially encoded polyphase signals.

Consideration of the transmission and detection of differentially encoded multiple phase-shift-keyed (MPSK) signals, paying particular attention to the ambiguity resolution problem resulting from suppression of the transmitted carrier. A study is made of the coherent detection of differentially encoded MPSK signals, and the performance of a differentially encoded MPSK system is compared with that of a system which transmits absolutely encoded polyphase signals and performs perfect ambiguity resolution. Both the perfect and noisy reference signal cases are treated. Also, the performance of coherent detection of differentially encoded MPSK signals is compared with that of differentially coherent reception of the same signal set.

Lindsey, W. C.↗