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All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Comparison of scientific and administrative database management systems

Some characteristics found to be different for scientific and administrative data bases are identified and some of the corresponding generic requirements for data base management systems (DBMS) are discussed. The requirements discussed are especially stringent for either the scientific or administrative data bases. For some, no commercial DBMS is fully satisfactory, and the data base designer must invent a suitable approach. For others, commercial systems are available with elegant solutions, and a wrong choice would mean an expensive work-around to provide the missing features. It is concluded that selection of a DBMS must be based on the requirements for the information system. There is no unique distinction between scientific and administrative data bases or DBMS. The distinction comes from the logical structure of the data, and understanding the data and their relationships is the key to defining the requirements and selecting an appropriate DBMS for a given set of applications.

Stoltzfus, J. C.↗
DOE OSTI2026

Multi-Modal Bayesian Neural Network Surrogates with Conjugate Last-Layer Estimation

As data collection and simulation capabilities advance, multi-modal learning, the task of learning from multiple modalities and sources of data, is becoming an increasingly important area of research. Surrogate models that learn from data of multiple auxiliary modalities to support the modeling of a highly expensive quantity of interest have the potential to aid outer loop applications such as optimization, inverse problems, or sensitivity analyses when multi-modal data are available. We develop two multi-modal Bayesian neural network surrogate models and leverage conditionally conjugate distributions in the last layer to estimate model parameters using stochastic variational inference (SVI). We provide a method to perform this conjugate SVI estimation in the presence of partially missing observations. Here, we demonstrate improved prediction accuracy and uncertainty quantification compared to unimodal surrogate models for both scalar and time series data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

DPM: A deep learning PDE augmentation method with application to large-eddy simulation

A framework is introduced that leverages known physics to reduce overfitting in machine learning for scientific applications. The partial differential equation (PDE) that expresses the physics is augmented with a neural network that uses available data to learn a description of the corresponding unknown or unrepresented physics. Training within this combined system corrects for missing, unknown, or erroneously represented physics, including discretization errors associated with the PDE's numerical solution. For optimization of the network within the PDE, an adjoint PDE is solved to provide high-dimensional gradients, and a stochastic adjoint method (SAM) further accelerates training. Additionally, the approach is demonstrated for large-eddy simulation (LES) of turbulence. High-fidelity direct numerical simulations (DNS) of decaying isotropic turbulence provide the training data used to learn sub-filter-scale closures for the filtered Navier–Stokes equations. Out-of-sample comparisons show that the deep learning PDE method outperforms widely-used models, even for filter sizes so large that they become qualitatively incorrect. It also significantly outperforms the same neural network when a priori trained based on simple data mismatch, not accounting for the full PDE. Measures of discretization errors, which are well-known to be consequential in LES, point to the importance of the unified training formulation's design, which without modification corrects for them. For comparable accuracy, simulation runtime is significantly reduced. A relaxation of the typical discrete enforcement of the divergence-free constraint in the solver is also successful, instead allowing the DPM to approximately enforce incompressibility physics. Since the training loss function is not restricted to correspond directly to the closure to be learned, training can incorporate diverse data, including experimental data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Biνo phenomenology at the LHC

We observe the LHC constraints on an $R$-symmetric SUSY model, where the neutrino masses are generated through higher dimensional operators involving the pseudo-Dirac bino, named bi$\nu$o. We consider a particle spectrum where the squarks are heavier than the lightest neutralino, which is a pure bi$\nu$o. The bi$\nu$o is produced through squark decays and it subsequently decays to a combination of jets and leptons, with or without missing energy, via its mixing with the Standard Model neutrinos. We recast the most recent LHC searches for jets+missing energy with $\sqrt{s}=13~$TeV and $\mathcal{L}=36~{\rm fb}^{-1}$ of data to determine the constraints on the squark and bi$\nu$o masses in this model. We find that squarks as light as 350 GeV are allowed if the bi$\nu$o is lighter than 150 GeV and squarks heavier than 950 GeV are allowed for any bi$\nu$o mass. We also present forecasts for the LHC with $\sqrt{s}=13$ TeV and $\mathcal{L}=300~{\rm fb}^{-1}$ and show that squarks up to 1150 GeV can be probed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Search for new phenomena in events with a photon and missing transverse momentum in pp collisions at $$ \sqrt{s}=13 $$ TeV with the ATLAS detector

Results of a search for new phenomena in events with an energetic photon and large missing transverse momentum with the ATLAS experiment at the Large Hadron Collider are reported. The data were collected in proton-proton collisions at a centre-of-mass energy of 13 TeV and correspond to an integrated luminosity of 3.2 fb -1 . The observed data are in agreement with the Standard Model expectations. Exclusion limits are presented in models of new phenomena including pair production of dark matter candidates or large extra spatial dimensions. In a simplified model of dark matter and an axial-vector mediator, the search excludes mediator masses below 710 GeV for dark matter candidate masses below 150 GeV. In an effective theory of dark matter production, values of the suppression scale M * up to 570 GeV are excluded and the effect of truncation for various coupling values is reported. Finally, for the ADD large extra spatial dimension model the search places more stringent limits than earlier searches in the same event topology, excluding M D up to about 2.3 (2.8) TeV for two (six) additional spatial dimensions; the limits are reduced by 20-40% depending on the number of additional spatial dimensions when applying a truncation procedure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Quantum confinement in self-assembled two-dimensional nanoporous honeycomb networks at close-packed metal surfaces

Quantum confinement of a two-dimensional electron gas by supramolecular nanoporous networks is investigated using the boundary elements method based on Green’s functions for finite geometries and electron plane wave expansion for periodic systems. The “particle in a box” picture was analyzed for cases with selected symmetries that model previously reported architectures constructed from organic and metal-organic scattering centers confining surface state electrons of Ag(111) and Cu(111). First, by analyzing a series of cases with systematically defined parameters (scattering geometry, potentials, and effective broadening), we demonstrate how the scattering processes affect the properties of the confined electrons. For the features of the local density of states reported by scanning tunneling spectroscopy (STS), we disentangle the contributions of lifetime broadening and splitting of quantum well states due to coupling of neighboring quantum dots. For each system, we analyze the local electron density distribution and relate it to the corresponding band structure as calculated within the plane-wave expansion framework. Then, we address two experimental investigations, where in one case only STS data and in the other case mainly angle-resolved photoemission spectroscopy (ARPES) data were reported. In both cases, the experimental findings can be successfully simulated. Furthermore, the missing information can be complemented because our approach allows to correlate the information obtained by STS with that of ARPES. The combined analysis of several observations suggests that the scattering potentials created by the network originate primarily from the adsorbate-induced changes of the local surface dipole barrier.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

Search for Higgsino pair production in $pp$ collisions at $\sqrt{s}$ = 13 TeV in final states with large missing transverse momentum and two Higgs bosons decaying via $H \to b \bar b$

Results are reported from a search for new physics in 13 TeV proton-proton collisions in the final state with large missing transverse momentum and two Higgs bosons decaying via H→bb¯. The search uses a data sample accumulated by the CMS experiment at the LHC in 2016, corresponding to an integrated luminosity of 35.9 fb-1. The search is motivated by models based on gauge-mediated supersymmetry breaking, which predict the electroweak production of a pair of Higgsinos, each of which can decay via a cascade process to a Higgs boson and an undetected lightest supersymmetric particle. The observed event yields in the signal regions are consistent with the standard model background expectation obtained from control regions in data. Higgsinos in the mass range 230–770 GeV are excluded at 95% confidence level in the context of a simplified model for the production and decay of approximately degenerate Higgsinos.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Using computer-extracted image features for modeling of error-making patterns in detection of mammographic masses among radiology residents

Purpose: Mammography is the most widely accepted and utilized screening modality for early breast cancer detection. Providing high quality mammography education to radiology trainees is essential, since excellent interpretation skills are needed to ensure the highest benefit of screening mammography for patients. The authors have previously proposed a computer-aided education system based on trainee models. Those models relate human-assessed image characteristics to trainee error. In this study, the authors propose to build trainee models that utilize features automatically extracted from images using computer vision algorithms to predict likelihood of missing each mass by the trainee. This computer vision-based approach to trainee modeling will allow for automatically searching large databases of mammograms in order to identify challenging cases for each trainee. Methods: The authors’ algorithm for predicting the likelihood of missing a mass consists of three steps. First, a mammogram is segmented into air, pectoral muscle, fatty tissue, dense tissue, and mass using automated segmentation algorithms. Second, 43 features are extracted using computer vision algorithms for each abnormality identified by experts. Third, error-making models (classifiers) are applied to predict the likelihood of trainees missing the abnormality based on the extracted features. The models are developed individually for each trainee using his/her previous reading data. The authors evaluated the predictive performance of the proposed algorithm using data from a reader study in which 10 subjects (7 residents and 3 novices) and 3 experts read 100 mammographic cases. Receiver operating characteristic (ROC) methodology was applied for the evaluation. Results: The average area under the ROC curve (AUC) of the error-making models for the task of predicting which masses will be detected and which will be missed was 0.607 (95% CI,0.564-0.650). This value was statistically significantly different from 0.5 (p < 0.0001). For the 7 residents only, the AUC performance of the models was 0.590 (95% CI,0.537-0.642) and was also significantly higher than 0.5 (p = 0.0009). Therefore, generally the authors’ models were able to predict which masses were detected and which were missed better than chance. Conclusions: The authors proposed an algorithm that was able to predict which masses will be detected and which will be missed by each individual trainee. This confirms existence of error-making patterns in the detection of masses among radiology trainees. Furthermore, the proposed methodology will allow for the optimized selection of difficult cases for the trainees in an automatic and efficient manner.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Search for dark matter produced in association with bottom or top quarks in $\sqrt{s}=13$ TeV pp collisions with the ATLAS detector

Here, a search for weakly interacting massive dark-matter particles produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and missing transverse momentum are considered. The analysis uses 36.1fb –1 of proton–proton collision data recorded by the ATLAS experiment at √s=13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are interpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour-neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross-section of 300 times the predicted rate for mediators with masses between 10 and 50GeV and assuming a dark-matter mass of 1GeV and unitary coupling. Constraints on colour-charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35GeV, mediator particles with mass below 1.1TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Search for new physics in events with a leptonically decaying Z boson and a large transverse momentum imbalance in proton–proton collisions at $\sqrt{s} $ = 13 $\,\text {TeV}$

A search for new physics in events with a Z boson produced in association with large missing transverse momentum at the LHC is presented. The search is based on the 2016 data sample of proton-proton collisions recorded with the CMS experiment at $\sqrt{s} = 13\,\text {TeV} $ , corresponding to an integrated luminosity of 35.9 $\,\text {fb}^{-1}$ . The results of this search are interpreted in terms of a simplified model of dark matter production via spin-0 or spin-1 mediators, a scenario with a standard-model-like Higgs boson produced in association with the Z boson and decaying invisibly, a model of unparticle production, and a model with large extra spatial dimensions. No significant deviations from the background expectations are found, and limits are set on relevant model parameters, significantly extending the results previously achieved in this channel.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Search for squarks and gluinos in final states with one isolated lepton, jets, and missing transverse momentum at $\sqrt{s}=13$ with the ATLAS detector

The results of a search for gluino and squark pair production with the pairs decaying via the lightest charginos into a final state consisting of two W bosons, the lightest neutralinos ($\tilde{χ}^0_1$), and quarks, are presented: the signal is characterised by the presence of a single charged lepton (e ± or μ ± ) from a W boson decay, jets, and missing transverse momentum. The analysis is performed using 139 fb -1 of proton–proton collision data taken at a centre-of-mass energy √s=13 delivered by the Large Hadron Collider and recorded by the ATLAS experiment. No statistically significant excess of events above the Standard Model expectation is found. Limits are set on the direct production of squarks and gluinos in simplified models. Masses of gluino (squark) up to 2.2 (1.4 ) are excluded at 95% confidence level for a light $\tilde{χ}^0_1$.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Analytical Modeling of Cache Behavior for Affine Programs

Modern optimizing compiler design integrates program transformation strategies aimed at reducing data movement to/from main memory by exploiting the data cache hierarchy. But in reality, the effect of these transformations on the actual cache miss count is ignored in compilers due to the lack of precise compile-time models of misses for hierarchical caches. The current state of practice for cache miss analysis is based on accurate simulation. However, simulation requires time proportional to the dataset/problem size as well as the number of distinct cache configurations of interest to be evaluated. This paper takes a fundamentally different approach, made possible by focusing on polyhedral programs with static control flow: instead of relying on costly simulation, this paper develops the first closed-form solution for exact modeling of misses in a set-associative cache hierarchy. It enabling simulation-less selection of program transformations at compile-time to optimize cache misses. A push-button tool implementing the approach is developed and used for extensive validation of the complete framework.

affine programs, cache modeling, set associativity↗
DOE OSTI2013

Proceedings of RIKEN BNL Research Center Workshop: Jet Quenching at RHIC vs LHC in Light of Recent dAu vs pPb Controls [Slides]

In the last decade of the RHIC physics program, studies of jet quenching has played an important role in the discovery and detailed characterization of the strongly interacting Quark-Gluon Plasma. However, these studies also generated several critical puzzles, such as the azimuthal anisotropy of jet quenching, heavy flavor energy loss and initial state suppression, hinting at missing ingredients in our current understanding of jet quenching. Now only two years into the data taking, LHC has produced new measurements on a variety of existing and new jet quenching observables, over a much broader kinematic range.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Recherche du boson de Higgs dans l'état final dimuonique et étude de l'asymétrie de production de la paire top antitop avec l'expérience DO auprès du Tevatron; Higgs boson search in the dimuonique final state and study of the top pair antitop production asymmetry with the DO experiment at the Tevatron.

Two high energy particle physics analyses are presented in this PhD report using events with two leptons oppositely charged and with missing transverse energy. These events are selected using 9.7 fb-1 of total pp collisions data collected with the DØ detector at the TeVatron at √s=1.96 TeV.The first analysis is the research of the Higgs boson decaying in the H→WW→μνμν channel. No significant excess above the background prediction is observed.Upper limits on Higgs boson production cross-section are computed in the standard model framework but also in the 4th generation of fermions and in the fermiophobic coupling to Higgs boson hypotheses. In order to validate the research methodology, the W boson pair production cross-section is measured.The second analysis is the measurement of the forward-backward asymmetry of the tt pair production. This is the first measurement in the dileptonic channel at DØ experiment. In this context, a new tt pair kinematic reconstruction is used (matrix element method) to give a raw measurement of the forward-backward asymmetry. Thanks to a dedicated calibration method, we give a final measurement of AFB=18.0 ± 6.0 (stat) ± 3.3 (syst).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Investigating Application of LiDAR for Nuclear Power Plants

Many evaluation, assessment, and modeling tasks at nuclear power plants require spatial in-formation; this often requires physical visits to locations within the facility because the 2D or 3D schematics and current models do not contain enough detail or do not capture as-built and real-world conditions. These visits require extensive manual labor for not only the requesting party, but also support groups, such as security. Light Detection and Ranging (LiDAR) mapping is trying to solve that problem by providing very detailed 3D models for low costs. However, the use of these models can be very limited because either component reference information is missing and too costly to add or there is no way to extract specific spatial data needed for other tools. This report outlines two main efforts. First, to reduce the effort of “Tagging” data in large 3D models, a general Application Programming Interface (API) was developed to import a variety of existing plant database information into a 3D-visualization engine. Filters allow the user to have only zone-specific items listed; then, they can simply click and assign the information to a specific spot or component in the 3D model. The second part of the work is the development of an interface for importing pieces from the3D-LiDAR model into other systems needed for modeling and simulation, outlined around fire modeling. This interface allows for the retrieval of item location and boundaries, enabling the auto generation of models for varying tools.

3D Modelling↗
DOE OSTI2023

Measurement of the top quark-antiquark pair charge asymmetry in events with highly boosted top quarks in proton-proton collisions at 13 TeV with the CMS detector

The top quark is the heaviest elementary particle, making it a unique tool to search for new physics. In this talk, I will present a new measurement of the top quark pair charge asymmetry for highly boosted top quarks decaying to a single lepton, missing transverse momentum and jets. The analysis is performed on 13TeV proton-proton collision data recorded by the CMS experiment during Run 2. We have defined a dedicated phase space that selects top quark-antiquark pairs with invariant mass greater than 750GeV in a semileptonic final state where the lepton is not necessarily isolated. This highly boosted sample is enhanced in valence quark production and thus expected to be more sensitive to deviations in the charge asymmetry caused by BSM processes. Dedicated tagging techniques are used to identify the decay products of hadronic top quarks and W bosons. An unfolding procedure is used to correct for detector resolution and acceptance, and inefficiencies in the event reconstruction. The result is presented in the full phase space at parton level and can be used as input to global EFT interpretations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2018

Impacts of Snow and Cloud Covers on Satellite-Derived PM 2.5 Levels

Satellite aerosol optical depth (AOD) has been widely employed to evaluate ground fine particle (PM 2.5 ) levels, whereas snow/cloud covers often lead to a large proportion of non-random missing AOD. As a result, the fully covered and unbiased PM 2.5 estimates will be hard to generate. Among the current approaches to deal with the data gap issue, few have considered the cloud-AOD relationship and none of them have considered the snow-AOD relationship. This study examined the impacts of snow and cloud covers on AOD and PM 2.5 and made full-coverage PM 2.5 predictions with the consideration of these impacts. To estimate the missing AOD, daily gap-filling models with snow/cloud fractions and meteorological covariates were developed using the random forest algorithm. By using these models in New York State, a daily AOD data set with a 1-km resolution was generated with a complete coverage. The“out-of-bag” R 2 of the gap-filling models averaged 0.93 with an interquartile range from 0.90 to 0.95. Subsequently, a random forest-based PM 2.5 prediction model with the gap-filled AOD and covariates was built to predict fully covered PM 2.5 estimates. A ten-fold cross-validation for the prediction model showed a good performance with an R 2 of 0.82. In the gap-filling models, the snow fraction was of higher significance in the snow season compared with the rest of the year. The prediction models fitted with/without the snow fraction also suggested the discernible changes in PM 2.5 patterns, further confirming the significance of this parameter. Compared with the methods without considering snow and cloud covers, our PM 2.5 prediction surfaces showed more spatial details and reflected small-scale terrain-driven PM 2.5 patterns. The proposed methods can be generalized to the areas with extensive snow/cloud covers and large proportions of missing satellite AOD for predicting PM 2.5 levels with high resolutions and complete coverage.

AOD↗