Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Differentiability”

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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Measurement of differential cross-sections of a single top quark produced in association with a W boson at $\sqrt{s}={13}{\text {TeV}}$ with ATLAS

The differential cross-section for the production of a W boson in association with a top quark is measured for several particle-level observables. The measurements are performed using 36.1fb -1 of pp collision data collected with the ATLAS detector at the LHC in 2015 and 2016. Differential cross-sections are then measured in a fiducial phase space defined by the presence of two charged leptons and exactly one jet matched to a b-hadron, and are normalised with the fiducial cross-section. Results are found to be in good agreement with predictions from several Monte Carlo event generators.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Measurements of $\pi ^\pm $, $K^\pm $ and proton double differential yields from the surface of the T2K replica target for incoming 31 GeV/c protons with the NA61/SHINE spectrometer at the CERN SPS: NA61/SHINE Collaboration

Measurements of the $\pi^{\pm}$, $K^{\pm}$, and proton double differential yields emitted from the surface of the 90-cm-long carbon target (T2K replica) were performed for the incoming 31 GeV/c protons with the NA61/SHINE spectrometer at the CERN SPS using data collected during 2010 run. The double differential $\pi^{\pm}$ yields were measured with increased precision compared to the previously published NA61/SHINE results, while the $K^{\pm}$ and proton yields were obtained for the first time. A strategy for dealing with the dependence of the results on the incoming proton beam profile is proposed. Furthermore, the purpose of these measurements is to reduce significantly the (anti)neutrino flux uncertainty in the T2K long-baseline neutrino experiment by constraining the production of (anti)neutrino ancestors coming from the T2K target.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Measurements of the Higgs boson inclusive and differential fiducial cross sections in the 4$\ell$ decay channel at $\sqrt{s}$ = 13 TeV

Inclusive and differential fiducial cross sections of the Higgs boson are measured in the H → Z Z * → 4 ℓ ( ℓ = e , μ ) decay channel. The results are based on proton-proton collision data produced at the Large Hadron Collider at a centre-of-mass energy of 13 TeV and recorded by the ATLAS detector from 2015 to 2018, equivalent to an integrated luminosity of 139 $\hbox {fb}^{-1}$ fb - 1 . The inclusive fiducial cross section for the H → Z Z * → 4 ℓ process is measured to be σ fid = 3.28 ± 0.32 fb, in agreement with the Standard Model prediction of σ fid , SM = 3.41 ± 0.18 fb. Differential fiducial cross sections are measured for a variety of observables which are sensitive to the production and decay of the Higgs boson. All measurements are in agreement with the Standard Model predictions. The results are used to constrain anomalous Higgs boson interactions with Standard Model particles.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Punzi-loss: a non-differentiable metric approximation for sensitivity optimisation in the search for new particles

We present the novel implementation of a non-differentiable metric approximation and a corresponding loss-scheduling aimed at the search for new particles of unknown mass in high energy physics experiments. We call the loss-scheduling, based on the minimisation of a figure-of-merit related function typical of particle physics, a Punzi-loss function, and the neural network that utilises this loss function a Punzi-net. We show that the Punzi-net outperforms standard multivariate analysis techniques and generalises well to mass hypotheses for which it was not trained. This is achieved by training a single classifier that provides a coherent and optimal classification of all signal hypotheses over the whole search space. Our result constitutes a complementary approach to fully differentiable analyses in particle physics. We implemented this work using PyTorch and provide users full access to a public repository containing all the codes and a training example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

A precise measurement of the Z -boson double-differential transverse momentum and rapidity distributions in the full phase space of the decay leptons with the ATLAS experiment at $\sqrt{s}=8$ TeV

This paper presents for the first time a precise measurement of the production properties of the Z boson in the full phase space of the decay leptons. This is in contrast to the many previous precise unfolded measurements per formed in the fiducial phase space of the decay leptons. The measurement is obtained from proton–proton collision data collected by the ATLAS experiment in 2012 at $\sqrt{s}$ = 8 TeV at the LHC and corresponding to an integrated luminosity of 20.2 fb -1 . The results, based on a total of 15.3 million Z boson decays to electron and muon pairs, extend and improve a previous measurement of the full set of angular coefficients describing Z-boson decay. The double-differential cross section distributions in Z-boson transverse momentum pT and rapidity y are measured in the pole region, defined as 80 < m ℓℓ < 100 GeV, over the range |y| < 3.6. The total uncertainty of the normalised cross-section measurements in the peak region of the pT distribution is dominated by statistical uncertainties over the full range and increases as a function of rapidity from 0.5–1.0% for |y| < 2.0 to 2 - 7% at higher rapidities. The results for the rapidity-dependent transverse momentum distributions are compared to state of-the-art QCD predictions, which combine in the best cases approximate N 4 LL resummation with N 3 LO fixed-order per turbative calculations. The differential rapidity distributions integrated over pT are even more precise, with accuracies from 0.2–0.3% for |y| < 2.0 to 0.4–0.9% at higher rapidities, and are compared to fixed-order QCD predictions using the most recent parton distribution functions. The agreement between data and predictions is quite good in most cases.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Precise measurement of the tt¯ production cross-section and lepton differential distributions in eμ dilepton events from s=13TeVpp collisions with the ATLAS detector

The inclusive top quark pair (tt¯$$t\bar{t}$$) cross-section σtt¯$$\sigma _{t\bar{t}}$$ has been measured in proton–proton collisions at s=13TeV$$\sqrt{s}=13\,\text {TeV}$$, using 140fb-1$$140\,{\text {fb}^{-1}} $$ of data collected by the ATLAS experiment at the Large Hadron Collider. Using events with an opposite-charge eμ$$e\mu $$ pair and b-tagged jets, the cross-section is measured to be: σtt¯=829.3±1.3(stat)±8.0(syst)±7.3(lumi)±1.9(beam)pb,$$\begin{aligned} \sigma _{t\bar{t}} & = 829.3\pm 1.3\,\mathrm {(stat)}\ \pm 8.0\,\mathrm {(syst)}\ \pm 7.3\,\mathrm {(lumi)}\ \\ & \quad \pm 1.9\,\mathrm {(beam)}\,\textrm{pb}, \end{aligned}$$where the uncertainties reflect the limited size of the data sample, experimental and theoretical systematic effects, the integrated luminosity, and the proton beam energy, giving a total uncertainty of 1.3%. The result is used to determine the top quark pole mass via the dependence of the predicted cross-section on mtpole$${m_{t}^\textrm{pole}}$$, giving mtpole=172.8-1.7+1.5$${m_{t}^\textrm{pole}}=172.8^{+1.5}_{-1.7}$$ GeV$$\text {GeV}$$. The same event sample is used to measure absolute and normalised differential cross-sections for the tt¯→eμνν¯bb¯$$t\bar{t} \rightarrow e\mu u \bar{ u }b\bar{b} $$ process as a function of single-lepton and dilepton kinematic variables. Complementary measurements of eμbb¯$$e\mu b\bar{b} $$ production, treating both tt¯$$t\bar{t}$$ and Wt events as signal, are also provided. Both sets of differential cross-sections are compared to the predictions of various Monte Carlo event generators, demonstrating that the state-of-the-art generators Powheg MiNNLO and Powhegbb4l describe the data better than Powheghvq.

Aad, G↗
DOE OSTI2014

Measurement Of Differential Cross Sections Of p(e,e'{pi}{sup +})n For High-Lying Resonances At Q{sup 2} < 5 GeV{sup 2}

The exclusive electro-production process ep -> e'n{pi}{sup +} was measured in the range of the invariant mass for n{pi}{sup +} system 1.6 GeV <= W <= 2.0 GeV, and the photon virtuality 1.8 GeV{sup 2} <= Q{sup 2} <= 4.0 GeV{sup 2} using CLAS. For the first time, these kinematics are probed in exclusive {pi}{sup +} production from the protons with nearly full coverage in the azimuthal and polar angles of the n{pi}{sup +} center-of-mass system. In this experiment, approximately 39,000 differential cross-section data points were measured. In this proceeding, preliminary results of our latest analysis work are presented on differential cross sections and structure functions as well as Legendre Moments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Differential Network Analyses of Alzheimer’s Disease Identify Early Events in Alzheimer’s Disease Pathology

In late-onset Alzheimer’s disease (AD), multiple brain regions are not affected simultaneously. Comparing the gene expression of the affected regions to identify the differences in the biological processes perturbed can lead to greater insight into AD pathogenesis and early characteristics. We identified differentially expressed (DE) genes from single cell microarray data of four AD affected brain regions: entorhinal cortex (EC), hippocampus (HIP), posterior cingulate cortex (PCC), and middle temporal gyrus (MTG). We organized the DE genes in the four brain regions into region-specific gene coexpression networks. Differential neighborhood analyses in the coexpression networks were performed to identify genes with low topological overlap (TO) of their direct neighbors. The low TO genes were used to characterize the biological differences between two regions. Our analyses show that increased oxidative stress, along with alterations in lipid metabolism in neurons, may be some of the very early events occurring in AD pathology. Cellular defense mechanisms try to intervene but fail, finally resulting in AD pathology as the disease progresses. Furthermore, disease annotation of the low TO genes in two independent protein interaction networks has resulted in association between cancer, diabetes, renal diseases, and cardiovascular diseases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Constitutive Models via Automatic Differentiation v.1.0.0

SAND2024-00905O Constitutive Models via Automatic Differentiation (CMAD) provides a software framework for solving constitutive or material model calibration problems. It relies on JAX's automatic differentiation capabilities to compute the derivatives needed for both forward and adjoint sensitivity analyses. The software can be used to implement constitutive models and calibrate the parameters from experimental data. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Seidl, Daniel↗
DOE OSTI2024

DESS (Differential Equation System Solver) [SWR-24-48]

The Differential Equation System Solver (DESS) is a Rust crate implementing fixed-step and adaptive-step solvers and designed especially for modeling physical systems. Seven explicit ordinary differential equation (ODE) solver methods have been added so far: Euler’s, Heun’s, Midpoint, Ralston’s, Classic Runge-Kutta, Bogacki-Shampine, and Cash-Karp. These comprise five fixed-step methods and two adaptive-step methods. Few solver packages are implemented in the Rust ecosystem and none are intended specifically for physical system modeling, so the goal of DESS is to create a Rust ODE solver crate designed to easily specify and model physical systems with modular, configurable solver options. In addition to allowing users to directly input equations to solve, DESS allows users to optionally specify and define relationships between nodes in their system, which the package then translates into a system of equations via the Rust macro system, leading to simpler and more intuitive code.

Steuteville, Robin↗
DOE OSTI2022

Differentially Private DBSCAN

SAND2022-15185 O Differentially Private DBSCAN is a differential private clustering algorithm used for running experiments and conducting data analysis. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Smith, MichaelReed↗
DOE OSTI2021

GNN Parameterized Differential Operators v.0.9

GNN Parametrized Differential Operators is an example code and layer implementation for using the parameterized differential operator used in conference submissions. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-2984 O

Potter, KevinMatthew↗
DOE OSTI2025

A multi-language auto differentiation package (mAD) v1.0

This is a multi-language auto differentiation package. It includes multiple language versions of the package. It can be included/used as a module/class in users' application program to enable differentiability of the program. It is simple, transparent, extensible, efficient compared with the other AD package such as Enzyme or Pytorch.

Qiang, Ji [Lawrence Berkeley National Laboratory (↗
DOE OSTI2016

On polarimetric radar signatures of deep convection for model evaluation: columns of specific differential phase observed during MC3E

The representation of deep convection in general circulation models is in part informed by cloud-resolving models (CRMs) that function at higher spatial and temporal resolution; however, recent studies have shown that CRMs often fail at capturing the details of deep convection updrafts. With the goal of providing constraint on CRM simulation of deep convection updrafts, ground-based remote sensing observations are analyzed and statistically correlated for four deep convection events observed during the Midlatitude Continental Convective Clouds Experiment (MC3E). Since positive values of specific differential phase observed above the melting level are associated with deep convection updraft cells, so-called columns are analyzed using two scanning polarimetric radars in Oklahoma: the National Weather Service Vance WSR-88D (KVNX) and the Department of Energy C-band Scanning Atmospheric Radiation Measurement (ARM) Precipitation Radar (C-SAPR). KVNX and C-SAPR volumes and columns are then statistically correlated with vertical winds retrieved via multi-Doppler wind analysis, lightning flash activity derived from the Oklahoma Lightning Mapping Array, and KVNX differential reflectivity . Results indicate strong correlations of volume above the melting level with updraft mass flux, lightning flash activity, and intense rainfall. Analysis of columns reveals signatures of changing updraft properties from one storm event to another as well as during event evolution. Comparison of to shows commonalities in information content of each, as well as potential problems with associated with observational artifacts.

Atm↗
DOE OSTI2013

Comparative genomics in acid mine drainage biofilm communities reveals metabolic and structural differentiation of co-occurring archaea

Background: Metal sulfide mineral dissolution during bioleaching and acid mine drainage (AMD) formation creates an environment that is inhospitable to most life. Despite dominance by a small number of bacteria, AMD microbial biofilm communities contain a notable variety of coexisting and closely related Euryarchaea, most of which have defied cultivation efforts. For this reason, we used metagenomics to analyze variation in gene content that may contribute to niche differentiation among co-occurring AMD archaea. Our analyses targeted members of the Thermoplasmatales and related archaea. These results greatly expand genomic information available for this archaeal order. Results: We reconstructed near-complete genomes for uncultivated, relatively low abundance organisms A-, E-, and Gplasma, members of Thermoplasmatales order, and for a novel organism, Iplasma. Genomic analyses of these organisms, as well as Ferroplasma type I and II, reveal that all are facultative aerobic heterotrophs with the ability to use many of the same carbon substrates, including methanol. Most of the genomes share genes for toxic metal resistance and surface-layer production. Only Aplasma and Eplasma have a full suite of flagellar genes whereas all but the Ferroplasma spp. have genes for pili production. Cryogenic-electron microscopy (cryo-EM) and tomography (cryo-ET) strengthen these metagenomics-based ultrastructural predictions. Notably, only Aplasma, Gplasma and the Ferroplasma spp. have predicted iron oxidation genes and Eplasma and Iplasma lack most genes for cobalamin, valine, (iso)leucine and histidine synthesis. Conclusion: The Thermoplasmatales AMD archaea share a large number of metabolic capabilities. All of the uncultivated organisms studied here (A-, E-, G-, and Iplasma) are metabolically very similar to characterized Ferroplasma spp., differentiating themselves mainly in their genetic capabilities for biosynthesis, motility, and possibly iron oxidation. These results indicate that subtle, but important genomic differences, coupled with unknown differences in gene expression, distinguish these organisms enough to allow for co-existence. Overall this study reveals shared features of organisms from the Thermoplasmatales lineage and provides new insights into the functioning of AMD communities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Differential expression of small RNAs from Burkholderia thailandensis in response to varying environmental and stress conditions

Background: Bacterial small RNAs (sRNAs) regulate gene expression by base-pairing with downstream target mRNAs to attenuate translation of mRNA into protein at the post-transcriptional level. In response to specific environmental changes, sRNAs can modulate the expression levels of target genes, thus enabling adaptation of cellular physiology. Results: We profiled sRNA expression in the Gram-negative bacteria Burkholderia thailandensis cultured under 54 distinct growth conditions using a Burkholderia-specific microarray that contains probe sets to all intergenic regions greater than 90 bases. We identified 38 novel sRNAs and performed experimental validation on five sRNAs that play a role in adaptation of Burkholderia to cell stressors. In particular, the trans-encoded BTH_s1 and s39 exhibited differential expression profiles dependent on growth phase and cell stimuli, such as antibiotics and serum. Furthermore, knockdown of the highly-expressed BTH_s39 by antisense transcripts reduced B. thailandensis cell growth and attenuated host immune response upon infection, indicating that BTH_s39 functions in bacterial metabolism and adaptation to the host. In addition, expression of cis-encoded BTH_s13 and s19 found in the 5' untranslated regions of their cognate genes correlated with tight regulation of gene transcript levels. This sRNA-mediated downregulation of gene expression may be a conserved mechanism of post-transcriptional gene dosage control. Conclusions: These studies provide a broad analysis of differential Burkholderia sRNA expression profiles and illustrate the complexity of bacterial gene regulation in response to different environmental stress conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Pseudo-differential representation of the metaplectic transform and its application to fast algorithms

The metaplectic transform (MT), also known as the linear canonical transform, is a unitary integral mapping that is widely used in signal processing and can be viewed as a generalization of the Fourier transform. For a given function $ψ$ on an $N$-dimensional continuous space q , the MT of $ψ$ is parameterized by a rotation (or more generally, a linear symplectic transformation) of the 2$N$-dimensional phase space ( q,p ), where p is the wavevector space dual to q . In this study, we derive a pseudo-differential form of the MT. For small-angle rotations, or near-identity transformations of the phase space, it readily yields asymptotic differential representations of the MT, which are easy to compute numerically. Rotations by larger angles are implemented as successive applications of $K \gg 1$ small-angle MTs. The algorithm complexity scales as $O(KN^3N_p)$ where $N_p$ is the number of grid points. Here, we present a numerical implementation of this algorithm and discuss how to mitigate the associated numerical instabilities.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Development of time-domain differential Raman for transient thermal probing of materials

A novel transient thermal characterization technology is developed based on the principles of transient optical heating and Raman probing: time-domain differential Raman. It employs a square-wave modulated laser of varying duty cycle to realize controlled heating and transient thermal probing. Very well defined extension of the heating time in each measurement changes the temperature evolution profile and the probed temperature field at μs resolution. Using this new technique, the transient thermal response of a tipless Si cantilever is investigated along the length direction. A physical model is developed to reconstruct the Raman spectrum considering the temperature evolution, while taking into account the temperature dependence of the Raman emission. By fitting the variation of the normalized Raman peak intensity, wavenumber, and peak area against the heating time, the thermal diffusivity is determined as 9.17 × 10⁻⁵, 8.14 × 10⁻⁵, and 9.51 × 10⁻⁵ m²/s. These results agree well with the reference value of 8.66 × 10⁻⁵ m²/s considering the 10% fitting uncertainty. The time-domain differential Raman provides a novel way to introduce transient thermal excitation of materials, probe the thermal response, and measure the thermal diffusivity, all with high accuracy.

36 MATERIALS SCIENCE↗