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At least 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Planck 2018 results

We report on the implications for cosmic inflation of the 2018 release of the Planck cosmic microwave background (CMB) anisotropy measurements. The results are fully consistent with those reported using the data from the two previous Planck cosmological releases, but have smaller uncertainties thanks to improvements in the characterization of polarization at low and high multipoles. Planck temperature, polarization, and lensing data determine the spectral index of scalar perturbations to be n s = 0.9649 ± 0.0042 at 68% CL. We find no evidence for a scale dependence of n s , either as a running or as a running of the running. The Universe is found to be consistent with spatial flatness with a precision of 0.4% at 95% CL by combining Planck with a compilation of baryon acoustic oscillation data. The Planck 95% CL upper limit on the tensor-to-scalar ratio, r0.002 < 0.10, is further tightened by combining with the BICEP2/Keck Array BK15 data to obtain r 0.002 < 0.056. In the framework of standard single-field inflationary models with Einstein gravity, these results imply that: (a) the predictions of slow-roll models with a concave potential, V"(Φ) < 0, are increasingly favoured by the data; and (b) based on two different methods for reconstructing the inflaton potential, we find no evidence for dynamics beyond slow roll. Three different methods for the non-parametric reconstruction of the primordial power spectrum consistently confirm a pure power law in the range of comoving scales 0.005 Mpc -1 ≲ k ≲ 0.2 Mpc -1 . A complementary analysis also finds no evidence for theoretically motivated parameterized features in the Planck power spectra. For the case of oscillatory features that are logarithmic or linear in k, this result is further strengthened by a new combined analysis including the Planck bispectrum data. The new Planck polarization data provide a stringent test of the adiabaticity of the initial conditions for the cosmological fluctuations. In correlated, mixed adiabatic and isocurvature models, the non-adiabatic contribution to the observed CMB temperature variance is constrained to 1.3%, 1.7%, and 1.7% at 95% CL for cold dark matter, neutrino density, and neutrino velocity, respectively. Planck power spectra plus lensing set constraints on the amplitude of compensated cold dark matter-baryon isocurvature perturbations that are consistent with current complementary measurements. The polarization data also provide improved constraints on inflationary models that predict a small statistically anisotropic quadupolar modulation of the primordial fluctuations. However, the polarization data do not support physical models for a scale-dependent dipolar modulation. All these findings support the key predictions of the standard single-field inflationary models, which will be further tested by future cosmological observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Real-Time event reconstruction for Nuclear Physics Experiments using Artificial Intelligence

Charged track reconstruction is a critical task in nuclear physics experiments, enabling the identification and analysis of particles produced in high-energy collisions. Machine learning (ML) has emerged as a powerful tool for this purpose, addressing the challenges posed by complex detector geometries, high event multiplicities, and noisy data. Traditional methods rely on pattern recognition algorithms like the Kalman filter, but ML techniques, such as neural networks, graph neural networks (GNNs), and recurrent neural networks (RNNs), offer improved accuracy and scalability. By learning from simulated and real detector data, ML models can identify and classify tracks, predict trajectories, and handle ambiguities caused by overlapping or missing hits. Moreover, ML-based approaches can process data in near-real-time, enhancing the efficiency of experiments at large-scale facilities like the Large Hadron Collider (LHC) and Jefferson Lab (JLAB). As detector technologies and computational resources evolve, ML-driven charged track reconstruction continues to push the boundaries of precision and discovery in nuclear physics. In these proceedings, we highlight advancements in charged track identification leveraging Artificial Intelligence within the CLAS12 detector, achieving a notable enhancement in experimental statistics compared to traditional methods. Additionally, we showcase real-time event reconstruction capabilities, including the inference of charged particle properties, such as momentum, direction, and species identification, at speeds matching data acquisition rates. These innovations enable the extraction of physics observables directly from the experiment in real-time.

Gavalian, Gagik (ORCID:0000000267385457)↗
DOE OSTI2014

Collisionless damping of geodesic acoustic mode in plasma with nonextensive distribution

Geodesic acoustic mode (GAM) in collisionless toroidal plasmas with a constant electrostatic potential around a magnetic surface is investigated based on the linear gyrokinetic theory in context of nonextensive statistics mechanics. The damping rate of GAM is shown to be dependent on the nonextensive parameters of ions, and in the extensive limit, the result in Maxwellian distribution plasma is recovered. The damping rate is found to be enhanced as the nonextensive parameter of ion decreases.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Spontaneous symmetry breaking in quasi one dimension

Electronic charge and spin separation leading to charge density wave and spin density wave is well established in one dimension in the presence and absence of Coulomb interaction. We start from quasi one dimension and show the possibility of such a transition in quasi one dimension as well as in two dimensions by going to a regime where it can be shown for electrons that just interact via Fermi statistics. Such density waves arise due to internal symmetry breaking in a many fermion quantum system. We can extend this result to very wide rings with infinitely many electrons including Coulomb interaction.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Sensitivity analysis of static resistance of slender beam under bending

The paper deals with statical and sensitivity analyses of resistance of simply supported I-beams under bending. The resistance was solved by geometrically nonlinear finite element method in the programme Ansys. The beams are modelled with initial geometrical imperfections following the first eigenmode of buckling. Imperfections were, together with geometrical characteristics of cross section, and material characteristics of steel, considered as random quantities. The method Latin Hypercube Sampling was applied to evaluate statistical and sensitivity resistance analyses.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

STATISTICAL COMPARISON BETWEEN PORES AND SUNSPOTS BY USING SDO/HMI

We carried out an extensive statistical study of the properties of pores and sunspots, and investigated the relationship among their physical parameters such as size, intensity, magnetic field, and the line-of-sight (LOS) velocity in the umbrae. For this, we classified 9881 samples into three groups of pores, transitional sunspots, and mature sunspots. As a result, (1) we find that the total magnetic flux inside the umbra of pores, transitional sunspots, and mature sunspots increases proportionally to the powers of the area and the power indices in the three groups significantly differ from each other. (2) The umbral area distribution of each group shows a Gaussian distribution and they are clearly separated, displaying three distinct peak values. All of the quantities significantly overlap among the three groups. (3) The umbral intensity shows a rapid decrease with increasing area, and their magnetic field strength shows a rapid increase with decreasing intensity. (4) The LOS velocity in pores is predominantly redshifted and its magnitude decreases with increasing magnetic field strength. The decreasing trend becomes nearly constant with marginal blueshift in the case of mature sunspots. The dispersion of LOS velocities in mature sunspots is significantly suppressed compared to pores. From our results, we conclude that the three groups have different characteristics in their area, intensity, magnetic field, and LOS velocity as well in their relationships.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Omega Electroproduction

The differential cross section for p(e, e'ω)p has been studied at Q{sup 2} ~ 5.5 (GeV/c)2. Here Q{sup 2} represents the four momentum squared of the virtual photon in the excitation of baryonic resonances by an electron projectile. In order to extract the ω-meson differential cross section from the JLAB data, the data was compared to a full Monte Carlo simulation of the detector based on events generated for omega production in a way that the production cross section was varied to achieve a match to the data. The bin selected for this procedure takes into account the measure of robustness of the stripping of the ω peak from the multi-pion background as well as the statistics in the measured data and the Monte Carlo simulation of the signal and background physics. An error estimation technique for the cross section was based on determining the dependence of the extracted cross section parameters on the experimental set-up (including parameters for the spectrometer, target beam geometeries and performance). We compare our results with a Regge-based model for hadronic content in the t-channel exchange of a photon in Q{sup 2} region of overlap. There is an extension of this data into a completely new region, which is the highest yet measured.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Measuring the scale dependence of intrinsic alignments using multiple shear estimates

We present a new method for measuring the scale dependence of the intrinsic alignment (IA) contamination to the galaxy–galaxy lensing signal, which takes advantage of multiple shear estimation methods applied to the same source galaxy sample. By exploiting the resulting correlation of both shape noise and cosmic variance, our method can provide an increase in the signal-to-noise of the measured IA signal as compared to methods which rely on the difference of the lensing signal from multiple photometric redshift bins. For a galaxy–galaxy lensing measurement which uses LSST sources and DESI lenses, the signal-to-noise on the IA signal from our method is predicted to improve by a factor of ~2 relative to the method of Blazek et al. (2012), for pairs of shear estimates which yield substantially different measured IA amplitudes and highly correlated shape noise terms. We show that statistical error necessarily dominates the measurement of IAs using our method. We also consider a physically motivated extension of the Blazek et al. (2012) method which assumes that all nearby galaxy pairs, rather than only excess pairs, are subject to IA. In this case, the signal-to-noise of the method of Blazek et al. (2012) is improved.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Landau-Zener extension of the Tavis-Cummings model: Structure of the solution

We explore the recently discovered solution of the driven Tavis-Cummings model (DTCM). It describes interaction of an arbitrary number of two-level systems with a bosonic mode that has linearly time-dependent frequency. We derive compact and tractable expressions for transition probabilities in terms of the well-known special functions. In this form, our formulas are suitable for fast numerical calculations and analytical approximations. As an application, we obtain the semiclassical limit of the exact solution and compare it to prior approximations. Furthermore, we also reveal connection between DTCM and q -deformed binomial statistics.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Quantum Statistics of Vortices from a Dual Theory of the X Y Ferromagnet

In this work, we extend the well-known mapping between the easy-plane ferromagnet and electrostatics in d = 2 spatial dimensions to dynamical and quantum phenomena in a d = 2+1 spacetime. Ferromagnetic vortices behave like quantum particles with an electric charge equal to the vortex number and a magnetic flux equal to the transverse spin of the vortex core. Vortices with half-integer core spin exhibit fermionic statistics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

SU-E-T-398: Evaluation of Radiobiological Parameters Using Serial Tumor Imaging During Radiotherapy as An Inverse Ill-Posed Problem

Purpose: Combination of serial tumor imaging with radiobiological modeling can provide more accurate information on the nature of treatment response and what underlies resistance. The purpose of this article is to improve the algorithms related to imaging-based radiobilogical modeling of tumor response. Methods: Serial imaging of tumor response to radiation therapy represents a sum of tumor cell sensitivity, tumor growth rates, and the rate of cell loss which are not separated explicitly. Accurate treatment response assessment would require separation of these radiobiological determinants of treatment response because they define tumor control probability. We show that the problem of reconstruction of radiobiological parameters from serial imaging data can be considered as inverse ill-posed problem described by the Fredholm integral equation of the first kind because it is governed by a sum of several exponential processes. Therefore, the parameter reconstruction can be solved using regularization methods. Results: To study the reconstruction problem, we used a set of serial CT imaging data for the head and neck cancer and a two-level cell population model of tumor response which separates the entire tumor cell population in two subpopulations of viable and lethally damage cells. The reconstruction was done using a least squared objective function and a simulated annealing algorithm. Using in vitro data for radiobiological parameters as reference data, we shown that the reconstructed values of cell surviving fractions and potential doubling time exhibit non-physical fluctuations if no stabilization algorithms are applied. The variational regularization allowed us to obtain statistical distribution for cell surviving fractions and cell number doubling times comparable to in vitro data. Conclusion: Our results indicate that using variational regularization can increase the number of free parameters in the model and open the way to development of more advanced algorithms which take into account tumor heterogeneity, for example, related to hypoxia.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Measurement of the W-boson mass in pp collisions at $\sqrt{s}=7 TeV$ with the ATLAS detector

A measurement of the mass of the W boson is presented based on proton–proton collision data recorded in 2011 at a centre-of-mass energy of 7 TeV with the ATLAS detector at the LHC, and corresponding to 4.6 fb -1 of integrated luminosity. The selected data sample consists of 7.8 × 10 6 candidates in the W→μν channel and 5.9×10 6 candidates in the W→eν channel. The W-boson mass is obtained from template fits to the reconstructed distributions of the charged lepton transverse momentum and of the W boson transverse mass in the electron and muon decay channels, yielding m W =80370 ± 7 (stat.) ± 11 (exp.syst.) ±14 (mod.syst.) MeV = 80370 ± 19 MeV where the first uncertainty is statistical, the second corresponds to the experimental systematic uncertainty, and the third to the physics-modelling systematic uncertainty. Finally, a measurement of the mass difference between the W + and W - bosons yields m W + -m W = -29 ± 28 MeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Mesoscale Science Data Analytics

This is software that will be used to do data analytics in experimental workflows for x-ray mesoscale science. This tool set will provide a mechanism for supporting experiments in many ways, from collecting calibration information and raw data, to managing and viewing data to extracting crystallographic and physical parameters. It will eventually include development of a fully automated workflow that will include statistical information and prediction capabilities to support the scientists in decision-making and replanning their experiments when necessary.

Sweeney, Christine↗
DOE OSTI2020

Uncertainty Quantification in Scientific ML

The intricate interactions between data sampling, model selection and the inherent randomness in complex systems strongly emphasize the need for a rigorous characterization of ML algorithms. In conventional statistics, uncertainty quantification (UQ) provides this characterization by measuring how accurately a model reflects the physical reality and by studying the impact of different error sources on the prediction.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1978

Climate diagnostics

Diagnoses of climate fluctuations is examined emphasizing the assemblage of a host of observations, to develop a clearer physical picture of the nature and causal interrelationships of the climate events. Development of better statistical methods for making predictions of climate fluctuations and improving numerical climate prediction models is considered along with obtaining data for areas for which meager records exist such as the tropics and the southern hemisphere. The major circulation systems in the tropics, energy transports by the oceans and atmosphere, and the reflected or absorbed solar radiation values from the earth's surface are among the phenomena to be studied.

Source record↗
NASA NTRS1984

Forecasts of the 500 mb height using a dynamically oriented statistical model

The forecast skill of a simple dynamically inspired statistical model of the Northern Hemisphere 500 mb height field is evaluated in spectral and physical space for a variety of forecast lead times (1-32 days) and predictand averaging times (1-32 days). The model includes viscous damping, wave propagation, climatology and implicit stochastic forcing. The largest model skill was found for forecasts of the zonal flow and the largest waves. In general, the largest forecast skills were also associated with the largest forecast error, there being a slight geographic phase shift of the skill with respect to the error. Model skills for climate (time-averaged) forecasts are greater when using instantaneous rather than time averages to forecast time averages. Analysis of model errors suggests areas for improvement in representing forcing terms and model physics. However, the model error fields are largely 'white noise' which suggests that global forecast skills substantially larger than those obtained here are unlikely to be achieved by more sophisticated models.

Roads, J. O.↗
NASA NTRS1991

Dynamo-based scheme for forecasting the magnitude of solar activity cycles

This paper presents a general framework for forecasting the smoothed maximum level of solar activity in a given cycle, based on a simple understanding of the solar dynamo. This type of forecasting requires knowledge of the sun's polar magnetic field strength at the preceding activity minimum. Because direct measurements of this quantity are difficult to obtain, the quality of a number of proxy indicators already used by other authors is evaluated, which are physically related to the sun's polar field. These indicators are subjected to a rigorous statistical analysis, and the analysis technique for each indicator is specified in detail in order to simplify and systematize reanalysis for future use. It is found that several of these proxies are in fact poorly correlated or uncorrelated with solar activity, and thus are of little value for predicting activity maxima. Also presented is a scheme in which the predictions of the individual proxies are combined via an appropriately weighted mean to produce a compound prediction. The scheme is then applied to the current cycle 22, and a maximum smoothed international sunspot number of 171 + or - 26 is estimated.

Layden, A. C.↗