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At least 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Statistical Uncertainty in Paleoclimate Proxy Reconstructions

A quantitative analysis of any environment older than the instrumental record relies on proxies. Uncertainties associated with proxy reconstructions are often underestimated, which can lead to artificial conflict between different proxies, and between data and models. In this paper, using ordinary least squares linear regression as a common example, we describe a simple, robust and generalizable method for quantifying uncertainty in proxy reconstructions. We highlight the primary controls on the magnitude of uncertainty, and compare this simple estimate to equivalent estimates from Bayesian, nonparametric and fiducial statistical frameworks. We discuss when it may be possible to reduce uncertainties, and conclude that the unexplained variance in the calibration must always feature in the uncertainty in the reconstruction. This directs future research toward explaining as much of the variance in the calibration data as possible. We also advocate for a “data-forward” approach, that clearly decouples the presentation of proxy data from plausible environmental inferences.

58 GEOSCIENCES↗
DOE OSTI2021

Origin of Electron Boomerang Stripes: Statistical Study

In the outer radiation belt, localized ultralow frequency (ULF) waves can interact with energetic electrons by drift resonance, leading to quasiperiodic oscillations. The oscillations in the pitch angle spectrum can be characterized by either boomerang-shaped or straight stripes. Previous studies have shown that boomerang-shaped stripes evolve from straight ones when electrons drift away from the localized wave interaction region. Based on the time-of-flight technique on the pitch angle-dependent drift velocity, the origin can be remotely identified from the pitch angle dispersion. Here, we report 27 straight stripe events and 86 boomerang-shaped events observed by Van Allen Probes from January 1, 2013, to December 31, 2017. Statistical study shows a good coincidence between the locations of straight ones and traceback regions from boomerang-shaped ones. These locations, mainly located in noon-to-dusk region, coincide well with the plasmaspheric plumes. Thus, localized ULF waves trapped in the plume may result in the preference of localized ULF wave-electron interactions at noon-to-dusk region.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Revealing the Statistics of Extreme Events Hidden in Short Weather Forecast Data

Extreme weather events have significant consequences, dominating the impact of climate on society. While high-resolution weather models can forecast many types of extreme events on synoptic timescales, long-term climatological risk assessment is an altogether different problem. A once-in-a-century event takes, on average, 100 years of simulation time to appear just once, far beyond the typical integration length of a weather forecast model. Therefore, this task is left to cheaper, but less accurate, low-resolution or statistical models. But there is untapped potential in weather model output: despite being short in duration, weather forecast ensembles are produced multiple times a week. Integrations are launched with independent perturbations, causing them to spread apart over time and broadly sample phase space. Collectively, these integrations add up to thousands of years of data. We establish methods to extract climatological information from these short weather simulations. Using ensemble hindcasts by the European Center for Medium-range Weather Forecasting archived in the subseasonal-to-seasonal (S2S) database, we characterize sudden stratospheric warming (SSW) events with multi-centennial return times. Consistent results are found between alternative methods, including basic counting strategies and Markov state modeling. By carefully combining trajectories together, we obtain estimates of SSW frequencies and their seasonal distributions that are consistent with reanalysis-derived estimates for moderately rare events, but with much tighter uncertainty bounds, and which can be extended to events of unprecedented severity that have not yet been observed historically. These methods hold potential for assessing extreme events throughout the climate system, beyond this example of stratospheric extremes.

58 GEOSCIENCES↗
DOE OSTI2025

Statistical Survey of Magnetic Flux Integral Quantities in Saturn's Magnetosphere

Magnetic flux integral quantities (e.g., flux tube entropy, flux tube content) are conserved quantities under the frozen-in assumption. The change of these quantities often indicates the violation of the frozen-in condition (e.g., interchange instability). In this study, we combine the Cassini CAPS and CHEMS moments data with a steady-state magnetic field model (i.e., the Caudal model) to estimate the flux tube mass and flux tube entropy in Saturn's magnetosphere. Our statistical survey found that the flux tube mass rapidly decreases with radial distance away from Saturn in the inner magnetosphere and roughly levels out in the middle magnetosphere. This indicates that the radial transport processes could occur via a double-reconnection process in the inner magnetosphere, while the radial transport processes appear to be more advective in the middle magnetosphere. Notice that Saturn's magnetosphere is stabilized by a radially increasing profile of flux tube entropy and destabilized by a radially decreasing profile of flux tube content. In this study, we also estimate the expected penetration location by using the flux tube interchange stability formalism developed by Southwood and Kivelson (1987, https://doi.org/10.1029/ja092ia01p00109). The results show that flux tube entropy can play a crucial role in braking the injections, while the flux tube content has a relatively smaller influence on the injected flux tube, being consistent with our previous case study by Wing et al. (2022, https://doi.org/10.3847/1538-4357/ac85b2).

Ma, Xuanye [Embry-Riddle Aeronautical University, ↗
DOE OSTI2022

$\alpha$-Clustering in atomic nuclei from first principles with statistical learning and the Hoyle state character

A long-standing crucial question with atomic nuclei is whether or not α clustering occurs there. An α particle (helium-4 nucleus) comprises two protons and two neutrons, and may be the building block of some nuclei. This is a very beautiful and fascinating idea, and is indeed plausible because the α particle is particularly stable with a large binding energy. However, direct experimental evidence has never been provided. Here, we show whether and how α(-like) objects emerge in atomic nuclei, by means of state-of-the-art quantum many-body simulations formulated from first principles, utilizing supercomputers including K/Fugaku. The obtained physical quantities exhibit agreement with experimental data. The appearance and variation of the α clustering are shown by utilizing density profiles for the nuclei beryllium-8, -10 and carbon-12. With additional insight by statistical learning, an unexpected crossover picture is presented for the Hoyle state, a critical gateway to the birth of life.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Electricity consumption variation versus economic structure during COVID-19 on metropolitan statistical areas in the US

The outbreak of novel coronavirus disease (COVID-19) has resulted in changes in productivity and daily life patterns, and as a result electricity consumption (EC) has also shifted. In this paper, we construct estimates of EC changes at the metropolitan level across the continental U.S., including total EC and residential EC during the initial two months of the pandemic. The total and residential data on the state level were broken down into the county level, and then metropolitan level EC estimates were aggregated from the counties included in each metropolitan statistical area (MSA). This work shows that the reduction in total EC is related to the shares of certain industries in an MSA, whereas regardless of the incidence level or economic structure, the residential sector shows a trend of increasing EC across the continental U.S. Since the MSAs account for 86% of the total population and 87% of the total EC of the continental U.S., the analytical result in this paper can provide important guidelines for future social-economic crises.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Identification of high-dielectric constant compounds from statistical design

Abstract The discovery of high-dielectric materials is crucial to increasing the efficiency of electronic devices and batteries. Here, we report three previously unexplored materials with very high dielectric constants (69 < ϵ < 101) and large band gaps (2.9 < E g (eV) < 5.5) obtained by screening materials databases using statistical optimization algorithms aided by artificial neural networks (ANN). Two of these new dielectrics are mixed-anion compounds (Eu 5 SiCl 6 O 4 and HoClO) and are shown to be thermodynamically stable against common semiconductors via phase diagram analysis. We also uncovered four other materials with relatively large dielectric constants (20 < ϵ < 40) and band gaps (2.3 < E g (eV) < 2.7). While the ANN training-data are obtained from the Materials Project, the search-space consists of materials from the Open Quantum Materials Database (OQMD)—demonstrating a successful implementation of cross-database materials design. Overall, we report the dielectric properties of 17 materials calculated using ab initio calculations, that were selected in our design workflow. The dielectric materials with high-dielectric properties predicted in this work open up further experimental research opportunities.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Error statistics and scalability of quantum error mitigation formulas

Quantum computing promises advantages over classical computing in many problems. Nevertheless, noise in quantum devices prevents most quantum algorithms from achieving the quantum advantage. Quantum error mitigation provides a variety of protocols to handle such noise using minimal qubit resources. While some of those protocols have been implemented in experiments for a few qubits, it remains unclear whether error mitigation will be effective in quantum circuits with tens to hundreds of qubits. In this paper, we apply statistics principles to quantum error mitigation and analyse the scaling behaviour of its intrinsic error. We find that the error increases linearly O(ϵN) with the gate number N before mitigation and sublinearly O(ϵ'N γ ) after mitigation, where γ ≈ 0.5, ϵ is the error rate of a quantum gate, and ϵ' is a protocol-dependent factor. The $\sqrt{N}$ scaling is a consequence of the law of large numbers, and it indicates that error mitigation can suppress the error by a larger factor in larger circuits. We propose the importance Clifford sampling as a key technique for error mitigation in large circuits to obtain this result.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Direct observation of anyonic braiding statistics

Anyons are quasiparticles that, unlike fermions and bosons, show fractional statistics when two of them are exchanged. Here, we report experimental observation of anyonic braiding statisticsfor the ν 1/3 fractional quantum Hall state using a device that is equivalent to a Fabry-Perot interferometer. Strong Aharonov-Bohm interference of the edge mode is punctuated by discrete phase slips that indicate an anyonic phase of $\theta$ anyon = 2π/3. Here, our results are consistent with a recent theory for an interferometer operated in a regime in which device charging energy is small compared to the energy of formation of charged quasiparticles, indicating that we have observed anyonic braiding.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Precision test of statistical dynamics with state-to-state ultracold chemistry

Chemical reactions represent a class of quantum problems that challenge both the current theoretical understanding and computational capabilities1. Reactions that occur at ultralow temperatures provide an ideal testing ground for quantum chemistry and scattering theories, because they can be experimentally studied with unprecedented control, yet display dynamics that are highly complex. Here we report the full product state distribution for the reaction 2KRb → K 2 + Rb 2 . Ultracold preparation of the reactants allows us complete control over their initial quantum degrees of freedom, whereas state-resolved, coincident detection of both products enables the probability of scattering into each of the 57 allowed rotational state-pairs to be measured. Our results show an overall agreement with a state-counting model based on statistical theory, but also reveal several deviating state-pairs. In particular, we observe a strong suppression of population in the state-pair closest to the exoergicity limit as a result of the long-range potential inhibiting the escape of products. Finally, the completeness of our measurements provides a benchmark for quantum dynamics calculations beyond the current state of the art.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Statistical study of ductility-dip cracking induced plastic deformation in polycrystalline laser 3D printed Ni-based superalloy

Ductility-dip cracking in Ni-based superalloy, resulting from heat treatment, is known to cause disastrous failure, but its mechanism is still not completely clear. A statistical study of the cracking behavior as a function of crystal orientation in a laser 3D-printed DL125L Ni-based superalloy polycrystal is investigated here using the synchrotron X-ray microdiffraction. The dislocation slip system in each of the forty crystal grains adjacent to the 300 μm long crack has been analyzed through Laue diffraction peak shapes. In all these grains, edge-type geometrically necessary dislocations (GNDs) dominate, and their dislocation line directions are almost parallel to the crack plane. Based on Schmid's law, the equivalent uniaxial tensile force direction is revealed normal to the trace of the crack. A qualitative mechanism is thus proposed. Thermal tensile stress perpendicular to the laser scanning direction is elevated due to a significant temperature gradient, and thus locations in the materials where the thermal stress exceeds the yield stress undergo plastic deformation mediated by GND activations. As the dislocations slip inside the crystal grains and pile up at the grain boundaries, local strain/stress keeps increasing, until the materials in these regions fail to sustain further deformation, leading to voids formation and cracks propagation.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Simulation of solute transport through heterogeneous networks: analysis using the method of moments and the statistics of local transport characteristics

We used a time domain random walk approach to simulate passive solute transport in networks. In individual pores, solute transport was modeled as a combination of Poiseuille flow and Taylor dispersion. The solute plume data were interpreted via the method of moments. Analysis of the first and second moments showed that the longitudinal dispersivity increased with increasing coefficient of variation of the pore radii CV and decreasing pore coordination number Z. The third moment was negative and its magnitude grew linearly with time, meaning that the simulated dispersion was intrinsically non-Fickian. The statistics of the Eulerian mean fluid velocities $\hat{u}_i$, the Taylor dispersion coefficients $\hat{D}_i$ and the transit times $\hat{t}_i$ were very complex and strongly affected by CV and Z. In particular, the probability of occurrence of negative velocities grew with increasing CV and decreasing Z. Hence, backward and forward transit times had to be distinguished. The high-τ branch of the transit-times probability curves had a power law form associated to non-Fickian behavior. However, the exponent was insensitive to pore connectivity, although variations of Z affected the third moment growth. Thus, we conclude that both the low- and high-τ branches played a role in generating the observed non-Fickian behavior.

Li, Min↗
DOE OSTI2018

Quantum work statistics, Loschmidt echo and information scrambling

A universal relation is established between the quantum work probability distribution of an isolated driven quantum system and the Loschmidt echo dynamics of a two-mode squeezed state. When the initial density matrix is canonical, the Loschmidt echo of the purified double thermofield state provides a direct measure of information scrambling and can be related to the analytic continuation of the partition function. Information scrambling is then described by the quantum work statistics associated with the time-reversal operation on a single copy, associated with the sudden negation of the system Hamiltonian.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Universal Quake Statistics: From Compressed Nanocrystals to Earthquakes

Slowly-compressed single crystals, bulk metallic glasses (BMGs), rocks, granular materials, and the earth all deform via intermittent slips or “quakes”. We find that although these systems span 12 decades in length scale, they all show the same scaling behavior for their slip size distributions and other statistical properties. Remarkably, the size distributions follow the same power law multiplied with the same exponential cutoff. The cutoff grows with applied force for materials spanning length scales from nanometers to kilometers. The tuneability of the cutoff with stress reflects “tuned critical” behavior, rather than self-organized criticality (SOC), which would imply stress-independence. A simple mean field model for avalanches of slipping weak spots explains the agreement across scales. It predicts the observed slip-size distributions and the observed stressdependent cutoff function. In conclusion, the results enable extrapolations from one scale to another, and from one force to another, across different materials and structures, from nanocrystals to earthquakes.

58 GEOSCIENCES↗
DOE OSTI2016

A Statistical Learning Framework for Materials Science: Application to Elastic Moduli of k -nary Inorganic Polycrystalline Compounds

Materials scientists increasingly employ machine or statistical learning (SL) techniques to accelerate materials discovery and design. Such pursuits benefit from pooling training data across, and thus being able to generalize predictions over, k -nary compounds of diverse chemistries and structures. This work presents a SL framework that addresses challenges in materials science applications, where datasets are diverse but of modest size, and extreme values are often of interest. Our advances include the application of power or Hölder means to construct descriptors that generalize over chemistry and crystal structure, and the incorporation of multivariate local regression within a gradient boosting framework. The approach is demonstrated by developing SL models to predict bulk and shear moduli (K and G, respectively) for polycrystalline inorganic compounds, using 1,940 compounds from a growing database of calculated elastic moduli for metals, semiconductors and insulators. The usefulness of the models is illustrated by screening for superhard materials.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Rapid acquisition of data dense solid-state CPMG NMR spectral sets using multi-dimensional statistical analysis

The development of multi-dimensional statistical methods has been demonstrated on variable contact time (VCT) 29 Si{ 1 H} cross-polarization magic angle spinning (CP/MAS) data sets collected using Carr–Purcell–Meiboom–Gill (CPMG) type acquisition. These methods utilize the transformation of the collected 2D VCT data set into a 3D data set and use tensor-rank decomposition to extract the spectral components that vary as a function of transverse relaxation time ( T 2 ) and CP contact time. The result is a data dense spectral set that can be used to reconstruct CP/MAS spectra at any contact time with a high signal to noise ratio and with an excellent agreement to 29 Si{ 1 H} CP/MAS spectra collected using conventional acquisition. These CPMG data can be collected in a fraction of time that would be required to collect a conventional VCT data set. Here, we demonstrate the method on samples of functionalized mesoporous silica materials and show that the method can provide valuable surface specific information about their functional chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗